Tootfinder

Bridging Language Gaps in Open-Source Documentation with Large-Language-Model Translation
Elijah Kayode Adejumo, Brittany Johnson, Mariam Guizani
https://arxiv.org/abs/2508.02497

Bridging Language Gaps in Open-Source Documentation with Large-Language-Model Translation
While open source communities attract diverse contributors globally, few repositories provide essential documentation in languages other than English. Large language models (LLMs) have demonstrated remarkable capabilities in software engineering tasks and translations across domains. However, little is known about LLM capabilities in translating open-source technical documentation, which mixes natural language, code, URLs, and markdown formatting. To understand the need and potential for LLMs i…

Bridging the Artificial Intelligence Governance Gap: The United States' and China's Divergent Approaches to Governing General-Purpose Artificial Intelligence
Oliver Guest, Kevin Wei
https://arxiv.org/abs/2506.03497

Bridging the Artificial Intelligence Governance Gap: The United States' and China's Divergent Approaches to Governing General-Purpose Artificial Intelligence
The United States and China are among the world's top players in the development of advanced artificial intelligence (AI) systems, and both are keen to lead in global AI governance and development. A look at U.S. and Chinese policy landscapes reveals differences in how the two countries approach the governance of general-purpose artificial intelligence (GPAI) systems. Three areas of divergence are notable for policymakers: the focus of domestic AI regulation, key principles of domestic AI regul…

Viele Menschen verstehen #Warnungen wie „#Hitzeindex“ oder „#Hitzewarnung“ falsch. Das zeigt eine US-Studie.
Fast die Hälfte hält den Hitzeindex für die reine

Bridging the Gap between National Weather Service Heat Terminology and Public Understanding
Abstract Clearly communicating heat warning information to the public is an important way to reduce heat mortality and morbidity. However, heat communication interventions from the National Weather Service commonly include technical and scientific terms, otherwise known as jargon. These terms, such as heat advisory or heat index, may not be understood by the public. Given the importance of message understanding in protective action decision-making, the purpose of this study is to assess how the…

Bridging the Silos of Digitalization and Sustainability by Twin Transition: A Multivocal Literature Review
Baran Shajari, Istvan David
https://arxiv.org/abs/2506.04267

Bridging the Silos of Digitalization and Sustainability by Twin Transition: A Multivocal Literature Review
Twin transition is the method of parallel digital and sustainability transitions in a mutually supporting way or, in common terms, "greening of and by IT and data." Twin transition reacts to the growing problem of unsustainable digitalization, particularly in the ecological sense. Ignoring this problem will eventually limit the digital adeptness of society and the problem-solving capacity of humankind. Information systems engineering must find ways to support twin transition journeys through it…

This https://arxiv.org/abs/2505.22990 has been replaced.
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MenTeR: A fully-automated Multi-agenT workflow for end-to-end RF/Analog Circuits Netlist Design
RF/Analog design is essential for bridging digital technologies with real-world signals, ensuring the functionality and reliability of a wide range of electronic systems. However, analog design procedures are often intricate, time-consuming and reliant on expert intuition, and hinder the time and cost efficiency of circuit development. To overcome the limitations of the manual circuit design, we introduce MenTeR - a multiagent workflow integrated into an end-to-end analog design framework. By e…

DigiT4TAF -- Bridging Physical and Digital Worlds for Future Transportation Systems
Maximilian Zipfl, Pascal Zwick, Patrick Schulz, Marc Rene Zofka, Albert Schotschneider, Helen Gremmelmaier, Nikolai Polley, Ferdinand M\"utsch, Kevin Simon, Fabian Gottselig, Michael Frey, Sergio Marschall, Akim Stark, Maximilian M\"uller, Marek Wehmer, Mihai Kocsis, Dominic Waldenmayer, Florian Schnepf, Erik Heinrich, Sabrina Pletz, Matthias K\"olle, Karin Langbein-Euchner, Alexander Vie…

DigiT4TAF -- Bridging Physical and Digital Worlds for Future Transportation Systems
In the future, mobility will be strongly shaped by the increasing use of digitalization. Not only will individual road users be highly interconnected, but also the road and associated infrastructure. At that point, a Digital Twin becomes particularly appealing because, unlike a basic simulation, it offers a continuous, bilateral connection linking the real and virtual environments. This paper describes the digital reconstruction used to develop the Digital Twin of the Test Area Autonomous Drivi…

Bridging Global Frameworks: Governance Strategies Behind Cisco Common Control Framework v4.0 for Scalable Cloud Compliance
Nishant Sonkar
https://arxiv.org/abs/2506.01984

Bridging Global Frameworks: Governance Strategies Behind Cisco Common Control Framework v4.0 for Scalable Cloud Compliance
CCF v4.0 provides a standard way to ensure that Cisco's cloud products comply with the many quickly evolving requirements worldwide. To cope with increasing demands brought by ISO 27001, SOC 2, NIST, FedRAMP, EU CRA, DORA, and NIS2, CCF v4.0 introduces reliable governance by grouping controls using modules mapped across many frameworks. In this document, I discuss the governance structure controlling the framework's progress, noting how the CAB helped and the relevant steps for mapping and vali…

This https://arxiv.org/abs/2505.16133 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csIR_…

HASH-RAG: Bridging Deep Hashing with Retriever for Efficient, Fine Retrieval and Augmented Generation
Retrieval-Augmented Generation (RAG) encounters efficiency challenges when scaling to massive knowledge bases while preserving contextual relevance. We propose Hash-RAG, a framework that integrates deep hashing techniques with systematic optimizations to address these limitations. Our queries directly learn binary hash codes from knowledgebase code, eliminating intermediate feature extraction steps, and significantly reducing storage and computational overhead. Building upon this hash-based eff…

Sad to hear that Maggie Boden has passed away. Her work on creativity e.g. her book "The Creative Mind" framed much of my work when I was a research student, bridging philosophy, psychology and computer science.
https://staff.sussex.ac.uk/news/articl

An effective analytic recurrence for prime numbers: from asymptotics to explicit bounds
Benoit Cloitre
https://arxiv.org/abs/2508.02690 https://arxiv.org/p…

An effective analytic recurrence for prime numbers: from asymptotics to explicit bounds
We present an explicit and effective recurrence formula for prime numbers, bridging arithmetic and analytic approaches. Building upon foundational work by Gandhi (1971), Golomb (1976), and Keller (2007), we establish the effective bound $s_n \le 2p_n$ for all $n \ge 1$ within the Golomb-Keller analytic recurrence. This transforms their asymptotic formula into an explicit recurrence using twice the n-th prime as the exponent: $$ p_{n+1} = \left\lceil \left( -1 + ζ(2p_n) \prod_{j=1}^{n} \left(1 …

This https://arxiv.org/abs/2501.11669 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_…

Bridging the Gap: OPTICAM Reveals the Hidden Spin of the WZ Sge Star GOTO 065054.49+593624.51
WZ Sge stars are highly evolved accreting white dwarf systems (AWDs) exhibiting remarkably large amplitude outbursts (a.k.a. super-outbursts), typically followed by short rebrightenings/echo outbursts. These systems have some of the lowest mass transfer rates among AWDs, making even low magnetic fields dynamically important. Such magnetic fields are often invoked to explain the phenomenology observed in these systems, such as their X-ray luminosity and long periods of quiescence (30+ years). Ho…

MiCoTA: Bridging the Learnability Gap with Intermediate CoT and Teacher Assistants
Dongyi Ding, Tiannan Wang, Chenghao Zhu, Meiling Tao, Yuchen Eleanor Jiang, Wangchunshu Zhou
https://arxiv.org/abs/2507.01887

MiCoTA: Bridging the Learnability Gap with Intermediate CoT and Teacher Assistants
Large language models (LLMs) excel at reasoning tasks requiring long thought sequences for planning, reflection, and refinement. However, their substantial model size and high computational demands are impractical for widespread deployment. Yet, small language models (SLMs) often struggle to learn long-form CoT reasoning due to their limited capacity, a phenomenon we refer to as the "SLMs Learnability Gap". To address this, we introduce \textbf{Mi}d-\textbf{Co}T \textbf{T}eacher \textbf{A}ssist…

Bridging Service Design, Visualizations, and Visual Analytics in Healthcare Digital Twins: Challenges, Gaps, and Research Opportunities
Mariia Ershova, Graziano Blasilli
https://arxiv.org/abs/2506.24104

Bridging Service Design, Visualizations, and Visual Analytics in Healthcare Digital Twins: Challenges, Gaps, and Research Opportunities
Digital twins (DT) are increasingly used in healthcare to model patients, processes, and physiological systems. While recent solutions leverage visualization, visual analytics, and user interaction, these systems rarely incorporate structured service design methodologies. Bridging service design with visual analytics and visualization can be valuable for the healthcare DT community. This paper aims to introduce the service design discipline to visualization researchers by framing this integrati…

A Framework Leveraging Large Language Models for Autonomous UAV Control in Flying Networks
Diana Nunes, Ricardo Amorim, Pedro Ribeiro, Andr\'e Coelho, Rui Campos
https://arxiv.org/abs/2506.04404

A Framework Leveraging Large Language Models for Autonomous UAV Control in Flying Networks
This paper proposes FLUC, a modular framework that integrates open-source Large Language Models (LLMs) with Unmanned Aerial Vehicle (UAV) autopilot systems to enable autonomous control in Flying Networks (FNs). FLUC translates high-level natural language commands into executable UAV mission code, bridging the gap between operator intent and UAV behaviour. FLUC is evaluated using three open-source LLMs - Qwen 2.5, Gemma 2, and LLaMA 3.2 - across scenarios involving code generation and mission …

This https://arxiv.org/abs/2501.09567 has been replaced.
initial toot: https://mastoxiv.page/@arX…

Bridging conformal field theory and parton approaches to SU(n)_k chiral spin liquids
We employ the $\mathrm{SU}(n)_k$ Wess-Zumino-Witten (WZW) model in conformal field theory to construct lattice wave functions in both one and two dimensions. The spins on all lattice sites are chosen to transform under the $\mathrm{SU}(n)$ irreducible representation with a single row and $k$ boxes in the Young tableau. It is demonstrated that the wave functions can be reinterpreted as parton states, which enables efficient conversion to matrix product states such that many physical properties c…

Hierarchical Multi-Label Contrastive Learning for Protein-Protein Interaction Prediction Across Organisms
Shiyi Liu, Buwen Liang, Yuetong Fang, Zixuan Jiang, Renjing Xu
https://arxiv.org/abs/2507.02724

Hierarchical Multi-Label Contrastive Learning for Protein-Protein Interaction Prediction Across Organisms
Recent advances in AI for science have highlighted the power of contrastive learning in bridging heterogeneous biological data modalities. Building on this paradigm, we propose HIPPO (HIerarchical Protein-Protein interaction prediction across Organisms), a hierarchical contrastive framework for protein-protein interaction(PPI) prediction, where protein sequences and their hierarchical attributes are aligned through multi-tiered biological representation matching. The proposed approach incorpora…

Bridging Classical and Learning-based Iterative Registration through Deep Equilibrium Models
Yi Zhang, Yidong Zhao, Qian Tao
https://arxiv.org/abs/2507.00582

Bridging Classical and Learning-based Iterative Registration through Deep Equilibrium Models
Deformable medical image registration is traditionally formulated as an optimization problem. While classical methods solve this problem iteratively, recent learning-based approaches use recurrent neural networks (RNNs) to mimic this process by unrolling the prediction of deformation fields in a fixed number of steps. However, classical methods typically converge after sufficient iterations, but learning-based unrolling methods lack a theoretical convergence guarantee and show instability empir…

This https://arxiv.org/abs/2402.12208 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

Language-Codec: Bridging Discrete Codec Representations and Speech Language Models
In recent years, large language models have achieved significant success in generative tasks related to speech, audio, music, and other signal domains. A crucial element of these models is the discrete acoustic codecs, which serve as an intermediate representation replacing the mel-spectrogram. However, there exist several gaps between discrete codecs and downstream speech language models. Specifically, 1) Due to the reconstruction paradigm of the Codec model and the structure of residual vecto…

Bridging Physical and Digital Worlds: Embodied Large AI for Future Wireless Systems
Xinquan Wang, Fenghao Zhu, Zhaohui Yang, Chongwen Huang, Xiaoming Chen, Zhaoyang Zhang, Sami Muhaidat, M\'erouane Debbah
https://arxiv.org/abs/2506.24009

Bridging Physical and Digital Worlds: Embodied Large AI for Future Wireless Systems
Large artificial intelligence (AI) models offer revolutionary potential for future wireless systems, promising unprecedented capabilities in network optimization and performance. However, current paradigms largely overlook crucial physical interactions. This oversight means they primarily rely on offline datasets, leading to difficulties in handling real-time wireless dynamics and non-stationary environments. Furthermore, these models often lack the capability for active environmental probing. …

This https://arxiv.org/abs/2505.20730 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csIR_…

What LLMs Miss in Recommendations: Bridging the Gap with Retrieval-Augmented Collaborative Signals
User-item interactions contain rich collaborative signals that form the backbone of many successful recommender systems. While recent work has explored the use of large language models (LLMs) for recommendation, it remains unclear whether LLMs can effectively reason over this type of collaborative information. In this paper, we conduct a systematic comparison between LLMs and classical matrix factorization (MF) models to assess LLMs' ability to leverage user-item interaction data. We further in…

Bridging Synthetic and Real-World Domains: A Human-in-the-Loop Weakly-Supervised Framework for Industrial Toxic Emission Segmentation
Yida Tao, Yen-Chia Hsu
https://arxiv.org/abs/2507.22002

Bridging Synthetic and Real-World Domains: A Human-in-the-Loop Weakly-Supervised Framework for Industrial Toxic Emission Segmentation
Industrial smoke segmentation is critical for air-quality monitoring and environmental protection but is often hampered by the high cost and scarcity of pixel-level annotations in real-world settings. We introduce CEDANet, a human-in-the-loop, class-aware domain adaptation framework that uniquely integrates weak, citizen-provided video-level labels with adversarial feature alignment. Specifically, we refine pseudo-labels generated by a source-trained segmentation model using citizen votes, and …

The approach of cluster symmetry to Diophantine equations
Leizhen Bao, Fang Li
https://arxiv.org/abs/2508.02005 https://arxiv.org/pdf/2508.02005

The approach of cluster symmetry to Diophantine equations
This paper aims to use a cluster-theoretic approach to give a kind of Diophantine equation whose solutions can be obtained by starting from initial solutions through mutations. We establish a novel framework bridging cluster theory and Diophantine equations through the lens of cluster symmetry. On the one hand, we give the necessary and sufficient condition for Laurent polynomials to remain invariant under a given cluster symmetric map. On the other hand, we construct a discriminant algorithm…

Proxy Target: Bridging the Gap Between Discrete Spiking Neural Networks and Continuous Control
Zijie Xu, Tong Bu, Zecheng Hao, Jianhao Ding, Zhaofei Yu
https://arxiv.org/abs/2505.24161

Proxy Target: Bridging the Gap Between Discrete Spiking Neural Networks and Continuous Control
Spiking Neural Networks (SNNs) offer low-latency and energy-efficient decision making through neuromorphic hardware, making them compelling for Reinforcement Learning (RL) in resource-constrained edge devices. Recent studies in this field directly replace Artificial Neural Networks (ANNs) by SNNs in existing RL frameworks, overlooking whether the RL algorithm is suitable for SNNs. However, most RL algorithms in continuous control are designed tailored to ANNs, including the target network soft …

Bridging Unstratified and Stratified Simulations of the Streaming Instability for $\tau_s=0.1$ Grains
Jeonghoon Lim, Stanley A. Baronett, Jacob B. Simon, Chao-Chin Yang, Debanjan Sengupta, Orkan M. Umurhan, Wladimir Lyra
https://arxiv.org/abs/2505.23902

Bridging Unstratified and Stratified Simulations of the Streaming Instability for $τ_s=0.1$ Grains
The streaming instability (SI), driven by aerodynamic coupling between solids and the gas under a global radial pressure gradient, concentrates solids and facilitates planetesimal formation. Unstratified simulations are commonly used to study the SI, based on the assumption that they approximate conditions near the disk midplane. However, it remains unclear how accurately these unstratified simulations capture the midplane dust-gas dynamics in stratified disks. To address this, we examine the s…

Higher-Order Automatic Differentiation Using Symbolic Differential Algebra: Bridging the Gap between Algorithmic and Symbolic Differentiation
He Zhang
https://arxiv.org/abs/2506.00796

Higher-Order Automatic Differentiation Using Symbolic Differential Algebra: Bridging the Gap between Algorithmic and Symbolic Differentiation
In scientific computation, it is often necessary to calculate higher-order derivatives of a function. Currently, two primary methods for higher-order automatic differentiation exist: symbolic differentiation and algorithmic automatic differentiation (AD). Differential Algebra (DA) is a mathematical technique widely used in beam dynamics analysis and simulations of particle accelerators, and it also functions as an algorithmic automatic differentiation method. DA automatically computes the Taylo…

At the Semantic Digital Humanities 2025 Workshop, Jose Maldonado-Rodríguez is presenting "Natural Language Querying for Humanities #KnowledgeGraphs A case study on the GOLEM KG". Main contribution is a bilingual dataset (English-Spanish) specifically designed to evaluate automatic text-to-SPARQL translation systems for GOLEM, a specialized humanities KG.
paper:

Bridging UI Design and chatbot Interactions: Applying Form-Based Principles to Conversational Agents
Sanjay Krishna Anbalagan, Xinrui Nie, Umesh Mohan, Vijay Kumar Kanamarlapudi, Anughna Kommalapati, Xiaodan Zhao
https://arxiv.org/abs/2507.01862

Bridging UI Design and chatbot Interactions: Applying Form-Based Principles to Conversational Agents
Domain specific chatbot applications often involve multi step interactions, such as refining search filters, selecting multiple items, or performing comparisons. Traditional graphical user interfaces (GUIs) handle these workflows by providing explicit "Submit" (commit data) and "Reset" (discard data) actions, allowing back-end systems to track user intent unambiguously. In contrast, conversational agents rely on subtle language cues, which can lead to confusion and incomplete context management…

This https://arxiv.org/abs/2410.09510 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csDL_…

SciEvo: A 2 Million, 30-Year Cross-disciplinary Dataset for Temporal Scientometric Analysis
Understanding the creation, evolution, and dissemination of scientific knowledge is crucial for bridging diverse subject areas and addressing complex global challenges such as pandemics, climate change, and ethical AI. Scientometrics, the quantitative and qualitative study of scientific literature, provides valuable insights into these processes. We introduce SciEvo, a longitudinal scientometric dataset with over two million academic publications, providing comprehensive contents information an…

Wide Reflective Equilibrium in LLM Alignment: Bridging Moral Epistemology and AI Safety
Matthew Brophy
https://arxiv.org/abs/2506.00415 https://

Wide Reflective Equilibrium in LLM Alignment: Bridging Moral Epistemology and AI Safety
As large language models (LLMs) become more powerful and pervasive across society, ensuring these systems are beneficial, safe, and aligned with human values is crucial. Current alignment techniques, like Constitutional AI (CAI), involve complex iterative processes. This paper argues that the Method of Wide Reflective Equilibrium (MWRE) -- a well-established coherentist moral methodology -- offers a uniquely apt framework for understanding current LLM alignment efforts. Moreover, this methodolo…

This https://arxiv.org/abs/2505.04825 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_…

SHELLQs. Bridging the gap: JWST unveils obscured quasars in the most luminous galaxies at z > 6
The unprecedented sensitivity of the James Webb Space Telescope (JWST) has uncovered a surprisingly abundant population of mildly obscured, low-luminosity active galactic nuclei (AGNs) in the epoch of reionization (EoR). However, the link between these objects and classical unobscured quasars remains a mystery. Here we report the discovery of obscured quasars hosted by the most luminous galaxies at $z > 6$, possibly bridging the gap between the two AGN populations. The 13 objects presented here…

Bridging CGR and $k$-mer Frequencies of DNA
Haoze He, Lila Kari, Pablo Millan Arias
https://arxiv.org/abs/2506.22172 https://arxiv.or…

Bridging CGR and $k$-mer Frequencies of DNA
This paper establishes formal mathematical foundations linking Chaos Game Representations (CGR) of DNA sequences to their underlying $k$-mer frequencies. We prove that the Frequency CGR (FCGR) of order $k$ is mathematically equivalent to a discretization of CGR at resolution $2^k \times 2^k$, and its vectorization corresponds to the $k$-mer frequencies of the sequence. Additionally, we characterize how symmetry transformations of CGR images correspond to specific nucleotide permutations in the …

Investigating the emergent invariant properties of Hungarian electric distribution networks
Michelle T. Cirunay, B\'alint Hartmann, T\'imea Erdei, Tam\'as Soha
https://arxiv.org/abs/2506.04009

Investigating the emergent invariant properties of Hungarian electric distribution networks
Electric power distribution networks serve as the final and essential stage in power delivery, bridging transmission infrastructure and end users. The structural configuration of these networks plays a critical role in determining system reliability, fault tolerance, and operational efficiency. Although the design of distribution systems is influenced by various regional factors, such as geography, customer density, and planning standards, the extent to which consistent structural characteristi…

This https://arxiv.org/abs/2505.23581 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qu…

Quantum Hilbert Transform
The Hilbert transform has been one of the foundational transforms in signal processing, finding it's way into multiple disciplines from cryptography to biomedical sciences. However, there does not exist any quantum analogue for the Hilbert transform. In this work, we introduce a formulation for the quantum Hilbert transform (QHT)and apply it to a quantum steganography protocol. By bridging classical phase-shift techniques with quantum operations, QHT opens new pathways in quantum signal process…

Bridging Subjective and Objective QoE: Operator-Level Aggregation Using LLM-Based Comment Analysis and Network MOS Comparison
Parsa Hassani Shariat Panahi, Amir Hossein Jalilvand, M. Hasan Najafi
https://arxiv.org/abs/2506.00924

Bridging Subjective and Objective QoE: Operator-Level Aggregation Using LLM-Based Comment Analysis and Network MOS Comparison
This paper introduces a dual-layer framework for network operator-side quality of experience (QoE) assessment that integrates both objective network modeling and subjective user perception extracted from live-streaming platforms. On the objective side, we develop a machine learning model trained on mean opinion scores (MOS) computed via the ITU-T P.1203 reference implementation, allowing accurate prediction of user-perceived video quality using only network parameters such as packet loss, delay…

Bridging Ethical Principles and Algorithmic Methods: An Alternative Approach for Assessing Trustworthiness in AI Systems
Michael Papademas, Xenia Ziouvelou, Antonis Troumpoukis, Vangelis Karkaletsis
https://arxiv.org/abs/2506.22774

Bridging Ethical Principles and Algorithmic Methods: An Alternative Approach for Assessing Trustworthiness in AI Systems
Artificial Intelligence (AI) technology epitomizes the complex challenges posed by human-made artifacts, particularly those widely integrated into society and exert significant influence, highlighting potential benefits and their negative consequences. While other technologies may also pose substantial risks, AI's pervasive reach makes its societal effects especially profound. The complexity of AI systems, coupled with their remarkable capabilities, can lead to a reliance on technologies that o…

Bridging Cloud Convenience and Protocol Transparency: A Hybrid Architecture for Ethereum Node Operations on Amazon Managed Blockchain
S M Mostaq Hossain, Amani Altarawneh, Maanak Gupta
https://arxiv.org/abs/2507.18774

Bridging Cloud Convenience and Protocol Transparency: A Hybrid Architecture for Ethereum Node Operations on Amazon Managed Blockchain
As blockchain technologies are increasingly adopted in enterprise and research domains, the need for secure, scalable, and performance-transparent node infrastructure has become critical. While self-hosted Ethereum nodes offer operational control, they often lack elasticity and require complex maintenance. This paper presents a hybrid, service-oriented architecture for deploying and monitoring Ethereum full nodes using Amazon Managed Blockchain (AMB), integrated with EC2-based observability, IA…

Bridging the Gap Between Semantic and User Preference Spaces for Multi-modal Music Representation Learning
Xiaofeng Pan, Jing Chen, Haitong Zhang, Menglin Xing, Jiayi Wei, Xuefeng Mu, Zhongqian Xie
https://arxiv.org/abs/2505.23298

Bridging the Gap Between Semantic and User Preference Spaces for Multi-modal Music Representation Learning
Recent works of music representation learning mainly focus on learning acoustic music representations with unlabeled audios or further attempt to acquire multi-modal music representations with scarce annotated audio-text pairs. They either ignore the language semantics or rely on labeled audio datasets that are difficult and expensive to create. Moreover, merely modeling semantic space usually fails to achieve satisfactory performance on music recommendation tasks since the user preference spac…

Physics-Informed Neural Networks: Bridging the Divide Between Conservative and Non-Conservative Equations
Arun Govind Neelan, Ferdin Sagai Don Bosco, Naveen Sagar Jarugumalli, Suresh Balaji Vedarethinam
https://arxiv.org/abs/2506.22413

Physics-Informed Neural Networks: Bridging the Divide Between Conservative and Non-Conservative Equations
In the realm of computational fluid dynamics, traditional numerical methods, which heavily rely on discretization, typically necessitate the formulation of partial differential equations (PDEs) in conservative form to accurately capture shocks and other discontinuities in compressible flows. Conversely, utilizing non-conservative forms often introduces significant errors near these discontinuities or results in smeared shocks. This dependency poses a considerable limitation, particularly as man…

Bridging the Gap: From Ad-hoc to Proactive Search in Conversations
Chuan Meng, Francesco Tonolini, Fengran Mo, Nikolaos Aletras, Emine Yilmaz, Gabriella Kazai
https://arxiv.org/abs/2506.00983

Bridging the Gap: From Ad-hoc to Proactive Search in Conversations
Proactive search in conversations (PSC) aims to reduce user effort in formulating explicit queries by proactively retrieving useful relevant information given conversational context. Previous work in PSC either directly uses this context as input to off-the-shelf ad-hoc retrievers or further fine-tunes them on PSC data. However, ad-hoc retrievers are pre-trained on short and concise queries, while the PSC input is longer and noisier. This input mismatch between ad-hoc search and PSC limits retr…

Bridging the Narrative Divide: Cross-Platform Discourse Networks in Fragmented Ecosystems
Patrick Gerard, Hans W. A. Hanley, Luca Luceri, Emilio Ferrara
https://arxiv.org/abs/2505.21729

Bridging the Narrative Divide: Cross-Platform Discourse Networks in Fragmented Ecosystems
Political discourse has grown increasingly fragmented across different social platforms, making it challenging to trace how narratives spread and evolve within such a fragmented information ecosystem. Reconstructing social graphs and information diffusion networks is challenging, and available strategies typically depend on platform-specific features and behavioral signals which are often incompatible across systems and increasingly restricted. To address these challenges, we present a platform…

This https://arxiv.org/abs/2409.02188 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_grqc_…

Stochastic dark matter: Covariant Brownian motion from Planckian discreteness
Quantum gravity has long remained elusive from an observational standpoint. Developing effective cosmological models motivated by the fundamental aspects of quantum gravity is crucial for bridging theory with observations. One key aspect is the granularity of spacetime, which suggests that free particles would deviate from classical geodesics by following a covariant Brownian motion. This notion is further supported by swerves models in causal set theory, a discrete approach to quantum gravity.…

Bridging the Gap: Enhancing Digital Accessibility for Medicaid Populations in Telehealth Adoption
Vishnu Ramineni, Aditya Gupta, Balakrishna Pothineni, Isan Sahoo, Shivareddy Devarapalli, Balaji Shesharao Ingole
https://arxiv.org/abs/2505.24035

Bridging the Gap: Enhancing Digital Accessibility for Medicaid Populations in Telehealth Adoption
The swift evolution of telehealth has revolutionized how medical professionals deliver healthcare services and boost convenience and accessibility. Yet, the Medicaid population encounters several impediments in utilizing facilities especially owing to poor internet connectivity, less awareness about digital platforms, and a shortage of assistive technologies. The paper aims to explicate key factors behind digital accessibility for Medicaid populations and expounds robust solutions to eradicate …

Singularity Protocol for Cross Chain AMM without Intermediate Tokens or Bridges
Sumit Vohra
https://arxiv.org/abs/2505.24337 https://…

Singularity Protocol for Cross Chain AMM without Intermediate Tokens or Bridges
Automated Market Makers (AMMs) are decentralized exchange protocols that provide continuous access to token liquidity without the need for order books or traditional market makers. However, this innovation has failed to scale when it comes to cross-chain swaps. Modern cross-chain swaps employ double-sided AMMs, which are not only inefficient due to liquidity fragmentation but also require an intermediate token. This introduces inherent volatility risk as well as blockchain and bridging risk, es…

SiPipe: Bridging the CPU-GPU Utilization Gap for Efficient Pipeline-Parallel LLM Inference
Yongchao He, Bohan Zhao, Zheng Cao
https://arxiv.org/abs/2506.22033

SiPipe: Bridging the CPU-GPU Utilization Gap for Efficient Pipeline-Parallel LLM Inference
As inference workloads for large language models (LLMs) scale to meet growing user demand, pipeline parallelism (PP) has become a widely adopted strategy for multi-GPU deployment, particularly in cross-node setups, to improve key-value (KV) cache capacity and inference throughput. However, PP suffers from inherent inefficiencies caused by three types of execution bubbles-load-imbalance, intra-stage, and inter-stage-which limit pipeline saturation. We present SiPipe, a heterogeneous pipeline des…

Bridging Classical Molecular Dynamics and Quantum Foundations for Comprehensive Protein Structural Analysis
Don Roosan, Rubayat Khan, Tiffany Khou, Saif Nirzhor, Fahmida Hai, Brian Provencher
https://arxiv.org/abs/2506.20830

Bridging Classical Molecular Dynamics and Quantum Foundations for Comprehensive Protein Structural Analysis
The objective of this paper is to investigate the structural stability, dynamic properties, and potential interactions among Amyloid Precursor Protein (APP), Tau, and Alpha-synuclein through a series of molecular dynamics simulations that integrate publicly available structural data, detailed force-field parameters, and comprehensive analytical protocols. By focusing on these three proteins, which are each implicated in various neurodegenerative disorders, the study aims to elucidate how their …

FreNBRDF: A Frequency-Rectified Neural Material Representation
Chenliang Zhou, Zheyuan Hu, Cengiz Oztireli
https://arxiv.org/abs/2507.00476 https://…

FreNBRDF: A Frequency-Rectified Neural Material Representation
Accurate material modeling is crucial for achieving photorealistic rendering, bridging the gap between computer-generated imagery and real-world photographs. While traditional approaches rely on tabulated BRDF data, recent work has shifted towards implicit neural representations, which offer compact and flexible frameworks for a range of tasks. However, their behavior in the frequency domain remains poorly understood. To address this, we introduce FreNBRDF, a frequency-rectified neural material…

💡 Wie werden die Querverbindungen zwischen kulturellen Ressourcen in @… hergestellt?
🚀 Bei der #DH2025 in Lissabon zeigen unsere 4Culture-Kolleginnen @… und Linnaea Sö…

Smooth Reading: Bridging the Gap of Recurrent LLM to Self-Attention LLM on Long-Context Tasks
Kai Liu, Zhan Su, Peijie Dong, Fengran Mo, Jianfei Gao, ShaoTing Zhang, Kai Chen
https://arxiv.org/abs/2507.19353

Smooth Reading: Bridging the Gap of Recurrent LLM to Self-Attention LLM on Long-Context Tasks
Recently, recurrent large language models (Recurrent LLMs) with linear computational complexity have re-emerged as efficient alternatives to self-attention-based LLMs (Self-Attention LLMs), which have quadratic complexity. However, Recurrent LLMs often underperform on long-context tasks due to their limited fixed-size memory. Previous research has primarily focused on enhancing the memory capacity of Recurrent LLMs through architectural innovations, but these approaches have not yet enabled Rec…

Subordinacy theory for long-range operators: hyperbolic geodesic flow insights and monotonicity theory
Zhenfu Wang, Disheng Xu, Qi Zhou
https://arxiv.org/abs/2506.23098

Subordinacy theory for long-range operators: hyperbolic geodesic flow insights and monotonicity theory
We introduce a comprehensive framework for subordinacy theory applicable to long-range operators on $\ell^2(\mathbb Z)$, bridging dynamical systems and spectral analysis. For finite-range operators, we establish a correspondence between the dynamical behavior of partially hyperbolic (Hermitian-)symplectic cocycles and the existence of purely absolutely continuous spectrum, resolving an open problem posed by Jitomirskaya. For infinite-range operators-where traditional cocycle methods become inap…

“The String… will be much faster”
my brain is breaking https://mastodon.social/@Catfish_Man/114655168110161214

Bridging Unsupervised and Semi-Supervised Anomaly Detection: A Theoretically-Grounded and Practical Framework with Synthetic Anomalies
Matthew Lau, Tian-Yi Zhou, Xiangchi Yuan, Jizhou Chen, Wenke Lee, Xiaoming Huo
https://arxiv.org/abs/2506.13955

Bridging Unsupervised and Semi-Supervised Anomaly Detection: A Theoretically-Grounded and Practical Framework with Synthetic Anomalies
Anomaly detection (AD) is a critical task across domains such as cybersecurity and healthcare. In the unsupervised setting, an effective and theoretically-grounded principle is to train classifiers to distinguish normal data from (synthetic) anomalies. We extend this principle to semi-supervised AD, where training data also include a limited labeled subset of anomalies possibly present in test time. We propose a theoretically-grounded and empirically effective framework for semi-supervised AD t…

This https://arxiv.org/abs/2307.07385 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csGT_…

Partial Allocations in Budget-Feasible Mechanism Design: Bridging Multiple Levels of Service and Divisible Agents
Budget-feasible procurement has been a major paradigm in mechanism design since its introduction by Singer (2010). An auctioneer (buyer) with a strict budget constraint is interested in buying goods or services from a group of strategic agents (sellers). In many scenarios it makes sense to allow the auctioneer to only partially buy what an agent offers, e.g., an agent might have multiple copies of an item to sell, they might offer multiple levels of a service, or they may be available to perfor…

Learning Steerable Imitation Controllers from Unstructured Animal Motions
Dongho Kang, Jin Cheng, Fatemeh Zargarbashi, Taerim Yoon, Sungjoon Choi, Stelian Coros
https://arxiv.org/abs/2507.00677

Learning Steerable Imitation Controllers from Unstructured Animal Motions
This paper presents a control framework for legged robots that leverages unstructured real-world animal motion data to generate animal-like and user-steerable behaviors. Our framework learns to follow velocity commands while reproducing the diverse gait patterns in the original dataset. To begin with, animal motion data is transformed into a robot-compatible database using constrained inverse kinematics and model predictive control, bridging the morphological and physical gap between the animal…

This https://arxiv.org/abs/2502.18710 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qbi…

Bridging Critical Gaps in Convergent Learning: How Representational Alignment Evolves Across Layers, Training, and Distribution Shifts
Understanding convergent learning -- the degree to which independently trained neural systems -- whether multiple artificial networks or brains and models -- arrive at similar internal representations -- is crucial for both neuroscience and AI. Yet, the literature remains narrow in scope -- typically examining just a handful of models with one dataset, relying on one alignment metric, and evaluating networks at a single post-training checkpoint. We present a large-scale audit of convergent lear…

Towards Explainable Sequential Learning
Giacomo Bergami, Emma Packer, Kirsty Scott, Silvia Del Din
https://arxiv.org/abs/2505.23624 https://

Towards Explainable Sequential Learning
This paper offers a hybrid explainable temporal data processing pipeline, DataFul Explainable MultivariatE coRrelatIonal Temporal Artificial inTElligence (EMeriTAte+DF), bridging numerical-driven temporal data classification with an event-based one through verified artificial intelligence principles, enabling human-explainable results. This was possible through a preliminary a posteriori explainable phase describing the numerical input data in terms of concurrent constituents with numerical pay…

Yue-Sai Kan is a Chinese-American television host, producer, author, entrepreneur and humanitarian. Renowned for her work in bridging the gap between China and the United States, she has been nicknamed "The Oprah of China". People, The Observer and ABS News have called her "the most famous woman in China".

Bridging Fitness With Search Spaces By Fitness Supremums: A Theoretical Study on LGP
Zhixing Huang, Yi Mei, Fangfang Zhang, Mengjie Zhang, Wolfgang Banzhaf
https://arxiv.org/abs/2505.21991

Bridging Fitness With Search Spaces By Fitness Supremums: A Theoretical Study on LGP
Genetic programming has undergone rapid development in recent years. However, theoretical studies of genetic programming are far behind. One of the major obstacles to theoretical studies is the challenge of developing a model to describe the relationship between fitness values and program genotypes. In this paper, we take linear genetic programming (LGP) as an example to study the fitness-to-genotype relationship. We find that the fitness expectation increases with fitness supremum over instruc…

Detection of pure warm-hot #IntergalacticMedium emission from a 7.2 Mpc long filament in the Shapley supercluster using X-ray spectroscopy: https://www.aanda.org/articles/aa/full_html/2025/06/aa54944-25/aa54944-25.html -> Astronomers have discovered a huge filament of hot gas bridging four galaxy clusters: https://www.esa.int/Science_Exploration/Space_Science/XMM-Newton/The_models_were_right_astronomers_find_missing_matter - at 10 times as massive as our galaxy, the thread could contain some of the Universe’s ‘missing’ matter, addressing a decades-long mystery.

Bridging Data-Driven and Physics-Based Models: A Consensus Multi-Model Kalman Filter for Robust Vehicle State Estimation
Farid Mafi (University of Waterloo, Waterloo, Canada), Ladan Khoshnevisan (University of Waterloo, Waterloo, Canada), Mohammad Pirani (University of Ottawa, Ottawa, Canada), Amir Khajepour (University of Waterloo, Waterloo, Canada)

Bridging Data-Driven and Physics-Based Models: A Consensus Multi-Model Kalman Filter for Robust Vehicle State Estimation
Vehicle state estimation presents a fundamental challenge for autonomous driving systems, requiring both physical interpretability and the ability to capture complex nonlinear behaviors across diverse operating conditions. Traditional methodologies often rely exclusively on either physics-based or data-driven models, each with complementary strengths and limitations that become most noticeable during critical scenarios. This paper presents a novel consensus multi-model Kalman filter framework t…

Recursive spectral relations and the charge versus neutral gap in fractional quantum Hall systems
Marius Lemm, Bruno Nachtergaele, Simone Warzel, Amanda Young
https://arxiv.org/abs/2507.18814

Recursive spectral relations and the charge versus neutral gap in fractional quantum Hall systems
We consider quantum lattice Hamiltonians and derive recursive spectral relations bridging successive particle number sectors. One relation gives conditions under which the charge gap dominates the neutral gap. We verify these conditions under a triad of symmetries (translation-invariance, charge and dipole conservation) that are present, e.g., in periodic fractional quantum Hall systems. Thus, this gap domination, previously observed numerically, is a universal feature imposed by symmetry. A se…

MoCHA: Advanced Vision-Language Reasoning with MoE Connector and Hierarchical Group Attention
Yuqi Pang, Bowen Yang, Yun Cao, Fan Rong, Xiaoyu Li, Chen He
https://arxiv.org/abs/2507.22805

MoCHA: Advanced Vision-Language Reasoning with MoE Connector and Hierarchical Group Attention
Vision large language models (VLLMs) are focusing primarily on handling complex and fine-grained visual information by incorporating advanced vision encoders and scaling up visual models. However, these approaches face high training and inference costs, as well as challenges in extracting visual details, effectively bridging across modalities. In this work, we propose a novel visual framework, MoCHA, to address these issues. Our framework integrates four vision backbones (i.e., CLIP, SigLIP, DI…

Universal Radial Scaling of Large-Scale Black Hole Accretion for Magnetically Arrested And Rocking Accretion Disks
Aretaios Lalakos, Alexander Tchekhovskoy, Elias R. Most, Bart Ripperda, Koushik Chatterjee, Matthew Liska
https://arxiv.org/abs/2505.23888

Universal Radial Scaling of Large-Scale Black Hole Accretion for Magnetically Arrested And Rocking Accretion Disks
Accretion onto supermassive black holes (BHs) can launch relativistic jets that inject energy and momentum into their surroundings. Understanding how such feedback shapes large-scale accretion is key to bridging observations from galactic scales (e.g., the Bondi radius, $r_{\rm B}$) down to event horizon scales ($r_{\rm g}$), spanning 5-6 orders of magnitude. We tackle this challenge by varying the spatial scale separation across 2-4 orders of magnitude and performing some of the longest contig…

Faithful-Newton Framework: Bridging Inner and Outer Solvers for Enhanced Optimization
Alexander Lim, Fred Roosta
https://arxiv.org/abs/2506.13154 https://

Faithful-Newton Framework: Bridging Inner and Outer Solvers for Enhanced Optimization
While Newton-type methods are known for their fast local convergence and strong empirical performance, achieving theoretically favorable global convergence compared to first-order methods remains a key challenge. For instance, surprisingly, for simple strongly convex problems, no straightforward variant of Newton's method matches the global complexity of gradient descent. Although sophisticated variants can improve iteration complexity over gradient descent for various problems, they often invo…

Bridging Compositional and Distributional Semantics: A Survey on Latent Semantic Geometry via AutoEncoder
Yingji Zhang, Danilo S. Carvalho, Andr\'e Freitas
https://arxiv.org/abs/2506.20083

Bridging Compositional and Distributional Semantics: A Survey on Latent Semantic Geometry via AutoEncoder
Integrating compositional and symbolic properties into current distributional semantic spaces can enhance the interpretability, controllability, compositionality, and generalisation capabilities of Transformer-based auto-regressive language models (LMs). In this survey, we offer a novel perspective on latent space geometry through the lens of compositional semantics, a direction we refer to as \textit{semantic representation learning}. This direction enables a bridge between symbolic and distri…

ClearerVoice-Studio: Bridging Advanced Speech Processing Research and Practical Deployment
Shengkui Zhao, Zexu Pan, Bin Ma
https://arxiv.org/abs/2506.19398

ClearerVoice-Studio: Bridging Advanced Speech Processing Research and Practical Deployment
This paper introduces ClearerVoice-Studio, an open-source, AI-powered speech processing toolkit designed to bridge cutting-edge research and practical application. Unlike broad platforms like SpeechBrain and ESPnet, ClearerVoice-Studio focuses on interconnected speech tasks of speech enhancement, separation, super-resolution, and multimodal target speaker extraction. A key advantage is its state-of-the-art pretrained models, including FRCRN with 3 million uses and MossFormer with 2.5 million us…

The Hofstadter Butterfly: Bridging Condensed Matter, Topology, and Number Theory
Indubala Satija
https://arxiv.org/abs/2507.13418 https://

The Hofstadter Butterfly: Bridging Condensed Matter, Topology, and Number Theory
Celebrating its golden jubilee, the Hofstadter butterfly fractal emerges as a remarkable fusion of art and science. This iconic X shaped fractal captivates physicists, mathematicians, and enthusiasts alike by elegantly illustrating the energy spectrum of electrons within a two dimensional crystal lattice influenced by a magnetic field. Enriched with integers of topological origin that serve as quanta of Hall conductivity, this quantum fractal and its variations have become paradigm models for t…

Bridging the Gap: Enhancing News Interpretation Across Diverse Audiences with Large Language Models
Leyi Ouyang
https://arxiv.org/abs/2507.21055 https://ar…

Bridging the Gap: Enhancing News Interpretation Across Diverse Audiences with Large Language Models
In the interconnected world, news media are critical in conveying information to public across diverse domains including technology, finance, and agriculture. Journalists make efforts to present accurate information, however, the interpretation of news often varies significantly among different audiences due to their specific expertise and age. In this work, we investigate how to identify these comprehension gaps and provide solutions to improve audiences understanding of news content, particul…

Bridging Equilibrium and Kinetics Prediction with a Data-Weighted Neural Network Model of Methane Steam Reforming
Zofia Pizo\'n, Shinji Kimijima, Grzegorz Brus
https://arxiv.org/abs/2506.17224

Bridging Equilibrium and Kinetics Prediction with a Data-Weighted Neural Network Model of Methane Steam Reforming
Hydrogen's role is growing as an energy carrier, increasing the need for efficient production, with methane steam reforming being the most widely used technique. This process is crucial for applications like fuel cells, where hydrogen is converted into electricity, pushing for reactor miniaturization and optimized process control through numerical simulations. Existing models typically address either kinetic or equilibrium regimes, limiting their applicability. Here we show a surrogate model ca…

Bridging Fitness With Search Spaces By Fitness Supremums: A Theoretical Study on LGP
Zhixing Huang, Yi Mei, Fangfang Zhang, Mengjie Zhang, Wolfgang Banzhaf
https://arxiv.org/abs/2505.21991

Bridging Fitness With Search Spaces By Fitness Supremums: A Theoretical Study on LGP
Genetic programming has undergone rapid development in recent years. However, theoretical studies of genetic programming are far behind. One of the major obstacles to theoretical studies is the challenge of developing a model to describe the relationship between fitness values and program genotypes. In this paper, we take linear genetic programming (LGP) as an example to study the fitness-to-genotype relationship. We find that the fitness expectation increases with fitness supremum over instruc…

Bridging the gap: consistent modeling of protoplanetary disk heating and gap formation by planet-induced spiral shocks
Satoshi Okuzumi, Takayuki Muto, Ryosuke T. Tominaga, Shizu Shimizu
https://arxiv.org/abs/2507.18283

Bridging the gap: consistent modeling of protoplanetary disk heating and gap formation by planet-induced spiral shocks
A giant planet embedded in a protoplanetary disk excites spiral density waves, which steepen into shocks as they propagate away from the planet. These shocks lead to secular disk heating and gap opening, both of which can have important implications for the evolution of solids near the planet. To date, these two effects have largely been modeled independently. In this study, we present a self-consistent model that unifies these processes by linking shock heating and angular momentum deposition …

ACT: Bridging the Gap in Code Translation through Synthetic Data Generation & Adaptive Training
Shreya Saxena, Siva Prasad, Zishan Ahmad, Vishal Vaddina
https://arxiv.org/abs/2507.16478

ACT: Bridging the Gap in Code Translation through Synthetic Data Generation & Adaptive Training
Code translation is a crucial process in software development and migration projects, enabling interoperability between different programming languages and enhancing software adaptability and thus longevity. Traditional automated translation methods rely heavily on handcrafted transformation rules, which often lack flexibility and scalability. Meanwhile, advanced language models present promising alternatives but are often limited by proprietary, API-based implementations that raise concerns ov…

ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask Dataset
Yilin Wang, Peixuan Lei, Jie Song, Yuzhe Hao, Tao Chen, Yuxuan Zhang, Lei Jia, Yuanxiang Li, Zhongyu Wei
https://arxiv.org/abs/2506.20093

ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask Dataset
Time-series data are critical in diverse applications, such as industrial monitoring, medical diagnostics, and climate research. However, effectively integrating these high-dimensional temporal signals with natural language for dynamic, interactive tasks remains a significant challenge. To address this, we introduce the Time-Series Question Answering (Time-Series QA) task and release EngineMT-QA, the first large-scale, multi-task, temporal-textual QA dataset designed to capture complex interact…

Reflective VLM Planning for Dual-Arm Desktop Cleaning: Bridging Open-Vocabulary Perception and Precise Manipulation
Yufan Liu, Yi Wu, Gweneth Ge, Haoliang Cheng, Rui Liu
https://arxiv.org/abs/2506.17328

Reflective VLM Planning for Dual-Arm Desktop Cleaning: Bridging Open-Vocabulary Perception and Precise Manipulation
Desktop cleaning demands open-vocabulary recognition and precise manipulation for heterogeneous debris. We propose a hierarchical framework integrating reflective Vision-Language Model (VLM) planning with dual-arm execution via structured scene representation. Grounded-SAM2 facilitates open-vocabulary detection, while a memory-augmented VLM generates, critiques, and revises manipulation sequences. These sequences are converted into parametric trajectories for five primitives executed by coordin…

Making the Right Thing: Bridging HCI and Responsible AI in Early-Stage AI Concept Selection
Ji-Youn Jung, Devansh Saxena, Minjung Park, Jini Kim, Jodi Forlizzi, Kenneth Holstein, John Zimmerman
https://arxiv.org/abs/2506.17494

Making the Right Thing: Bridging HCI and Responsible AI in Early-Stage AI Concept Selection
AI projects often fail due to financial, technical, ethical, or user acceptance challenges -- failures frequently rooted in early-stage decisions. While HCI and Responsible AI (RAI) research emphasize this, practical approaches for identifying promising concepts early remain limited. Drawing on Research through Design, this paper investigates how early-stage AI concept sorting in commercial settings can reflect RAI principles. Through three design experiments -- including a probe study with ind…

Bridging the Gap in Vision Language Models in Identifying Unsafe Concepts Across Modalities
Yiting Qu, Michael Backes, Yang Zhang
https://arxiv.org/abs/2507.11155

Bridging the Gap in Vision Language Models in Identifying Unsafe Concepts Across Modalities
Vision-language models (VLMs) are increasingly applied to identify unsafe or inappropriate images due to their internal ethical standards and powerful reasoning abilities. However, it is still unclear whether they can recognize various unsafe concepts when presented in different modalities, such as text and images. To address this, we first compile the UnsafeConcepts dataset, featuring 75 unsafe concepts, i.e., ``Swastika,'' ``Sexual Harassment,'' and ``Assaults,'' along with associated 1.5K im…

Bridging Scales in Black Hole Accretion and Feedback: Relativistic Jet linking the Horizon to the Host Galaxy
Hyerin Cho, Ben S. Prather, Ramesh Narayan, Kung-Yi Su, Priyamvada Natarajan
https://arxiv.org/abs/2507.17818

Bridging Scales in Black Hole Accretion and Feedback: Relativistic Jet linking the Horizon to the Host Galaxy
Simulating black hole (BH) accretion and feedback from the horizon to galactic scales is extremely challenging, as it involves a vast range of scales. Recently, our multizone method has successfully achieved global dynamical steady-states of hot accretion flows in three-dimensional general relativistic magnetohydrodynamic (GRMHD) simulations by tracking the bidirectional interaction between a non-spinning BH and its host galaxy. In this paper, we present technical improvements to the method and…

Towards Bridging Formal Methods and Human Interpretability
Abhijit Paul, Proma Chowdhury, Kazi Sakib
https://arxiv.org/abs/2506.09759 https://

Towards Bridging Formal Methods and Human Interpretability
Labeled Transition Systems (LTS) are integral to model checking and design repair tools. System engineers frequently examine LTS designs during model checking or design repair to debug, identify inconsistencies, and validate system behavior. Despite LTS's significance, no prior research has examined human comprehension of these designs. To address this, we draw on traditional software engineering and graph theory, identifying 7 key metrics: cyclomatic complexity, state space size, average branc…

Binarization-Aware Adjuster: Bridging Continuous Optimization and Binary Inference in Edge Detection
Hao Shu
https://arxiv.org/abs/2506.12460 https://

Binarization-Aware Adjuster: Bridging Continuous Optimization and Binary Inference in Edge Detection
Image edge detection (ED) faces a fundamental mismatch between training and inference: models are trained using continuous-valued outputs but evaluated using binary predictions. This misalignment, caused by the non-differentiability of binarization, weakens the link between learning objectives and actual task performance. In this paper, we propose a theoretical method to design a Binarization-Aware Adjuster (BAA), which explicitly incorporates binarization behavior into gradient-based optimizat…

Bridging Pattern-Aware Complexity with NP-Hard Optimization: A Unifying Framework and Empirical Study
Olivier Saidi
https://arxiv.org/abs/2506.13810 https:…

Bridging Pattern-Aware Complexity with NP-Hard Optimization: A Unifying Framework and Empirical Study
NP hard optimization problems like the Traveling Salesman Problem (TSP) defy efficient solutions in the worst case, yet real-world instances often exhibit exploitable patterns. We propose a novel patternaware complexity framework that quantifies and leverages structural regularities e.g., clustering, symmetry to reduce effective computational complexity across domains, including financial forecasting and LLM optimization. With rigorous definitions, theorems, and a meta learning driven solver pi…

3LM: Bridging Arabic, STEM, and Code through Benchmarking
Basma El Amel Boussaha, Leen AlQadi, Mugariya Farooq, Shaikha Alsuwaidi, Giulia Campesan, Ahmed Alzubaidi, Mohammed Alyafeai, Hakim Hacid
https://arxiv.org/abs/2507.15850

3LM: Bridging Arabic, STEM, and Code through Benchmarking
Arabic is one of the most widely spoken languages in the world, yet efforts to develop and evaluate Large Language Models (LLMs) for Arabic remain relatively limited. Most existing Arabic benchmarks focus on linguistic, cultural, or religious content, leaving a significant gap in domains like STEM and code which are increasingly relevant for real-world LLM applications. To help bridge this gap, we present 3LM, a suite of three benchmarks designed specifically for Arabic. The first is a set of S…

DISCOVERSE: Efficient Robot Simulation in Complex High-Fidelity Environments
Yufei Jia, Guangyu Wang, Yuhang Dong, Junzhe Wu, Yupei Zeng, Haonan Lin, Zifan Wang, Haizhou Ge, Weibin Gu, Kairui Ding, Zike Yan, Yunjie Cheng, Yue Li, Ziming Wang, Chuxuan Li, Wei Sui, Lu Shi, Guanzhong Tian, Ruqi Huang, Guyue Zhou
https://arxiv.org/abs/2507.219…

DISCOVERSE: Efficient Robot Simulation in Complex High-Fidelity Environments
We present the first unified, modular, open-source 3DGS-based simulation framework for Real2Sim2Real robot learning. It features a holistic Real2Sim pipeline that synthesizes hyper-realistic geometry and appearance of complex real-world scenarios, paving the way for analyzing and bridging the Sim2Real gap. Powered by Gaussian Splatting and MuJoCo, Discoverse enables massively parallel simulation of multiple sensor modalities and accurate physics, with inclusive supports for existing 3D assets, …

This https://arxiv.org/abs/2410.09516 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCE_…

Bridging the Gap Between Data-Driven And Theory-Driven Modelling - Leveraging Causal Machine Learning for Integrative Modelling of Dynamical Systems
Classical machine learning techniques often struggle with overfitting and unreliable predictions when exposed to novel conditions. Introducing causality into the modelling process offers a promising way to mitigate these challenges by enhancing predictive robustness. However, constructing an initial causal graph manually using domain knowledge is time-consuming, particularly in complex time series with numerous variables. To address this, causal discovery algorithms can provide a preliminary ca…

Enabling Bitcoin Smart Contracts on the Internet Computer
Ryan Croote, Islam El-Ashi, Thomas Locher, Yvonne-Anne Pignolet
https://arxiv.org/abs/2506.21327 …

Enabling Bitcoin Smart Contracts on the Internet Computer
There is growing interest in providing programmatic access to the value locked in Bitcoin, which famously offers limited programmability itself. Various approaches have been put forth in recent years, with the vast majority of proposed mechanisms either building new functionality on top of Bitcoin or leveraging a bridging mechanism to enable smart contracts that make use of ``wrapped'' bitcoins on entirely different platforms. In this work, an architecture is presented that follows a differen…

Bridging MOOCs, Smart Teaching, and AI: A Decade of Evolution Toward a Unified Pedagogy
Bo Yuan, Jiazi Hu
https://arxiv.org/abs/2507.14266 https://

Bridging MOOCs, Smart Teaching, and AI: A Decade of Evolution Toward a Unified Pedagogy
Over the past decade, higher education has evolved through three distinct paradigms: the emergence of Massive Open Online Courses (MOOCs), the integration of Smart Teaching technologies into classrooms, and the rise of AI-enhanced learning. Each paradigm is intended to address specific challenges in traditional education: MOOCs enable ubiquitous access to learning resources; Smart Teaching supports real-time interaction with data-driven insights; and generative AI offers personalized feedback a…

Shelter Soul: Bridging Shelters and Adopters Through Technology
Yashodip Dharmendra Jagtap
https://arxiv.org/abs/2506.12739 https://a…

Shelter Soul: Bridging Shelters and Adopters Through Technology
Pet adoption processes often face inefficiencies, including limited accessibility, lack of real-time information, and mismatched expectations between shelters and adopters. To address these challenges, this study presents Shelter Soul, a technology-based solution designed to streamline pet adoption through an integrated, web-based platform. Developed using the MERN stack and GraphQL, Shelter Soul is a prototype system built to improve pet matching accuracy, shelter management efficiency, and se…

Bridging AI and Software Security: A Comparative Vulnerability Assessment of LLM Agent Deployment Paradigms
Tarek Gasmi, Ramzi Guesmi, Ines Belhadj, Jihene Bennaceur
https://arxiv.org/abs/2507.06323

Bridging AI and Software Security: A Comparative Vulnerability Assessment of LLM Agent Deployment Paradigms
Large Language Model (LLM) agents face security vulnerabilities spanning AI-specific and traditional software domains, yet current research addresses these separately. This study bridges this gap through comparative evaluation of Function Calling architecture and Model Context Protocol (MCP) deployment paradigms using a unified threat classification framework. We tested 3,250 attack scenarios across seven language models, evaluating simple, composed, and chained attacks targeting both AI-specif…

Breaking Single-Tester Limits: Multi-Agent LLMs for Multi-User Feature Testing
Sidong Feng, Changhao Du, Huaxiao Liu, Qingnan Wang, Zhengwei Lv, Mengfei Wang, Chunyang Chen
https://arxiv.org/abs/2506.17539

Breaking Single-Tester Limits: Multi-Agent LLMs for Multi-User Feature Testing
The growing dependence on mobile phones and their apps has made multi-user interactive features, like chat calls, live streaming, and video conferencing, indispensable for bridging the gaps in social connectivity caused by physical and situational barriers. However, automating these interactive features for testing is fraught with challenges, owing to their inherent need for timely, dynamic, and collaborative user interactions, which current automated testing methods inadequately address. Inspi…

Bridging the Gap: Leveraging Retrieval-Augmented Generation to Better Understand Public Concerns about Vaccines
Muhammad Javed, Sedigh Khademi Habibabadi, Christopher Palmer, Hazel Clothier, Jim Buttery, Gerardo Luis Dimaguila
https://arxiv.org/abs/2507.12840

Bridging the Gap: Leveraging Retrieval-Augmented Generation to Better Understand Public Concerns about Vaccines
Vaccine hesitancy threatens public health, leading to delayed or rejected vaccines. Social media is a vital source for understanding public concerns, and traditional methods like topic modelling often struggle to capture nuanced opinions. Though trained for query answering, large Language Models (LLMs) often miss current events and community concerns. Additionally, hallucinations in LLMs can compromise public health communication. To address these limitations, we developed a tool (VaxPulse Quer…

Bridging Perspectives: A Survey on Cross-view Collaborative Intelligence with Egocentric-Exocentric Vision
Yuping He, Yifei Huang, Guo Chen, Lidong Lu, Baoqi Pei, Jilan Xu, Tong Lu, Yoichi Sato
https://arxiv.org/abs/2506.06253

Bridging Perspectives: A Survey on Cross-view Collaborative Intelligence with Egocentric-Exocentric Vision
Perceiving the world from both egocentric (first-person) and exocentric (third-person) perspectives is fundamental to human cognition, enabling rich and complementary understanding of dynamic environments. In recent years, allowing the machines to leverage the synergistic potential of these dual perspectives has emerged as a compelling research direction in video understanding. In this survey, we provide a comprehensive review of video understanding from both exocentric and egocentric viewpoint…

Replaced article(s) found for cs.CE. https://arxiv.org/list/cs.CE/new
[1/1]:
- Bridging Sequential Deep Operator Network and Video Diffusion: Residual Refinement of Spatio-Temp...
Park, Ahmed, Kobayashi, Koric, Alam, Jasiuk, Abueidda

SPOT: Bridging Natural Language and Geospatial Search for Investigative Journalists
Lynn Khellaf, Ipek Baris Schlicht, Tilman Mirass, Julia Bayer, Tilman Wagner, Ruben Bouwmeester
https://arxiv.org/abs/2506.13188

SPOT: Bridging Natural Language and Geospatial Search for Investigative Journalists
OpenStreetMap (OSM) is a vital resource for investigative journalists doing geolocation verification. However, existing tools to query OSM data such as Overpass Turbo require familiarity with complex query languages, creating barriers for non-technical users. We present SPOT, an open source natural language interface that makes OSM's rich, tag-based geographic data more accessible through intuitive scene descriptions. SPOT interprets user inputs as structured representations of geospatial objec…

Model Cards Revisited: Bridging the Gap Between Theory and Practice for Ethical AI Requirements
Tim Puhlf\"ur{\ss}, Julia Butzke, Walid Maalej
https://arxiv.org/abs/2507.06014

Model Cards Revisited: Bridging the Gap Between Theory and Practice for Ethical AI Requirements
Model cards are the primary documentation framework for developers of artificial intelligence (AI) models to communicate critical information to their users. Those users are often developers themselves looking for relevant documentation to ensure that their AI systems comply with the ethical requirements of existing laws, guidelines, and standards. Recent studies indicate inadequate model documentation practices, suggesting a gap between AI requirements and current practices in model documentat…

Bridging Boundaries: How to Foster Effective Research Collaborations Across Affiliations in the Field of Trust and Safety
Amanda Menking, Mona Elswah, David J. Gr\"uning, Lasse H. Hansen, Irene Huang, Julia Kamin, Catrine Normann
https://arxiv.org/abs/2507.13008

Bridging Boundaries: How to Foster Effective Research Collaborations Across Affiliations in the Field of Trust and Safety
As the field of Trust and Safety in digital spaces continues to grow, it has become increasingly necessary - but also increasingly complex - to collaborate on research across the academic, industry, governmental and non-governmental sectors. This paper examines how cross-affiliation research partnerships can be structured to overcome misaligned incentives, timelines and constraints while delivering on the unique strengths of each stakeholder. Drawing on our own experience of cross-sector collab…

Bridging Perception and Action: Spatially-Grounded Mid-Level Representations for Robot Generalization
Jonathan Yang, Chuyuan Kelly Fu, Dhruv Shah, Dorsa Sadigh, Fei Xia, Tingnan Zhang
https://arxiv.org/abs/2506.06196

Bridging Perception and Action: Spatially-Grounded Mid-Level Representations for Robot Generalization
In this work, we investigate how spatially grounded auxiliary representations can provide both broad, high-level grounding as well as direct, actionable information to improve policy learning performance and generalization for dexterous tasks. We study these mid-level representations across three critical dimensions: object-centricity, pose-awareness, and depth-awareness. We use these interpretable mid-level representations to train specialist encoders via supervised learning, then feed them as…

Bridging Logic and Learning: Decoding Temporal Logic Embeddings via Transformers
Sara Candussio, Gaia Saveri, Gabriele Sarti, Luca Bortolussi
https://arxiv.org/abs/2507.07808

Bridging Logic and Learning: Decoding Temporal Logic Embeddings via Transformers
Continuous representations of logic formulae allow us to integrate symbolic knowledge into data-driven learning algorithms. If such embeddings are semantically consistent, i.e. if similar specifications are mapped into nearby vectors, they enable continuous learning and optimization directly in the semantic space of formulae. However, to translate the optimal continuous representation into a concrete requirement, such embeddings must be invertible. We tackle this issue by training a Transformer…

Co-persona: Leveraging LLMs and Expert Collaboration to Understand User Personas through Social Media Data Analysis
Min Yin, Haoyu Liu, Boyi Lian, Chunlei Chai
https://arxiv.org/abs/2506.18269

Co-persona: Leveraging LLMs and Expert Collaboration to Understand User Personas through Social Media Data Analysis
This study introduces \textsc{Co-Persona}, a framework bridging large-scale social media analysis and user understanding via integration of Large Language Models (LLMs) and expert validation. Through a case study of B.Co, a Chinese manufacturer, we applied \textsc{Co-Persona} to bedside lamp development by analyzing 38 million posts from Xiao Hongshu. Our multi-stage NLP processing revealed five user personas based on nighttime behaviors: Health Aficionados, Night Owls, Interior Decorators, Chi…

Beyond Interactions: Node-Level Graph Generation for Knowledge-Free Augmentation in Recommender Systems
Zhaoyan Wang, Hyunjun Ahn, In-Young Ko
https://arxiv.org/abs/2507.20578 h…

Beyond Interactions: Node-Level Graph Generation for Knowledge-Free Augmentation in Recommender Systems
Recent advances in recommender systems rely on external resources such as knowledge graphs or large language models to enhance recommendations, which limit applicability in real-world settings due to data dependency and computational overhead. Although knowledge-free models are able to bolster recommendations by direct edge operations as well, the absence of augmentation primitives drives them to fall short in bridging semantic and structural gaps as high-quality paradigm substitutes. Unlike ex…

OpenNav: Open-World Navigation with Multimodal Large Language Models
Mingfeng Yuan, Letian Wang, Steven L. Waslander
https://arxiv.org/abs/2507.18033 https://

OpenNav: Open-World Navigation with Multimodal Large Language Models
Pre-trained large language models (LLMs) have demonstrated strong common-sense reasoning abilities, making them promising for robotic navigation and planning tasks. However, despite recent progress, bridging the gap between language descriptions and actual robot actions in the open-world, beyond merely invoking limited predefined motion primitives, remains an open challenge. In this work, we aim to enable robots to interpret and decompose complex language instructions, ultimately synthesizing a…

ArtifactsBench: Bridging the Visual-Interactive Gap in LLM Code Generation Evaluation
Chenchen Zhang, Yuhang Li, Can Xu, Jiaheng Liu, Ao Liu, Shihui Hu, Dengpeng Wu, Guanhua Huang, Kejiao Li, Qi Yi, Ruibin Xiong, Haotian Zhu, Yuanxing Zhang, Yuhao Jiang, Yue Zhang, Zenan Xu, Bohui Zhai, Guoxiang He, Hebin Li, Jie Zhao, Le Zhang, Lingyun Tan, Pengyu Guo, Xianshu Pang, Yang Ruan, Zhifeng Zhang, Zhonghu Wang, Ziyan Xu, Zuopu Yin, Wiggin Zhou, Chayse Zhou, Fengzong Lian

ArtifactsBench: Bridging the Visual-Interactive Gap in LLM Code Generation Evaluation
The generative capabilities of Large Language Models (LLMs) are rapidly expanding from static code to dynamic, interactive visual artifacts. This progress is bottlenecked by a critical evaluation gap: established benchmarks focus on algorithmic correctness and are blind to the visual fidelity and interactive integrity that define modern user experiences. To bridge this gap, we introduce ArtifactsBench, a new benchmark and paradigm for the automated, multimodal evaluation of visual code generati…

Bridging Offline and Online Reinforcement Learning for LLMs
Jack Lanchantin, Angelica Chen, Janice Lan, Xian Li, Swarnadeep Saha, Tianlu Wang, Jing Xu, Ping Yu, Weizhe Yuan, Jason E Weston, Sainbayar Sukhbaatar, Ilia Kulikov
https://arxiv.org/abs/2506.21495 https://arxiv.org/pdf/2506.21495 https://arxiv.org/html/2506.21495
arXiv:2506.21495v1 Announce Type: new
Abstract: We investigate the effectiveness of reinforcement learning methods for finetuning large language models when transitioning from offline to semi-online to fully online regimes for both verifiable and non-verifiable tasks. Our experiments cover training on verifiable math as well as non-verifiable instruction following with a set of benchmark evaluations for both. Across these settings, we extensively compare online and semi-online Direct Preference Optimization and Group Reward Policy Optimization objectives, and surprisingly find similar performance and convergence between these variants, which all strongly outperform offline methods. We provide a detailed analysis of the training dynamics and hyperparameter selection strategies to achieve optimal results. Finally, we show that multi-tasking with verifiable and non-verifiable rewards jointly yields improved performance across both task types.
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