Tootfinder

1/ Since it's open season on the Chinese in the US right now, I wanted to post about a remarkable Chinese-American experience that is one of the real gems of New England, making the region and country better in every way. It's about jazz and blues music. ↵

It’s truly remarkable that we exist at all. Each of us breaks free from the chains of history and authority to experience life anew. Today, countless souls will awaken to their first love, their first union, or the birth of new life. Others will face heartbreak or part ways.
This moment, this very act of being alive and conscious, is a quiet act of rebellion against the forces that seek to suppress our humanity. To exist freely for the first time is the most radical and beautiful thing…

heise | Von reMarkable bis Supernote: Das passende E-Ink-Tablet für jeden Zweck finden
Sie ersetzen die Schreibkladde und machen Tablets Konkurrenz: E-Ink-Notizblöcke mit Farbe und Stift. So finden Sie den richtigen.

This https://arxiv.org/abs/2506.02658 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csSE_…

Computational Thinking Reasoning in Large Language Models
While large language models (LLMs) have demonstrated remarkable reasoning capabilities, they often struggle with complex tasks that require specific thinking paradigms, such as divide-and-conquer and procedural deduction, \etc Previous researches integrate external, reliable tools to alleviate logical inconsistencies and hallucinations in LLMs' problem-solving processes. However, we argue that the root challenge is more profound: LLMs lack the complex thinking paradigms (\ie, computational thin…

from my link log —
“Twelfth Night Till Candlemas: the story of a forty-year book-quest and of its remarkable ending.
https://davidallengreen.com/2024/12/twelfth-night-till-candlemas-the-story…

“Twelfth Night Till Candlemas” – the story of a forty-year book-quest and of its remarkable ending
The day before the Winter Solstice, 2024 This post is about finally finding a book from one’s youth forty years later – and after nearly thirty years of searching. It is also a tale about gob…

"2025 was the hottest spring on record and driest in over 50 years, Met Office says"
#UK #UnitedKingdom #Climate

2025 was the hottest spring on record and driest in over 50 years, Met Office says
The remarkable season unfolded month by month, beginning with a record-breaking sunny March that set the tone

This https://arxiv.org/abs/2501.04901 has been replaced.
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ThriftLLM: On Cost-Effective Selection of Large Language Models for Classification Queries
In recent years, large language models (LLMs) have demonstrated remarkable capabilities in comprehending and generating natural language content, attracting widespread attention in both industry and academia. An increasing number of services offer LLMs for various tasks via APIs. Different LLMs demonstrate expertise in different domains of queries (e.g., text classification queries). Meanwhile, LLMs of different scales, complexities, and performance are priced diversely. Driven by this, several…

Eye of the vortex: bound spectra in tunable horizonless rotational analogs
H. S. Vieira, Kyriakos Destounis
https://arxiv.org/abs/2506.03451 https://

Eye of the vortex: bound spectra in tunable horizonless rotational analogs
Analog gravity experiments are making remarkable strides in unveiling both the classical and quantum nature of black holes. By harnessing diverse states of matter, contemporary tabletop setups now replicate strong-field phenomena typically confined to the enigmatic regions surrounding black holes. Through these modern gravity simulators, physical processes once considered elusive may finally be brought into experimental reach. In this work, we investigate the bound spectrum of massless scalar e…

This https://arxiv.org/abs/2505.15380 has been replaced.
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Accelerating Autoregressive Speech Synthesis Inference With Speech Speculative Decoding
Modern autoregressive speech synthesis models leveraging language models have demonstrated remarkable performance. However, the sequential nature of next token prediction in these models leads to significant latency, hindering their deployment in scenarios where inference speed is critical. In this work, we propose Speech Speculative Decoding (SSD), a novel framework for autoregressive speech synthesis acceleration. Specifically, our method employs a lightweight draft model to generate candidat…

This https://arxiv.org/abs/2311.14590 has been replaced.
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Stability of domain walls with inflationary fluctuations under potential bias, and gravitational wave signatures
A recent study has shown that domain walls with inflationary initial fluctuations exhibit remarkable stability against population bias due to long-range correlations, challenging the claims of prior research. In this paper, we study the dynamics of these domain walls in the presence of potential bias and show that they collapse with a lifetime several times longer than that due to thermal fluctuations. This is interpreted as a difference in the average distance between domain walls, leading us …

Intelligent Channel Allocation for IEEE 802.11be Multi-Link Operation: When MAB Meets LLM
Shumin Lian, Jingwen Tong, Jun Zhang, Liqun Fu
https://arxiv.org/abs/2506.04594

Intelligent Channel Allocation for IEEE 802.11be Multi-Link Operation: When MAB Meets LLM
WiFi networks have achieved remarkable success in enabling seamless communication and data exchange worldwide. The IEEE 802.11be standard, known as WiFi 7, introduces Multi-Link Operation (MLO), a groundbreaking feature that enables devices to establish multiple simultaneous connections across different bands and channels. While MLO promises substantial improvements in network throughput and latency reduction, it presents significant challenges in channel allocation, particularly in dense netwo…

The remarkable story of Dr. James Mackness — a 19th-century village doctor whose quiet compassion and tireless service touched lives from Wellingborough, Turvey and Northampton to Hastings. A life of duty, resilience, and heart. https://edintone.com/james-mackness/

A Life of Quiet Duty: The Story of Dr. James Mackness (1804–1851) - Miscellanea Edintone
The remarkable story of Dr. James Mackness — a 19th-century village doctor whose quiet compassion and tireless service touched lives from Wellingborough, Turvey and Northampton to Hastings. A life of duty, resilience, and heart.

The Roman View of Strong Gravitational Lenses
Bryce Wedig, Tansu Daylan, Simon Birrer, Francis-Yan Cyr-Racine, Cora Dvorkin, Douglas P. Finkbeiner, Alan Huang, Xiaosheng Huang, Rahul Karthik, Narayan Khadka, Priyamvada Natarajan, Anna M. Nierenberg, Annika H. G. Peter, Justin D. R. Pierel, Xianzhe TZ Tang, Risa H. Wechsler
https://

The Roman View of Strong Gravitational Lenses
Galaxy-galaxy strong gravitational lenses can constrain dark matter models and the Lambda Cold Dark Matter cosmological paradigm at sub-galactic scales. Currently, there is a dearth of images of these rare systems with high signal-to-noise and angular resolution. The Nancy Grace Roman Space Telescope (hereafter, Roman), scheduled for launch in late 2026, will play a transformative role in strong lensing science with its planned wide-field surveys. With its remarkable 0.281 square degree field o…

This https://arxiv.org/abs/2505.05822 has been replaced.
initial toot: https://mastoxiv.page/@arX…

Self-reorganization and Information Transfer in Massive Schools of Fish
The remarkable cohesion and coordination observed in moving animal groups and their collective responsiveness to threats are thought to be mediated by scale-free correlations, where changes in the behavior of one animal influence others in the group, regardless of the distance between them. But are these features independent of group size? Here, we investigate group cohesiveness and collective responsiveness in computational models of massive schools of fish of up to 50,000 individuals. We show…

After watching yesterday's #f1 sprint qualifying I just told my friend, we are witnessing the birth of the next F1 legend. You can talk about technical/timing/race ability all you want, but it's quite simple. What Antonelli is doing in his first months in F1 is beyond remarkable. And the great ones always announce themselves like that. Beating McLaren's to the pole? Are you kidding me? Beati…

Wind-fed Supermassive Black Hole Accretion by the Nuclear Star Cluster: the Case of M31*
Zhao Su, Zhiyuan Li, Zongnan Li
https://arxiv.org/abs/2506.04778 h…

Wind-fed Supermassive Black Hole Accretion by the Nuclear Star Cluster: the Case of M31*
The central supermassive black hole (SMBH) of the Andromeda galaxy, known as M31*, exhibits dim electromagnetic emission and is inferred to have an extremely low accretion rate for its remarkable mass ($\sim10^8~\rm~M_\odot$). In this work, we use three-dimensional hydrodynamical simulations to explore a previously untested scenario, in which M31* is fed by the collective stellar mass-loss from its surrounding nuclear star cluster, manifested as a famous eccentric disk of predominantly old stel…

This https://arxiv.org/abs/2412.11934 has been replaced.
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Stepwise Reasoning Error Disruption Attack of LLMs
Large language models (LLMs) have made remarkable strides in complex reasoning tasks, but their safety and robustness in reasoning processes remain underexplored. Existing attacks on LLM reasoning are constrained by specific settings or lack of imperceptibility, limiting their feasibility and generalizability. To address these challenges, we propose the Stepwise rEasoning Error Disruption (SEED) attack, which subtly injects errors into prior reasoning steps to mislead the model into producing i…

Less is Enough: Training-Free Video Diffusion Acceleration via Runtime-Adaptive Caching
Xin Zhou, Dingkang Liang, Kaijin Chen, Tianrui Feng, Xiwu Chen, Hongkai Lin, Yikang Ding, Feiyang Tan, Hengshuang Zhao, Xiang Bai
https://arxiv.org/abs/2507.02860

Less is Enough: Training-Free Video Diffusion Acceleration via Runtime-Adaptive Caching
Video generation models have demonstrated remarkable performance, yet their broader adoption remains constrained by slow inference speeds and substantial computational costs, primarily due to the iterative nature of the denoising process. Addressing this bottleneck is essential for democratizing advanced video synthesis technologies and enabling their integration into real-world applications. This work proposes EasyCache, a training-free acceleration framework for video diffusion models. EasyCa…

This https://arxiv.org/abs/2411.13280 has been replaced.
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Empower Structure-Based Molecule Optimization with Gradient Guided Bayesian Flow Networks
Structure-Based molecule optimization (SBMO) aims to optimize molecules with both continuous coordinates and discrete types against protein targets. A promising direction is to exert gradient guidance on generative models given its remarkable success in images, but it is challenging to guide discrete data and risks inconsistencies between modalities. To this end, we leverage a continuous and differentiable space derived through Bayesian inference, presenting Molecule Joint Optimization (MolJO),…

Musical Improvisation - 3 Tips For Creating Remarkable Music In No Time https://muz4now.com/2016/musical-improv-3-tips-creating-remarkable-music-no-time/

Musical Improvisation - 3 Tips For Creating Remarkable Music In No Time
Stan Stewart - @muz4now

This https://arxiv.org/abs/2410.03590 has been replaced.
initial toot: https://mastoxiv.page/@a…

Enhancement to Fusion Reactivity in Sheared Flows
Sheared flow increases the reactivity of fusion plasma. In unmagnetized plasma with flow gradients comparable to the mean free path of reacting ions, fusion reactivity can be more than doubled. The effect is of particular relevance to inertial confinement fusion (ICF), where it allows implosion kinetic energy to contribute to the fusion burn even before thermalizing. In fast ignition, this allows remarkable energy savings because colder fuel stops alpha particles more quickly, enabling ignition…

Signatures of the Fermi surface reconstruction of a doped Mott insulator in a slab geometry
Gregorio Staffieri, Michele Fabrizio
https://arxiv.org/abs/2506.04155

Signatures of the Fermi surface reconstruction of a doped Mott insulator in a slab geometry
We investigate a hole-doped Mott insulator in a slab geometry using the dynamical cluster approximation. We show that the enhancement of the correlation strength at the surface results in the remarkable evolution of the layer-projected Fermi surface, which exhibits hole-like pockets in the superficial layers, but gradually evolves into a single electron-like surface in the innermost layers. We further analyze the behavior of the Friedel oscillations induced by the surface and identify distinct …

HAC-LOCO: Learning Hierarchical Active Compliance Control for Quadruped Locomotion under Continuous External Disturbances
Xiang Zhou, Xinyu Zhang, Qingrui Zhang
https://arxiv.org/abs/2507.02447

HAC-LOCO: Learning Hierarchical Active Compliance Control for Quadruped Locomotion under Continuous External Disturbances
Despite recent remarkable achievements in quadruped control, it remains challenging to ensure robust and compliant locomotion in the presence of unforeseen external disturbances. Existing methods prioritize locomotion robustness over compliance, often leading to stiff, high-frequency motions, and energy inefficiency. This paper, therefore, presents a two-stage hierarchical learning framework that can learn to take active reactions to external force disturbances based on force estimation. In the…

This https://arxiv.org/abs/2502.11191 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCR_…

Primus: A Pioneering Collection of Open-Source Datasets for Cybersecurity LLM Training
Large Language Models (LLMs) have shown remarkable advancements in specialized fields such as finance, law, and medicine. However, in cybersecurity, we have noticed a lack of open-source datasets, with a particular lack of high-quality cybersecurity pretraining corpora, even though much research indicates that LLMs acquire their knowledge during pretraining. To address this, we present a comprehensive suite of datasets covering all major training stages, including pretraining, instruction fine-…

HTSC-2025: A Benchmark Dataset of Ambient-Pressure High-Temperature Superconductors for AI-Driven Critical Temperature Prediction
Xiao-Qi Han, Ze-Feng Gao, Xin-De Wang, Zhenfeng Ouyang, Peng-Jie Guo, Zhong-Yi Lu
https://arxiv.org/abs/2506.03837

HTSC-2025: A Benchmark Dataset of Ambient-Pressure High-Temperature Superconductors for AI-Driven Critical Temperature Prediction
The discovery of high-temperature superconducting materials holds great significance for human industry and daily life. In recent years, research on predicting superconducting transition temperatures using artificial intelligence~(AI) has gained popularity, with most of these tools claiming to achieve remarkable accuracy. However, the lack of widely accepted benchmark datasets in this field has severely hindered fair comparisons between different AI algorithms and impeded further advancement of…

This https://arxiv.org/abs/2505.22906 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csHC_…

HiLDe: Intentional Code Generation via Human-in-the-Loop Decoding
While AI programming tools hold the promise of increasing programmers' capabilities and productivity to a remarkable degree, they often exclude users from essential decision-making processes, causing many to effectively "turn off their brains" and over-rely on solutions provided by these systems. These behaviors can have severe consequences in critical domains, like software security. We propose Human-in-the-loop Decoding, a novel interaction technique that allows users to observe and directly …

This https://arxiv.org/abs/2311.00388 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csIR_…

Towards Automatic Sampling of User Behaviors for Sequential Recommender Systems
Sequential recommender systems (SRS) have gained increasing popularity due to their remarkable proficiency in capturing dynamic user preferences. In the current setup of SRS, a common configuration is to uniformly consider each historical behavior as a positive interaction. However, this setting has the potential to yield sub-optimal performance as each individual item often have a different impact on shaping the user's interests. Hence, in this paper, we propose a novel automatic sampling fram…

Morabo Morojele’s creative career was remarkable.
What wove his three identities together – musician, development worker and writer – was his conscious, committed pan-Africanism
and his master craftsman’s skill with sound:
the sound of his drums and the sound of his words as they rose off the page.
Through his books, and his (far too few) recordings, that beauty lives with us still.
Robala ka khotso (Sleep in peace)

Morabo Morojele: The social and political drum beats of the Lesotho jazz musician
The jazz drummer, novelist and development scholar died on May 20.

Transformers as Multi-task Learners: Decoupling Features in Hidden Markov Models
Yifan Hao, Chenlu Ye, Chi Han, Tong Zhang
https://arxiv.org/abs/2506.01919

Transformers as Multi-task Learners: Decoupling Features in Hidden Markov Models
Transformer based models have shown remarkable capabilities in sequence learning across a wide range of tasks, often performing well on specific task by leveraging input-output examples. Despite their empirical success, a comprehensive theoretical understanding of this phenomenon remains limited. In this work, we investigate the layerwise behavior of Transformers to uncover the mechanisms underlying their multi-task generalization ability. Taking explorations on a typical sequence model, i.e, H…

This https://arxiv.org/abs/2502.16888 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_sta…

Functional BART with Shape Priors: A Bayesian Tree Approach to Constrained Functional Regression
Motivated by the remarkable success of Bayesian additive regression trees (BART) in regression modelling, we propose a novel nonparametric Bayesian method, termed Functional BART (FBART), tailored specifically for function-on-scalar regression. FBART leverages spline-based representations for functional responses coupled with a flexible tree-based partitioning structure, effectively capturing complex and heterogeneous relationships between response curves and scalar predictors. To facilitate ef…

AI4Research: A Survey of Artificial Intelligence for Scientific Research
Qiguang Chen, Mingda Yang, Libo Qin, Jinhao Liu, Zheng Yan, Jiannan Guan, Dengyun Peng, Yiyan Ji, Hanjing Li, Mengkang Hu, Yimeng Zhang, Yihao Liang, Yuhang Zhou, Jiaqi Wang, Zhi Chen, Wanxiang Che
https://arxiv.org/abs/2507.01903

AI4Research: A Survey of Artificial Intelligence for Scientific Research
Recent advancements in artificial intelligence (AI), particularly in large language models (LLMs) such as OpenAI-o1 and DeepSeek-R1, have demonstrated remarkable capabilities in complex domains such as logical reasoning and experimental coding. Motivated by these advancements, numerous studies have explored the application of AI in the innovation process, particularly in the context of scientific research. These AI technologies primarily aim to develop systems that can autonomously conduct rese…

This https://arxiv.org/abs/2409.01043 has been replaced.
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On derangements in simple permutation groups
Let $G \leqslant {\rm Sym}(Ω)$ be a finite transitive permutation group and recall that an element in $G$ is a derangement if it has no fixed points on $Ω$. Let $Δ(G)$ be the set of derangements in $G$ and define $δ(G) = |Δ(G)|/|G|$ and $Δ(G)^2 = \{ xy \,:\, x,y \in Δ(G)\}$. In recent years, there has been a focus on studying derangements in simple groups, leading to several remarkable results. For example, by combining a theorem of Fulman and Guralnick with recent wo…

This https://arxiv.org/abs/2501.01659 has been replaced.
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Modification of single-hole-like states by configuration mixing in the $^{99-131}$In
Large-scale shell-model calculations are performed for the $9/2^+_{\rm g.s.}$, $1/2^-_1$, $3/2^-_1$, and $5/2^-_1$ states in the odd-$A$ indium isotopes with $N=50-82$. The calculated energy levels, electromagnetic moments, and spectroscopic factors exhibit remarkable agreement with the experimental data due to significant configuration mixing for the neutron numbers away from the closed shells. The $1/2^-_1$ energy levels closely follow the trend of effective single-particle energies, which ar…

Remarkable.
I visited Budapest not too long ago and ••loved•• the place. I had trouble while there parsing or even perceiving all the layers of Orbanism and cosmopolitanism and Hungarian-ness. I could tell that there were strong undercurrents invisible to me, both oppressive and liberatory. And I had a sense that yes, it was a city where a march like this was just beneath the surface everywhere, every day.
Watch a few seconds the video for a sense of scale.
https://www.theguardian.com/world/live/2025/jun/28/europe-latest-news-budapest-pride-march-hungary-orban-ukraine-russia-updates

This https://arxiv.org/abs/2501.11744 has been replaced.
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Confinement-induced proliferation of vortices around marine invertebrate larvae
The ocean is teeming with a myriad of mm-sized invertebrate planktonic larvae, which thrive in a viscous fluid environment. Many of them rely on ciliary beating to generate fluid flows for locomotion and feeding. Their larval forms, local morphologies, and ciliation patterns exhibit remarkable diversity, producing intricate and dynamic 3D flows that are notoriously difficult to characterize in laboratory settings. Traditional microscopic imaging techniques typically involve gently squeeze-confi…

Retrieval-Augmented Generation in Biomedicine: A Survey of Technologies, Datasets, and Clinical Applications
Jiawei He, Boya Zhang, Hossein Rouhizadeh, Yingjian Chen, Rui Yang, Jin Lu, Xudong Chen, Nan Liu, Irene Li, Douglas Teodoro
https://arxiv.org/abs/2505.01146

Retrieval-Augmented Generation in Biomedicine: A Survey of Technologies, Datasets, and Clinical Applications
Recent advances in large language models (LLMs) have demonstrated remarkable capabilities in natural language processing tasks. However, their application in the biomedical domain presents unique challenges, particularly regarding factual accuracy and up-to-date knowledge integration. Retrieval Augmented Generation (RAG) has emerged as a promising solution to address these challenges by combining the generative capabilities of LLMs with external knowledge retrieval. This comprehensive survey ex…

This https://arxiv.org/abs/2412.13147 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csAI_…

Are Your LLMs Capable of Stable Reasoning?
The rapid advancement of large language models (LLMs) has shown remarkable progress in complex reasoning tasks. However, a significant disparity exists between benchmark performances and real-world applications. We attribute this gap primarily to current evaluation protocols and metrics, which inadequately capture the full spectrum of LLM capabilities, especially in complex reasoning tasks where both accuracy and consistency are essential. In this paper, we introduce G-Pass@$k$, a novel evaluat…

RichControl: Structure- and Appearance-Rich Training-Free Spatial Control for Text-to-Image Generation
Liheng Zhang, Lexi Pang, Hang Ye, Xiaoxuan Ma, Yizhou Wang
https://arxiv.org/abs/2507.02792

RichControl: Structure- and Appearance-Rich Training-Free Spatial Control for Text-to-Image Generation
Text-to-image (T2I) diffusion models have shown remarkable success in generating high-quality images from text prompts. Recent efforts extend these models to incorporate conditional images (e.g., depth or pose maps) for fine-grained spatial control. Among them, feature injection methods have emerged as a training-free alternative to traditional fine-tuning approaches. However, they often suffer from structural misalignment, condition leakage, and visual artifacts, especially when the condition …

The Exact and Approximate Tales of Boost-Breaking Cosmological Correlators
Zhehan Qin, S\'ebastien Renaux-Petel, Xi Tong, Denis Werth, Yuhang Zhu
https://arxiv.org/abs/2506.01555

The Exact and Approximate Tales of Boost-Breaking Cosmological Correlators
Cosmological correlators offer a remarkable window into the high-energy physics governing Universe's earliest moments, with the tantalising prospect of discovering new particles. However, extracting new physics from these observables requires both precise theoretical predictions of inflationary theories and accurate, analytical templates suitable for data analysis throughout parameter and kinematic spaces. In this paper, we extend the current analytical results by computing the most general boo…

Enhancing Finite State Machine Design Automation with Large Language Models and Prompt Engineering Techniques
Qun-Kai Lin, Cheng Hsu, Tian-Sheuan Chang
https://arxiv.org/abs/2506.00001

Enhancing Finite State Machine Design Automation with Large Language Models and Prompt Engineering Techniques
Large Language Models (LLMs) have attracted considerable attention in recent years due to their remarkable compatibility with Hardware Description Language (HDL) design. In this paper, we examine the performance of three major LLMs, Claude 3 Opus, ChatGPT-4, and ChatGPT-4o, in designing finite state machines (FSMs). By utilizing the instructional content provided by HDLBits, we evaluate the stability, limitations, and potential approaches for improving the success rates of these models. Further…

Computational Thinking Reasoning in Large Language Models
Kechi Zhang, Ge Li, Jia Li, Huangzhao Zhang, Jingjing Xu, Hao Zhu, Lecheng Wang, Jia Li, Yihong Dong, Jing Mai, Bin Gu, Zhi Jin
https://arxiv.org/abs/2506.02658

Computational Thinking Reasoning in Large Language Models
While large language models (LLMs) have demonstrated remarkable reasoning capabilities, they often struggle with complex tasks that require specific thinking paradigms, such as divide-and-conquer and procedural deduction, \etc Previous researches integrate external, reliable tools to alleviate logical inconsistencies and hallucinations in LLMs' problem-solving processes. However, we argue that the root challenge is more profound: LLMs lack the complex thinking paradigms (\ie, computational thin…

This https://arxiv.org/abs/2505.21432 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

Hume: Introducing System-2 Thinking in Visual-Language-Action Model
Humans practice slow thinking before performing actual actions when handling complex tasks in the physical world. This thinking paradigm, recently, has achieved remarkable advancement in boosting Large Language Models (LLMs) to solve complex tasks in digital domains. However, the potential of slow thinking remains largely unexplored for robotic foundation models interacting with the physical world. In this work, we propose Hume: a dual-system Vision-Language-Action (VLA) model with value-guided…

Diffusion Buffer: Online Diffusion-based Speech Enhancement with Sub-Second Latency
Bunlong Lay, Rostilav Makarov, Timo Gerkmann
https://arxiv.org/abs/2506.02908

Diffusion Buffer: Online Diffusion-based Speech Enhancement with Sub-Second Latency
Diffusion models are a class of generative models that have been recently used for speech enhancement with remarkable success but are computationally expensive at inference time. Therefore, these models are impractical for processing streaming data in real-time. In this work, we adapt a sliding window diffusion framework to the speech enhancement task. Our approach progressively corrupts speech signals through time, assigning more noise to frames close to the present in a buffer. This approach …

DMCIE: Diffusion Model with Concatenation of Inputs and Errors to Improve the Accuracy of the Segmentation of Brain Tumors in MRI Images
Sara Yavari, Rahul Nitin Pandya, Jacob Furst
https://arxiv.org/abs/2507.00983

DMCIE: Diffusion Model with Concatenation of Inputs and Errors to Improve the Accuracy of the Segmentation of Brain Tumors in MRI Images
Accurate segmentation of brain tumors in MRI scans is essential for reliable clinical diagnosis and effective treatment planning. Recently, diffusion models have demonstrated remarkable effectiveness in image generation and segmentation tasks. This paper introduces a novel approach to corrective segmentation based on diffusion models. We propose DMCIE (Diffusion Model with Concatenation of Inputs and Errors), a novel framework for accurate brain tumor segmentation in multi-modal MRI scans. We e…

Beyond the Black Box: Interpretability of LLMs in Finance
Hariom Tatsat (Barclays), Ariye Shater (Barclays)
https://arxiv.org/abs/2505.24650 https://

Beyond the Black Box: Interpretability of LLMs in Finance
Large Language Models (LLMs) exhibit remarkable capabilities across a spectrum of tasks in financial services, including report generation, chatbots, sentiment analysis, regulatory compliance, investment advisory, financial knowledge retrieval, and summarization. However, their intrinsic complexity and lack of transparency pose significant challenges, especially in the highly regulated financial sector, where interpretability, fairness, and accountability are critical. As far as we are aware, t…

Bootstrapping Grounded Chain-of-Thought in Multimodal LLMs for Data-Efficient Model Adaptation
Jiaer Xia, Bingkui Tong, Yuhang Zang, Rui Shao, Kaiyang Zhou
https://arxiv.org/abs/2507.02859

Bootstrapping Grounded Chain-of-Thought in Multimodal LLMs for Data-Efficient Model Adaptation
Multimodal Large Language Models (MLLMs) have demonstrated remarkable capabilities in interpreting images using natural language. However, without using large-scale datasets for retraining, these models are difficult to adapt to specialized vision tasks, e.g., chart understanding. This problem is caused by a mismatch between pre-training and downstream datasets: pre-training datasets primarily concentrate on scenes and objects but contain limited information about specialized, non-object images…

This https://arxiv.org/abs/2501.07071 has been replaced.
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Value Compass Leaderboard: A Platform for Fundamental and Validated Evaluation of LLMs Values
As Large Language Models (LLMs) achieve remarkable breakthroughs, aligning their values with humans has become imperative for their responsible development and customized applications. However, there still lack evaluations of LLMs values that fulfill three desirable goals. (1) Value Clarification: We expect to clarify the underlying values of LLMs precisely and comprehensively, while current evaluations focus narrowly on safety risks such as bias and toxicity. (2) Evaluation Validity: Existing …

Swifts’ decline: how can Britons help these remarkable birds? #Britain

A Preference-Driven Methodology for High-Quality Solidity Code Generation
Zhiyuan Peng, Xin Yin, Chenhao Ying, Chao Ni, Yuan Luo
https://arxiv.org/abs/2506.03006

A Preference-Driven Methodology for High-Quality Solidity Code Generation
While Large Language Models (LLMs) have demonstrated remarkable progress in generating functionally correct Solidity code, they continue to face critical challenges in producing gas-efficient and secure code, which are critical requirements for real-world smart contract deployment. Although recent advances leverage Supervised Fine-Tuning (SFT) and Direct Preference Optimization (DPO) for code preference alignment, existing approaches treat functional correctness, gas optimization, and security …

This https://arxiv.org/abs/2411.07502 has been replaced.
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Ab initio informed 20Ne(p, p$α$)16O reaction elucidates the emergence of alpha clustering from chiral potentials
We report on the first \textit{ab initio} informed $α$ knock-out reaction in the intermediate-mass region, with the aim to probe the underlying chiral potential and its impact on the emergence of alpha clustering in this mass region. The theoretical predictions of the $α+^{16}$O clustering in the $^{20}$Ne ground state, based on the \textit{ab initio} symmetry-adapted no-core shell model, yield a triple differential cross section for $^{20}$Ne(p, p$α$)$^{16}$O that is in a remarkable agreeme…

G{\"o}pel Varieties
Vladimiro Benedetti (LJAD), Michele Bolognesi (IMAG), Daniele Faenzi (IMB), Laurent Manivel (IMT)
https://arxiv.org/abs/2506.22030

G{ö}pel Varieties
We show that the Coble hypersurfaces, uniquely characterized by the remarkable property that their singular loci are an abelian surface and a Kummer threefold, respectively, belong to a family of hypersurfaces exhibiting similar behavior, but defined in various types of homogeneous spaces. With the help of Jordan-Vinberg theory, we show how these hypersurfaces can be parametrized by G{ö}pel type varieties inside projectivized representations of complex reflection groups.

FairHuman: Boosting Hand and Face Quality in Human Image Generation with Minimum Potential Delay Fairness in Diffusion Models
Yuxuan Wang, Tianwei Cao, Huayu Zhang, Zhongjiang He, Kongming Liang, Zhanyu Ma
https://arxiv.org/abs/2507.02714

FairHuman: Boosting Hand and Face Quality in Human Image Generation with Minimum Potential Delay Fairness in Diffusion Models
Image generation has achieved remarkable progress with the development of large-scale text-to-image models, especially diffusion-based models. However, generating human images with plausible details, such as faces or hands, remains challenging due to insufficient supervision of local regions during training. To address this issue, we propose FairHuman, a multi-objective fine-tuning approach designed to enhance both global and local generation quality fairly. Specifically, we first construct thr…

Failure by Interference: Language Models Make Balanced Parentheses Errors When Faulty Mechanisms Overshadow Sound Ones
Daking Rai, Samuel Miller, Kevin Moran, Ziyu Yao
https://arxiv.org/abs/2507.00322

Failure by Interference: Language Models Make Balanced Parentheses Errors When Faulty Mechanisms Overshadow Sound Ones
Despite remarkable advances in coding capabilities, language models (LMs) still struggle with simple syntactic tasks such as generating balanced parentheses. In this study, we investigate the underlying mechanisms behind the persistence of these errors across LMs of varying sizes (124M-7B) to both understand and mitigate the errors. Our study reveals that LMs rely on a number of components (attention heads and FF neurons) that independently make their own predictions. While some components reli…

Maybe I'm just being horny but it just occurred to me this gentleman and this book are remarkable fetish potential.

Symmetry-protected electronic metastability in an optically driven cuprate ladder
Hari Padma, Filippo Glerean, Sophia F. R. TenHuisen, Zecheng Shen, Haoxin Wang, Luogen Xu, Joshua D. Elliott, Christopher C. Homes, Elizabeth Skoropata, Hiroki Ueda, Biaolong Liu, Eugenio Paris, Arnau Romaguera, Byungjune Lee, Wei He, Yu Wang, Seng Huat Lee, Hyeongi Choi, Sang-Youn Park, Zhiqiang Mao, Matteo Calandra, Hoyoung Jang, Elia Razzoli, Mark P. M. Dean, Yao Wang, Matteo Mitrano

Symmetry-protected electronic metastability in an optically driven cuprate ladder
Optically excited quantum materials exhibit nonequilibrium states with remarkable emergent properties, but these phenomena are usually transient, decaying on picosecond timescales and limiting practical applications. Advancing the design and control of nonequilibrium phases requires the development of targeted strategies to achieve long-lived, metastable phases. Here, we report the discovery of symmetry-protected electronic metastability in the model cuprate ladder Sr$_{14}$Cu$_{24}$O$_{41}$. U…

A remarkable dynamical symmetry of the Landau problem
Tekin Dereli, Philippe Nounahon, Todor Popov
https://arxiv.org/abs/2506.11642 https://

A remarkable dynamical symmetry of the Landau problem
We show that the dynamical group of an electron in a constant magnetic field is the group of symplectomorphisms $Sp(4,\mathbb{R})$. It is generated by the spinorial realization of the conformal algebra $\mathfrak{so}(2,3)$ considered in Dirac's seminal paper "A Remarkable Representation of the 3 + 2 de Sitter Group". The symplectic group $Sp(4,\mathbb{R})$ is the double covering of the conformal group $SO(2,3)$ of 2+1 dimensional Minkowski spacetime which is in turn the dynamical group of a hyd…

ReFlow-VC: Zero-shot Voice Conversion Based on Rectified Flow and Speaker Feature Optimization
Pengyu Ren, Wenhao Guan, Kaidi Wang, Peijie Chen, Qingyang Hong, Lin Li
https://arxiv.org/abs/2506.01032

ReFlow-VC: Zero-shot Voice Conversion Based on Rectified Flow and Speaker Feature Optimization
In recent years, diffusion-based generative models have demonstrated remarkable performance in speech conversion, including Denoising Diffusion Probabilistic Models (DDPM) and others. However, the advantages of these models come at the cost of requiring a large number of sampling steps. This limitation hinders their practical application in real-world scenarios. In this paper, we introduce ReFlow-VC, a novel high-fidelity speech conversion method based on rectified flow. Specifically, ReFlow-VC…

USB: A Comprehensive and Unified Safety Evaluation Benchmark for Multimodal Large Language Models
Baolin Zheng, Guanlin Chen, Hongqiong Zhong, Qingyang Teng, Yingshui Tan, Zhendong Liu, Weixun Wang, Jiaheng Liu, Jian Yang, Huiyun Jing, Jincheng Wei, Wenbo Su, Xiaoyong Zhu, Bo Zheng, Kaifu Zhang
https://arxiv.org/abs/2505.23793…

USB: A Comprehensive and Unified Safety Evaluation Benchmark for Multimodal Large Language Models
Despite their remarkable achievements and widespread adoption, Multimodal Large Language Models (MLLMs) have revealed significant security vulnerabilities, highlighting the urgent need for robust safety evaluation benchmarks. Existing MLLM safety benchmarks, however, fall short in terms of data quality and coverge, and modal risk combinations, resulting in inflated and contradictory evaluation results, which hinders the discovery and governance of security concerns. Besides, we argue that vulne…

🪤 A California dairy tried to capture its methane, and it worked
#dairy

A California dairy tried to capture its methane, and it worked
A giant, balloon-like tarp stretches over a lagoon of manure on a Central Valley dairy farm, concealing a quiet but remarkable transformation. Methane, a potent climate-warming gas, is being captured and cleaned instead of released into the atmosphere.

Reuse or Generate? Accelerating Code Editing via Edit-Oriented Speculative Decoding
Peiding Wang, Li Zhang, Fang Liu, Yinghao Zhu, Wang Xu, Lin Shi, Xiaoli Lian, Minxiao Li, Bo Shen, An Fu
https://arxiv.org/abs/2506.02780

Reuse or Generate? Accelerating Code Editing via Edit-Oriented Speculative Decoding
Large Language Models (LLMs) have demonstrated remarkable capabilities in code editing, substantially enhancing software development productivity. However, the inherent complexity of code editing tasks forces existing approaches to rely on LLMs' autoregressive end-to-end generation, where decoding speed plays a critical role in efficiency. While inference acceleration techniques like speculative decoding are applied to improve the decoding efficiency, these methods fail to account for the uniqu…

A Survey on Vision-Language-Action Models: An Action Tokenization Perspective
Yifan Zhong, Fengshuo Bai, Shaofei Cai, Xuchuan Huang, Zhang Chen, Xiaowei Zhang, Yuanfei Wang, Shaoyang Guo, Tianrui Guan, Ka Nam Lui, Zhiquan Qi, Yitao Liang, Yuanpei Chen, Yaodong Yang
https://arxiv.org/abs/2507.01925

A Survey on Vision-Language-Action Models: An Action Tokenization Perspective
The remarkable advancements of vision and language foundation models in multimodal understanding, reasoning, and generation has sparked growing efforts to extend such intelligence to the physical world, fueling the flourishing of vision-language-action (VLA) models. Despite seemingly diverse approaches, we observe that current VLA models can be unified under a single framework: vision and language inputs are processed by a series of VLA modules, producing a chain of \textit{action tokens} that …

"An overlooked biocultural landscape in Sri Lanka receives overdue protection"
#SriLanka #Environment #Nature

An overlooked biocultural landscape in Sri Lanka receives overdue protection
COLOMBO — Nestled in the eastern edge of Sri Lanka’s Uva province, Nilgala stands out as a landscape of remarkable ecological and cultural importance. Long overlooked in mainstream conservation efforts despite its significance, Nilgala finally received due recognition on June 2 when it was declared a forest reserve covering its full extent of 40,685 hectares […]

Gigantic Harmonic Generation in N\'eel-Torque Antiferromagnetic Resonance
Kuangyin Deng, Ran Cheng
https://arxiv.org/abs/2506.22974 https://

Gigantic Harmonic Generation in Néel-Torque Antiferromagnetic Resonance
We theoretically investigate the resonant and higher-harmonic magnetic responses of a collinear antiferromagnet induced by Néel spin-orbit torques (NSOTs). By deriving the dynamical susceptibilities up to the third harmonic, we find remarkable NSOT-induced amplifications of the linear and nonlinear magnetic dynamics by orders of magnitude compared to conventional spin-orbit torques, enabling highly-efficient frequency conversion in the sub-terahertz frequency range. We then propose a multilaye…

During my research into my family's extended genealogy, I've come across some remarkable descriptions of people from old documents.

Gaussian Invariant Markov Chain Monte Carlo
Michalis K. Titsias, Angelos Alexopoulos, Siran Liu, Petros Dellaportas
https://arxiv.org/abs/2506.21511 https:…

Gaussian Invariant Markov Chain Monte Carlo
We develop sampling methods, which consist of Gaussian invariant versions of random walk Metropolis (RWM), Metropolis adjusted Langevin algorithm (MALA) and second order Hessian or Manifold MALA. Unlike standard RWM and MALA we show that Gaussian invariant sampling can lead to ergodic estimators with improved statistical efficiency. This is due to a remarkable property of Gaussian invariance that allows us to obtain exact analytical solutions to the Poisson equation for Gaussian targets. These …

from my link log —
10 years of pomological watercolors.
https://parkerhiggins.net/2025/04/10-years-of-pomological-watercolors/
saved 2025-04-13

10 years of pomological watercolors
A decade ago today I published a blog post calling for the US government to release its paintings of fruits. The Pomological Watercolor Collection, as I had recently come to know, is a beautiful and remarkable corpus of over 7,000 pictures of fruits and other biological specimens, made between the 1880s and 1940s. Through a handful of FOIA requests I’d learned that the images had been meticulously digitized and put online for purchase, but that less than 100 pictures had been sold that way �…

Uncovering the origin of bound state in the continuum
Zeyu Rao, Changling Zou, Yang Chen, Guangcan Guo, Ming Gong
https://arxiv.org/abs/2506.19678 https://…

Uncovering the origin of bound state in the continuum
Bound state in the continuum (BIC) and quasi-BIC represent a remarkable class of wave functions that disobey conventional intuition by exhibiting spatially localized modes embedded in the continuum spectrum. In recent years, these states have found important applications in interdisciplinary systems as a non-radiating mode with ultra-long lifetime. In these applications, a key question is how to convert a quasi-BIC into an exact BIC, and what the general criterion is for this transition. In thi…

SAR-GS: 3D Gaussian Splatting for Synthetic Aperture Radar Target Reconstruction
Aobo Li, Zhengxin Lei, Jiangtao Wei, Feng Xu
https://arxiv.org/abs/2506.21633

SAR-GS: 3D Gaussian Splatting for Synthetic Aperture Radar Target Reconstruction
Three-dimensional target reconstruction from synthetic aperture radar (SAR) imagery is crucial for interpreting complex scattering information in SAR data. However, the intricate electromagnetic scattering mechanisms inherent to SAR imaging pose significant reconstruction challenges. Inspired by the remarkable success of 3D Gaussian Splatting (3D-GS) in optical domain reconstruction, this paper presents a novel SAR Differentiable Gaussian Splatting Rasterizer (SDGR) specifically designed for SA…

I got this post by @… in my email today, it was forwarded while it still was attributed to Liz Cheney with this preface which I agree with:
"When she was in Congress, I disagreed with almost everything she said and every vote she made. But on the transcendent issue of our time — protecting our democracy from Trump and the forces of authoritarianism and fascism — Liz Cheney has been correct, clear, and courageous."
Turns out the message is not by Liz Cheney but is well worth reading as a kick in the ass to the Democratic Party.
https://robertreich.substack.com/p/a-remarkable-message

Acoustic-Assisted Fabrication of Thin Shells with Spatially Distributed Imperfections
Ilyes Krida, Jacob Tang, Daniel Floryan, Tian Chen
https://arxiv.org/abs/2506.23828

Acoustic-Assisted Fabrication of Thin Shells with Spatially Distributed Imperfections
Thin-shell structures, found in biological systems such as beetle carapaces and widely used in aerospace, civil, and mechanical engineering, achieve remarkable strength-to-mass ratio given their slenderness and curved geometries. However, their load-bearing capacity is highly sensitive to geometric imperfections, which are often unavoidable during fabrication and can trigger subcritical buckling. Silicone-based hemispherical domes have served as an experimental modal system to study this phenom…

A system of 2 nonlinearly coupled ODEs which is explicitly solvable and possibly isochronous provided its coefficients are suitably restricted
Fabio Briscese, Francesco Calogero, Farrin Payandeh
https://arxiv.org/abs/2505.24370

A system of 2 nonlinearly coupled ODEs which is explicitly solvable and possibly isochronous provided its coefficients are suitably restricted
In this paper we discuss some remarkable properties of the autonomous system of 2 first-order Ordinary Differential Equations (ODEs), which equates the derivatives $\dot{x}_n(t)$ ($n = 1, 2$) of the 2 dependent variables $x_n(t)$ to the ratios of polynomials (with constant coefficients) in the 2 variables $x_n (t)$: each of the 2 (a priori different) polynomials $P_3^{(n)}(x_1, x_2)$ in the 2 numerators is of degree 3; the 2 denominators are instead given by the same polynomial $P_1(x_1, x_2)$ …

Globally Consistent RGB-D SLAM with 2D Gaussian Splatting
Xingguang Zhong, Yue Pan, Liren Jin, Marija Popovi\'c, Jens Behley, Cyrill Stachniss
https://arxiv.org/abs/2506.00970

Globally Consistent RGB-D SLAM with 2D Gaussian Splatting
Recently, 3D Gaussian splatting-based RGB-D SLAM displays remarkable performance of high-fidelity 3D reconstruction. However, the lack of depth rendering consistency and efficient loop closure limits the quality of its geometric reconstructions and its ability to perform globally consistent mapping online. In this paper, we present 2DGS-SLAM, an RGB-D SLAM system using 2D Gaussian splatting as the map representation. By leveraging the depth-consistent rendering property of the 2D variant, we pr…

Kwai Keye-VL Technical Report
Kwai Keye Team, Biao Yang, Bin Wen, Changyi Liu, Chenglong Chu, Chengru Song, Chongling Rao, Chuan Yi, Da Li, Dunju Zang, Fan Yang, Guorui Zhou, Hao Peng, Haojie Ding, Jiaming Huang, Jiangxia Cao, Jiankang Chen, Jingyun Hua, Jin Ouyang, Kaibing Chen, Kaiyu Jiang, Kaiyu Tang, Kun Gai, Shengnan Zhang, Siyang Mao, Sui Huang, Tianke Zhang, Tingting Gao, Wei Chen, Wei Yuan, Xiangyu Wu, Xiao Hu, Xingyu Lu, Yang Zhou, Yi-Fan Zhang, Yiping Yang, Yulong Chen, Zhenh…

Kwai Keye-VL Technical Report
While Multimodal Large Language Models (MLLMs) demonstrate remarkable capabilities on static images, they often fall short in comprehending dynamic, information-dense short-form videos, a dominant medium in today's digital landscape. To bridge this gap, we introduce \textbf{Kwai Keye-VL}, an 8-billion-parameter multimodal foundation model engineered for leading-edge performance in short-video understanding while maintaining robust general-purpose vision-language abilities. The development of Ke…

StableCodec: Taming One-Step Diffusion for Extreme Image Compression
Tianyu Zhang, Xin Luo, Li Li, Dong Liu
https://arxiv.org/abs/2506.21977 https://

StableCodec: Taming One-Step Diffusion for Extreme Image Compression
Diffusion-based image compression has shown remarkable potential for achieving ultra-low bitrate coding (less than 0.05 bits per pixel) with high realism, by leveraging the generative priors of large pre-trained text-to-image diffusion models. However, current approaches require a large number of denoising steps at the decoder to generate realistic results under extreme bitrate constraints, limiting their application in real-time compression scenarios. Additionally, these methods often sacrific…

SpeechAccentLLM: A Unified Framework for Foreign Accent Conversion and Text to Speech
Cheng Zhuangfei, Zhang Guangyan, Tu Zehai, Song Yangyang, Mao Shuiyang, Jiao Xiaoqi, Li Jingyu, Guo Yiwen, Wu Jiasong
https://arxiv.org/abs/2507.01348

SpeechAccentLLM: A Unified Framework for Foreign Accent Conversion and Text to Speech
Foreign accent conversion (FAC) in speech processing remains a challenging task. Building on the remarkable success of large language models (LLMs) in Text-to-Speech (TTS) tasks, this study investigates the adaptation of LLM-based techniques for FAC, which we term SpeechAccentLLM. At the core of this framework, we introduce SpeechCodeVAE, the first model to integrate connectionist temporal classification (CTC) directly into codebook discretization for speech content tokenization. This novel arc…

Literature-Grounded Novelty Assessment of Scientific Ideas
Simra Shahid, Marissa Radensky, Raymond Fok, Pao Siangliulue, Daniel S. Weld, Tom Hope
https://arxiv.org/abs/2506.22026 …

Literature-Grounded Novelty Assessment of Scientific Ideas
Automated scientific idea generation systems have made remarkable progress, yet the automatic evaluation of idea novelty remains a critical and underexplored challenge. Manual evaluation of novelty through literature review is labor-intensive, prone to error due to subjectivity, and impractical at scale. To address these issues, we propose the Idea Novelty Checker, an LLM-based retrieval-augmented generation (RAG) framework that leverages a two-stage retrieve-then-rerank approach. The Idea Nove…

evMLP: An Efficient Event-Driven MLP Architecture for Vision
Zhentan Zheng
https://arxiv.org/abs/2507.01927 https://arxiv.org/pdf/250…

evMLP: An Efficient Event-Driven MLP Architecture for Vision
Deep neural networks have achieved remarkable results in computer vision tasks. In the early days, Convolutional Neural Networks (CNNs) were the mainstream architecture. In recent years, Vision Transformers (ViTs) have become increasingly popular. In addition, exploring applications of multi-layer perceptrons (MLPs) has provided new perspectives for research into vision model architectures. In this paper, we present evMLP accompanied by a simple event-driven local update mechanism. The proposed…

CODEMENV: Benchmarking Large Language Models on Code Migration
Keyuan Cheng, Xudong Shen, Yihao Yang, Tengyue Wang, Yang Cao, Muhammad Asif Ali, Hanbin Wang, Lijie Hu, Di Wang
https://arxiv.org/abs/2506.00894

CODEMENV: Benchmarking Large Language Models on Code Migration
Large language models (LLMs) have shown remarkable capabilities across various software engineering tasks; however, their effectiveness in code migration, adapting code to run in different environments, remains insufficiently studied. In this work, we introduce CODEMENV: Code Migration Across Environment, a new benchmark specifically designed to assess LLMs' abilities in code migration scenarios. CODEMENV consists of 922 examples spanning 19 Python and Java packages, and covers three core tasks…

Evaluating Scoring Bias in LLM-as-a-Judge
Qingquan Li, Shaoyu Dou, Kailai Shao, Chao Chen, Haixiang Hu
https://arxiv.org/abs/2506.22316 https://

Evaluating Scoring Bias in LLM-as-a-Judge
The remarkable performance of Large Language Models (LLMs) gives rise to``LLM-as-a-Judge'', where LLMs are employed as evaluators for complex tasks. Moreover, it has been widely adopted across fields such as Natural Language Processing (NLP), preference learning, and various specific domains. However, there are various biases within LLM-as-a-Judge, which adversely affect the fairness and reliability of judgments. Current research on evaluating or mitigating bias in LLM-as-a-Judge predominantly …

The Societal Impact of Foundation Models: Advancing Evidence-based AI Policy
Rishi Bommasani
https://arxiv.org/abs/2506.23123 https://

The Societal Impact of Foundation Models: Advancing Evidence-based AI Policy
Artificial intelligence is humanity's most promising technology because of the remarkable capabilities offered by foundation models. Yet, the same technology brings confusion and consternation: foundation models are poorly understood and they may precipitate a wide array of harms. This dissertation explains how technology and society coevolve in the age of AI, organized around three themes. First, the conceptual framing: the capabilities, risks, and the supply chain that grounds foundation mode…

How Well Does GPT-4o Understand Vision? Evaluating Multimodal Foundation Models on Standard Computer Vision Tasks
Rahul Ramachandran, Ali Garjani, Roman Bachmann, Andrei Atanov, O\u{g}uzhan Fatih Kar, Amir Zamir
https://arxiv.org/abs/2507.01955

How Well Does GPT-4o Understand Vision? Evaluating Multimodal Foundation Models on Standard Computer Vision Tasks
Multimodal foundation models, such as GPT-4o, have recently made remarkable progress, but it is not clear where exactly these models stand in terms of understanding vision. In this paper, we benchmark the performance of popular multimodal foundation models (GPT-4o, o4-mini, Gemini 1.5 Pro and Gemini 2.0 Flash, Claude 3.5 Sonnet, Qwen2-VL, Llama 3.2) on standard computer vision tasks (semantic segmentation, object detection, image classification, depth and surface normal prediction) using establ…

Reactive Aerobatic Flight via Reinforcement Learning
Zhichao Han, Xijie Huang, Zhuxiu Xu, Jiarui Zhang, Yuze Wu, Mingyang Wang, Tianyue Wu, Fei Gao
https://arxiv.org/abs/2505.24396

Reactive Aerobatic Flight via Reinforcement Learning
Quadrotors have demonstrated remarkable versatility, yet their full aerobatic potential remains largely untapped due to inherent underactuation and the complexity of aggressive maneuvers. Traditional approaches, separating trajectory optimization and tracking control, suffer from tracking inaccuracies, computational latency, and sensitivity to initial conditions, limiting their effectiveness in dynamic, high-agility scenarios. Inspired by recent breakthroughs in data-driven methods, we propose …

StreamLink: Large-Language-Model Driven Distributed Data Engineering System
Dawei Feng, Di Mei, Huiri Tan, Lei Ren, Xianying Lou, Zhangxi Tan
https://arxiv.org/abs/2505.21575

StreamLink: Large-Language-Model Driven Distributed Data Engineering System
Large Language Models (LLMs) have shown remarkable proficiency in natural language understanding (NLU), opening doors for innovative applications. We introduce StreamLink - an LLM-driven distributed data system designed to improve the efficiency and accessibility of data engineering tasks. We build StreamLink on top of distributed frameworks such as Apache Spark and Hadoop to handle large data at scale. One of the important design philosophies of StreamLink is to respect user data privacy by ut…

APRMCTS: Improving LLM-based Automated Program Repair with Iterative Tree Search
Haichuan Hu, Congqing He, Hao Zhang, Xiaochen Xie, Quanjun Zhang
https://arxiv.org/abs/2507.01827 …

APRMCTS: Improving LLM-based Automated Program Repair with Iterative Tree Search
Automated Program Repair (APR) attempts to fix software bugs without human intervention, which plays a crucial role in software development and maintenance. Recently, with the advances in Large Language Models (LLMs), a rapidly increasing number of APR techniques have been proposed with remarkable performance. However, existing LLM-based APR techniques typically adopt trial-and-error strategies, which suffer from two major drawbacks: (1) inherently limited patch effectiveness due to local explo…

A mature approach to handling challenging issues in church life - a historical example. #baptist

The College Lane Covenant - Miscellanea Edintone
A remarkable example from a Baptist Church in Northampton, England, models how controversial issues can be handled well, even if not fully resolved.

This https://arxiv.org/abs/2505.18975 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csAR_…

FastMamba: A High-Speed and Efficient Mamba Accelerator on FPGA with Accurate Quantization
State Space Models (SSMs), like recent Mamba2, have achieved remarkable performance and received extensive attention. However, deploying Mamba2 on resource-constrained edge devices encounters many problems: severe outliers within the linear layer challenging the quantization, diverse and irregular element-wise tensor operations, and hardware-unfriendly nonlinear functions in the SSM block. To address these issues, this paper presents FastMamba, a dedicated accelerator on FPGA with hardware-algo…

Training Language Model to Critique for Better Refinement
Tianshu Yu, Chao Xiang, Mingchuan Yang, Pei Ke, Bosi Wen, Cunxiang Wang, Jiale Cheng, Li Zhang, Xinyu Mu, Chuxiong Sun, Minlie Huang
https://arxiv.org/abs/2506.22157

Training Language Model to Critique for Better Refinement
Large language models (LLMs) have demonstrated remarkable evaluation and critique capabilities, providing insightful feedback and identifying flaws in various tasks. However, limited research has explored which types of critiques are most effective for improving model responses or how to generate such critiques. To address this gap, we introduce \textbf{R}efinement-oriented \textbf{C}ritique \textbf{O}ptimization (RCO), a novel framework designed to train critic models using refinement signals.…

Kinematic Confirmation of a Remarkable Linear Trail of Galaxies in the NGC 1052 Field, Consistent with Formation in a High-Speed Bullet Dwarf Collision
Michael A. Keim, Pieter van Dokkum, Zili Shen, Harrison Souchereau, Imad Pasha, Shany Danieli, Roberto Abraham, Aaron J. Romanowsky, Yimeng Tang
https://arxiv.org/abs/2506.10220

Kinematic Confirmation of a Remarkable Linear Trail of Galaxies in the NGC 1052 Field, Consistent with Formation in a High-Speed Bullet Dwarf Collision
A unique linear trail of diffuse galaxies was recently identified in the NGC 1052 field. This trail includes the remarkable, ultra-diffuse galaxies DF2 and DF4 which lack dark matter and host unusually luminous globular clusters. It has been proposed that the trail formed via a high-speed collision between two gas-rich dwarf galaxies. This scenario predicts that the trail galaxies are kinematically connected and follow a specific trend in radial velocity as a function of position, based on the …

Prospects and challenges of Bluetooth backscatters system
Jingyun Du
https://arxiv.org/abs/2505.21526 https://arxiv.org/pdf/2505.2152…

Prospects and challenges of Bluetooth backscatters system
Bluetooth backscatter systems, as a crucial technology for low-power communication in the Internet of Things (IoT), have witnessed remarkable development in recent years. This article comprehensively analyzes multiple related papers, including the latest advancements in RF-Transformer and B2Loc systems, summarizes their research progress, challenges faced, and classification, and explores the application prospects and future development directions of such systems. Bluetooth backscatter systems …

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…

This https://arxiv.org/abs/2505.19595 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

Accelerating Diffusion-based Text-to-Speech Model Training with Dual Modality Alignment
The goal of this paper is to optimize the training process of diffusion-based text-to-speech models. While recent studies have achieved remarkable advancements, their training demands substantial time and computational costs, largely due to the implicit guidance of diffusion models in learning complex intermediate representations. To address this, we propose A-DMA, an effective strategy for Accelerating training with Dual Modality Alignment. Our method introduces a novel alignment pipeline leve…

Retrieval-Confused Generation is a Good Defender for Privacy Violation Attack of Large Language Models
Wanli Peng, Xin Chen, Hang Fu, XinYu He, Xue Yiming, Juan Wen
https://arxiv.org/abs/2506.19889

Retrieval-Confused Generation is a Good Defender for Privacy Violation Attack of Large Language Models
Recent advances in large language models (LLMs) have made a profound impact on our society and also raised new security concerns. Particularly, due to the remarkable inference ability of LLMs, the privacy violation attack (PVA), revealed by Staab et al., introduces serious personal privacy issues. Existing defense methods mainly leverage LLMs to anonymize the input query, which requires costly inference time and cannot gain satisfactory defense performance. Moreover, directly rejecting the PVA …

Ark: An Open-source Python-based Framework for Robot Learning
Magnus Dierking, Christopher E. Mower, Sarthak Das, Huang Helong, Jiacheng Qiu, Cody Reading, Wei Chen, Huidong Liang, Huang Guowei, Jan Peters, Quan Xingyue, Jun Wang, Haitham Bou-Ammar
https://arxiv.org/abs/2506.21628

Ark: An Open-source Python-based Framework for Robot Learning
Robotics has made remarkable hardware strides-from DARPA's Urban and Robotics Challenges to the first humanoid-robot kickboxing tournament-yet commercial autonomy still lags behind progress in machine learning. A major bottleneck is software: current robot stacks demand steep learning curves, low-level C/C++ expertise, fragmented tooling, and intricate hardware integration, in stark contrast to the Python-centric, well-documented ecosystems that propelled modern AI. We introduce ARK, an open-so…

From Release to Adoption: Challenges in Reusing Pre-trained AI Models for Downstream Developers
Peerachai Banyongrakkul, Mansooreh Zahedi, Patanamon Thongtanunam, Christoph Treude, Haoyu Gao
https://arxiv.org/abs/2506.23234

From Release to Adoption: Challenges in Reusing Pre-trained AI Models for Downstream Developers
Pre-trained models (PTMs) have gained widespread popularity and achieved remarkable success across various fields, driven by their groundbreaking performance and easy accessibility through hosting providers. However, the challenges faced by downstream developers in reusing PTMs in software systems are less explored. To bridge this knowledge gap, we qualitatively created and analyzed a dataset of 840 PTM-related issue reports from 31 OSS GitHub projects. We systematically developed a comprehensi…

This https://arxiv.org/abs/2312.10741 has been replaced.
link: https://scholar.google.com/scholar?q=a

StyleSinger: Style Transfer for Out-of-Domain Singing Voice Synthesis
Style transfer for out-of-domain (OOD) singing voice synthesis (SVS) focuses on generating high-quality singing voices with unseen styles (such as timbre, emotion, pronunciation, and articulation skills) derived from reference singing voice samples. However, the endeavor to model the intricate nuances of singing voice styles is an arduous task, as singing voices possess a remarkable degree of expressiveness. Moreover, existing SVS methods encounter a decline in the quality of synthesized singin…

ReCode: Updating Code API Knowledge with Reinforcement Learning
Haoze Wu, Yunzhi Yao, Wenhao Yu, Huajun Chen, Ningyu Zhang
https://arxiv.org/abs/2506.20495

ReCode: Updating Code API Knowledge with Reinforcement Learning
Large Language Models (LLMs) exhibit remarkable code generation capabilities but falter when adapting to frequent updates in external library APIs. This critical limitation, stemming from reliance on outdated API knowledge from their training data, even with access to current documentation, impedes reliable code generation in dynamic environments. To tackle this issue, we propose ReCode (rule-based Reinforcement learning for Code Update), a novel framework that mimics human programmer adaptatio…

SV-LLM: An Agentic Approach for SoC Security Verification using Large Language Models
Dipayan Saha, Shams Tarek, Hasan Al Shaikh, Khan Thamid Hasan, Pavan Sai Nalluri, Md. Ajoad Hasan, Nashmin Alam, Jingbo Zhou, Sujan Kumar Saha, Mark Tehranipoor, Farimah Farahmandi
https://arxiv.org/abs/2506.20415…

SV-LLM: An Agentic Approach for SoC Security Verification using Large Language Models
Ensuring the security of complex system-on-chips (SoCs) designs is a critical imperative, yet traditional verification techniques struggle to keep pace due to significant challenges in automation, scalability, comprehensiveness, and adaptability. The advent of large language models (LLMs), with their remarkable capabilities in natural language understanding, code generation, and advanced reasoning, presents a new paradigm for tackling these issues. Moving beyond monolithic models, an agentic ap…

GPTailor: Large Language Model Pruning Through Layer Cutting and Stitching
Guinan Su, Li Shen, Lu Yin, Shiwei Liu, Yanwu Yang, Jonas Geiping
https://arxiv.org/abs/2506.20480

GPTailor: Large Language Model Pruning Through Layer Cutting and Stitching
Large language models (LLMs) have shown remarkable capabilities in language understanding and generation. However, such impressive capability typically comes with a substantial model size, which presents significant challenges in deployment and inference. While structured pruning of model parameters offers a promising way to reduce computational costs at deployment time, current methods primarily focus on single model pruning. In this work, we develop a novel strategy to compress models by stra…

GenHSI: Controllable Generation of Human-Scene Interaction Videos
Zekun Li, Rui Zhou, Rahul Sajnani, Xiaoyan Cong, Daniel Ritchie, Srinath Sridhar
https://arxiv.org/abs/2506.19840

GenHSI: Controllable Generation of Human-Scene Interaction Videos
Large-scale pre-trained video diffusion models have exhibited remarkable capabilities in diverse video generation. However, existing solutions face several challenges in using these models to generate long movie-like videos with rich human-object interactions that include unrealistic human-scene interaction, lack of subject identity preservation, and require expensive training. We propose GenHSI, a training-free method for controllable generation of long human-scene interaction videos (HSI). Ta…