Tootfinder

Input Time Scaling
Rapheal Huang (Yuming), Weilong Guo
https://arxiv.org/abs/2508.13654 https://arxiv.org/pdf/2508.13654

Input Time Scaling
Current Large Language Models (LLMs) are usually post-trained on large-scale carefully curated datasets (data & training scaling) and doing reasoning in test time (inference time scaling). In this work, we present a new scaling paradigm, Input Time Scaling, to complement previous scaling methods by putting resources on queries (input time). During training and testing, we combine meta-knowledge from LLMs to refine inputs with different strategies. We also find a new phenomenon, training-testing…

from my link log —
A brief consideration of input shapes for fuzzers.
https://addisoncrump.info/research/consideration-of-input-shapes/
saved 2025-08-17

Evaluating Retrieval-Augmented Generation vs. Long-Context Input for Clinical Reasoning over EHRs
Skatje Myers, Dmitriy Dligach, Timothy A. Miller, Samantha Barr, Yanjun Gao, Matthew Churpek, Anoop Mayampurath, Majid Afshar
https://arxiv.org/abs/2508.14817

Evaluating Retrieval-Augmented Generation vs. Long-Context Input for Clinical Reasoning over EHRs
Electronic health records (EHRs) are long, noisy, and often redundant, posing a major challenge for the clinicians who must navigate them. Large language models (LLMs) offer a promising solution for extracting and reasoning over this unstructured text, but the length of clinical notes often exceeds even state-of-the-art models' extended context windows. Retrieval-augmented generation (RAG) offers an alternative by retrieving task-relevant passages from across the entire EHR, potentially reducin…

SCOPE for Hexapod Gait Generation
Jim O'Connor, Jay B. Nash, Derin Gezgin, Gary B. Parker
https://arxiv.org/abs/2507.13539 https://

SCOPE for Hexapod Gait Generation
Evolutionary methods have previously been shown to be an effective learning method for walking gaits on hexapod robots. However, the ability of these algorithms to evolve an effective policy rapidly degrades as the input space becomes more complex. This degradation is due to the exponential growth of the solution space, resulting from an increasing parameter count to handle a more complex input. In order to address this challenge, we introduce Sparse Cosine Optimized Policy Evolution (SCOPE). S…

A very cool thread about live audio for video from @…
#gearsquad
https://old.mermaid…

Revisiting Prompt Engineering: A Comprehensive Evaluation for LLM-based Personalized Recommendation
Genki Kusano, Kosuke Akimoto, Kunihiro Takeoka
https://arxiv.org/abs/2507.13525

Revisiting Prompt Engineering: A Comprehensive Evaluation for LLM-based Personalized Recommendation
Large language models (LLMs) can perform recommendation tasks by taking prompts written in natural language as input. Compared to traditional methods such as collaborative filtering, LLM-based recommendation offers advantages in handling cold-start, cross-domain, and zero-shot scenarios, as well as supporting flexible input formats and generating explanations of user behavior. In this paper, we focus on a single-user setting, where no information from other users is used. This setting is practi…

Active Learning of Symbolic Mealy Automata
Kengo Irie, Masaki Waga, Kohei Suenaga
https://arxiv.org/abs/2509.14694 https://arxiv.org/pdf/2509.14694

Active Learning of Symbolic Mealy Automata
We propose $Λ^*_M$-an active learning algorithm that learns symbolic Mealy automata, which support infinite input alphabets and multiple output characters. Each of these two features has been addressed separately in prior work. Combining these two features poses a challenge in learning the outputs corresponding to potentially infinite sets of input characters at each state. To address this challenge, we introduce the notion of essential input characters, a finite set of input characters that i…

Ein spannender Morgen, danke für euren ganzen Input, ich habe wieder einiges über mich gelernt.

AutoMPC: A Code Generator for MPC-based Automated Driving
Georg Schildbach, Jasper Pflughaupt
https://arxiv.org/abs/2508.13656 https://arxiv.org/pdf/2508.1…

AutoMPC: A Code Generator for MPC-based Automated Driving
Model Predictive Control (MPC) is a powerful technique to control nonlinear, multi-input multi-output systems subject to input and state constraints. It is now a standard tool for trajectory tracking control of automated vehicles. As such it has been used in many research and development projects. However, MPC faces several challenges to be integrated into industrial production vehicles. The most important ones are its high computational demands and the complexity of implementation. The softwar…

Hands-on with Meta Ray-Ban Display and Neural Band: small display adds new functionality, useful real-time translation, Neural Band seems the ideal input method (Ben Lang/Road to VR)
https://www.roadtovr.com/hands-on-meta-ray-b…

Hands-on: Meta Ray-Ban Display Glasses & Neural Band Offer a Glimpse of Future AR Glasses
The newly announced Meta Ray-Ban Display glasses, and the ‘Neural Band’ input device that comes with them, are still far from proper augmented reality. But Meta has made several clever design choices that will pay dividends once their true AR glasses are ready for the masses. The Ray-Ban Display glasses are a new category for …

Woke up to email from Montreal that they have a new parking payment app.
The old one is called “P$Mobile”—good luck remembering that when you’re trying to pay for parking—so maybe this is a step up.
"Proudly 100% made in Quebec” (if you don’t count the XKCD tower of dependencies… sure… I guess). 🙄
Immediately: email input that isn’t designated as such so the keyboard is wrong.
Second thing: it thinks the password I used is too long at >20 characters. This is n…

Inferring Attributed Grammars from Parser Implementations
Andreas Pointner, Josef Pichler, Herbert Pr\"ahofer
https://arxiv.org/abs/2507.13117 https:/…

Inferring Attributed Grammars from Parser Implementations
Software systems that process structured inputs often lack complete and up-to-date specifications, which specify the input syntax and the semantics of input processing. While grammar mining techniques have focused on recovering syntactic structures, the semantics of input processing remains largely unexplored. In this work, we introduce a novel approach for inferring attributed grammars from parser implementations. Given an input grammar, our technique dynamically analyzes the implementation of…

RotBench: Evaluating Multimodal Large Language Models on Identifying Image Rotation
Tianyi Niu, Jaemin Cho, Elias Stengel-Eskin, Mohit Bansal
https://arxiv.org/abs/2508.13968 ht…

RotBench: Evaluating Multimodal Large Language Models on Identifying Image Rotation
We investigate to what extent Multimodal Large Language Models (MLLMs) can accurately identify the orientation of input images rotated 0°, 90°, 180°, and 270°. This task demands robust visual reasoning capabilities to detect rotational cues and contextualize spatial relationships within images, regardless of their orientation. To evaluate MLLMs on these abilities, we introduce RotBench -- a 350-image manually-filtered benchmark comprising lifestyle, portrait, and landscape images. Despite t…

STPFormer: A State-of-the-Art Pattern-Aware Spatio-Temporal Transformer for Traffic Forecasting
Jiayu Fang, Zhiqi Shao, S T Boris Choy, Junbin Gao
https://arxiv.org/abs/2508.13433

STPFormer: A State-of-the-Art Pattern-Aware Spatio-Temporal Transformer for Traffic Forecasting
Spatio-temporal traffic forecasting is challenging due to complex temporal patterns, dynamic spatial structures, and diverse input formats. Although Transformer-based models offer strong global modeling, they often struggle with rigid temporal encoding and weak space-time fusion. We propose STPFormer, a Spatio-Temporal Pattern-Aware Transformer that achieves state-of-the-art performance via unified and interpretable representation learning. It integrates four modules: Temporal Position Aggregat…

Improving the efficiency of quantum engineering of SCSs by adding two demultiplexed input photons
Mikhail S. Podoshvedov, Sergey A. Podoshvedov
https://arxiv.org/abs/2509.14625 …

Improving the efficiency of quantum engineering of SCSs by adding two demultiplexed input photons
Conditional addition and subtraction of photons is a powerful tool for quantum engineering of continuous variable (CV) states that forms the fundamental building blocks of advanced photonic technologies. For high fidelity information processing, precise control of quantum engineering of CV states is highly demanded. We propose a scheme for measurement induced quantum engineering of even/odd superposition of coherent states (SCSs) of amplitude>2.5 and with fidelity exceeding>0.99. It includes si…

Reactive Semantics for User Interface Description Languages
Basile Pesin (Federation ENAC ISAE-SUPAERO ONERA, Universite de Toulouse, France), Celia Picard (Federation ENAC ISAE-SUPAERO ONERA, Universite de Toulouse, France), Cyril Allignol (Federation ENAC ISAE-SUPAERO ONERA, Universite de Toulouse, France)
https://arxiv.org/abs/2508.1361…

Reactive Semantics for User Interface Description Languages
User Interface Description Languages (UIDLs) are high-level languages that facilitate the development of Human-Machine Interfaces, such as Graphical User Interface (GUI) applications. They usually provide first-class primitives to specify how the program reacts to an external event (user input, network message), and how data flows through the program. Although these domain-specific languages are now widely used to implement safety-critical GUIs, little work has been invested in their formalizat…

Optimizing Scalar Selection in Elliptic Curve Cryptography Using Differential Evolution for Enhanced Security
Takreem Haider
https://arxiv.org/abs/2508.13520 https://

Optimizing Scalar Selection in Elliptic Curve Cryptography Using Differential Evolution for Enhanced Security
Elliptic Curve Cryptography (ECC) is a fundamental component of modern public-key cryptosystems that enable efficient and secure digital signatures, key exchanges, and encryption. Its core operation, scalar multiplication, denoted as $k \cdot P$, where $P$ is a base point and $k$ is a private scalar, relies heavily on the secrecy and unpredictability of $k$. Conventionally, $k$ is selected using user input or pseudorandom number generators. However, in resource-constrained environments with wea…

Democratizing Game Modding with GenAI: A Case Study of StarCharM, a Stardew Valley Character Maker
Hamid Zand Miralvand, Mohammad Ronagh Nikghalb, Mohammad Darandeh, Abidullah Khan, Ian Arawjo, Jinghui Cheng
https://arxiv.org/abs/2507.13951

Democratizing Game Modding with GenAI: A Case Study of StarCharM, a Stardew Valley Character Maker
Game modding offers unique and personalized gaming experiences, but the technical complexity of creating mods often limits participation to skilled users. We envision a future where every player can create personalized mods for their games. To explore this space, we designed StarCharM, a GenAI-based non-player character (NPC) creator for Stardew Valley. Our tool enables players to iteratively create new NPC mods, requiring minimal user input while allowing for fine-grained adjustments through u…

Mitigating the Impact of Location Uncertainty on Radio Map-Based Predictive Rate Selection via Noisy-Input Gaussian Process
Koya Sato
https://arxiv.org/abs/2509.14710 https://…

Mitigating the Impact of Location Uncertainty on Radio Map-Based Predictive Rate Selection via Noisy-Input Gaussian Process
This paper proposes a predictive rate-selection framework based on Gaussian process (GP)-based radio map construction that is robust to location uncertainty. Radio maps are a promising tool for improving communication efficiency in 6G networks. Although they enable the design of location-based maximum transmission rates by exploiting statistical channel information, existing discussions often assume perfect (i.e., noiseless) location information during channel sensing. Since such information mu…

Qwen-Image-Edit: Image Editing with Higher Quality and Efficiency
https://qwenlm.github.io/blog/qwen-image-edit/?utm_source=www.the…

Distributional Adversarial Attacks and Training in Deep Hedging
Guangyi He, Tobias Sutter, Lukas Gonon
https://arxiv.org/abs/2508.14757 https://arxiv.org/p…

Distributional Adversarial Attacks and Training in Deep Hedging
In this paper, we study the robustness of classical deep hedging strategies under distributional shifts by leveraging the concept of adversarial attacks. We first demonstrate that standard deep hedging models are highly vulnerable to small perturbations in the input distribution, resulting in significant performance degradation. Motivated by this, we propose an adversarial training framework tailored to increase the robustness of deep hedging strategies. Our approach extends pointwise adversari…

Boosting Payment Channel Network Liquidity with Topology Optimization and Transaction Selection
Krishnendu Chatterjee, Jan Maty\'a\v{s} K\v{r}i\v{s}\v{t}an, Stefan Schmid, Jakub Svoboda, Michelle Yeo
https://arxiv.org/abs/2508.14524

Boosting Payment Channel Network Liquidity with Topology Optimization and Transaction Selection
Payment channel networks (PCNs) are a promising technology that alleviates blockchain scalability by shifting the transaction load from the blockchain to the PCN. Nevertheless, the network topology has to be carefully designed to maximise the transaction throughput in PCNs. Additionally, users in PCNs also have to make optimal decisions on which transactions to forward and which to reject to prolong the lifetime of their channels. In this work, we consider an input sequence of transactions over…

Well yeh that's why my Epson HX-20's 'charge battery' triggers - the detector input is indeed dropping below the 1.2v threshold with serial running (and microcassette connected albeit idle). So the voltage detector is triggering at the right voltage.
It could just be the lack of real batteries I guess, but hmm, getting there.
#retrocomputing

Fast and Efficient Merge of Sorted Input Lists in Hardware Using List Offset Merge Sorters
Robert B. Kent, Marios S. Pattichis
https://arxiv.org/abs/2507.08658

Fast and Efficient Merge of Sorted Input Lists in Hardware Using List Offset Merge Sorters
A new set of hardware merge sort devices are introduced here, which merge multiple sorted input lists into a single sorted output list in a fast and efficient manner. In each merge sorter, the values from the sorted input lists are arranged in an input 2-D setup array, but with the order of each sorted input list offset from the order of each of the other sorted input lists. In these new devices, called List Offset Merge Sorters (LOMS), a minimal set of column sort stages alternating with row s…

from my link log —
RE#: high performance derivative-based regex matching with intersection, complement, and lookarounds.
https://arxiv.org/abs/2407.20479
saved 2025-04-17

RE#: High Performance Derivative-Based Regex Matching with Intersection, Complement and Lookarounds
We present a tool and theory RE# for regular expression matching that is built on symbolic derivatives, does not use backtracking, and, in addition to the classical operators, also supports complement, intersection and lookarounds. We develop the theory formally and show that the main matching algorithm has input-linear complexity both in theory as well as experimentally. We apply thorough evaluation on popular benchmarks that show that RE# is over 71% faster than the next fastest regex engine …

Quantum Pattern Matching with Wildcards
Masoud Seddighin, Saeed Seddighin
https://arxiv.org/abs/2507.13885 https://arxiv.org/pdf/2507…

Quantum Pattern Matching with Wildcards
Pattern matching is one of the fundamental problems in Computer Science. Both the classic version of the problem as well as the more sophisticated version where wildcards can also appear in the input can be solved in almost linear time $\tilde O(n)$ using the KMP algorithm and Fast Fourier Transform, respectively. In 2000, Ramesh and Vinay~\cite{ramesh2003string} give a quantum algorithm that solves classic pattern matching in sublinear time and asked whether the wildcard problem can also be so…

Minimum and maximum mass-luminosity relations for stripped stars
Gautham N. Sabhahit, Jorick S. Vink, Andreas A. C. Sander, Varsha Ramachandran
https://arxiv.org/abs/2508.14161 …

Minimum and maximum mass-luminosity relations for stripped stars
Envelope stripping, whether through single-star wind mass loss or binary mass transfer, is a key evolutionary pathway for the formation of classical Wolf-Rayet stars and lower-mass stripped helium (He) stars. However, to study the evolution of these objects into black holes, neutron stars, and stripped-envelope supernovae, we need appropriate input models for the core-He burning phase without relying on the uncertain evolution into this evolved phase. Reliable mass-luminosity relations (MLRs) f…

Mamba2 Meets Silence: Robust Vocal Source Separation for Sparse Regions
Euiyeon Kim, Yong-Hoon Choi
https://arxiv.org/abs/2508.14556 https://arxiv.org/pdf/…

Mamba2 Meets Silence: Robust Vocal Source Separation for Sparse Regions
We introduce a new music source separation model tailored for accurate vocal isolation. Unlike Transformer-based approaches, which often fail to capture intermittently occurring vocals, our model leverages Mamba2, a recent state space model, to better capture long-range temporal dependencies. To handle long input sequences efficiently, we combine a band-splitting strategy with a dual-path architecture. Experiments show that our approach outperforms recent state-of-the-art models, achieving a cS…

Treedepth Inapproximability and Exponential ETH Lower Bound
\'Edouard Bonnet, Daniel Neuen, Marek Soko{\l}owski
https://arxiv.org/abs/2507.13818 https:…

Treedepth Inapproximability and Exponential ETH Lower Bound
Treedepth is a central parameter to algorithmic graph theory. The current state-of-the-art in computing and approximating treedepth consists of a $2^{O(k^2)} n$-time exact algorithm and a polynomial-time $O(\text{OPT} \log^{3/2} \text{OPT})$-approximation algorithm, where the former algorithm returns an elimination forest of height $k$ (witnessing that treedepth is at most $k$) for the $n$-vertex input graph $G$, or correctly reports that $G$ has treedepth larger than $k$, and $\text{OPT}$ is t…

Oh no. It's true: The mouse cursor image on Wayland is delayed by one frame. 😭
Proof: https://mort.coffee/home/wayland-input-latency/
Great explaination by @…@…

Preprint: Did I Just Browse A Website Written by LLMs?
Sichang "Steven" He, Ramesh Govindan, Harsha V. Madhyastha
https://arxiv.org/abs/2507.13933

Preprint: Did I Just Browse A Website Written by LLMs?
Increasingly, web content is automatically generated by large language models (LLMs) with little human input. We call this "LLM-dominant" content. Since LLMs plagiarize and hallucinate, LLM-dominant content can be unreliable and unethical. Yet, websites rarely disclose such content, and human readers struggle to distinguish it. Thus, we must develop reliable detectors for LLM-dominant content. However, state-of-the-art LLM detectors are insufficient, because they perform well mainly on clean, p…

A novel geometric predictive algorithm for assessing Compressive Elastic Modulus in MEX additive processes, based on part nonlinearities and layers stiffness,validated with PETG and PLA materials
J. M. Mercado Colmenero, C. Martin Donate
https://arxiv.org/abs/2508.13164

A novel geometric predictive algorithm for assessing Compressive Elastic Modulus in MEX additive processes, based on part nonlinearities and layers stiffness,validated with PETG and PLA materials
The paper presents an innovative methodology based on the use of a new predictive algorithm created by the researchers capable of obtaining the elastic modulus of a plastic material manufactured with MEX and its mechanical behaviour in the elastic zone under compressive loads. The predictive algorithm only needs as input the compressive elastic modulus of the isotropic plastic material filament and the manufacturing parameters of the MEX process. The smart developed algorithm calculates the sti…

Isotropic Remeshing with Inter-Angle Optimization
Hanbing Zheng, Chenlei Lv
https://arxiv.org/abs/2507.13641 https://arxiv.org/pdf/25…

Isotropic Remeshing with Inter-Angle Optimization
As an important metric for mesh quality evaluation, the isotropy property holds significant value for applications such as texture UV-mapping, physical simulation, and discrete geometric analysis. Classical isotropy remeshing methods adjust vertices and edge lengths, which exhibit certain limitations in terms of input data sensitivity, geometric consistency control, and convergence speed. In this paper, we propose an improved isotropy remeshing solution with inter-angle optimization during mesh…

#Multisensory vs. #unisensory learning: how they shape effective connectivity networks subserving unimodal and multimodal integration

Frontiers | Multisensory vs. unisensory learning: how they shape effective connectivity networks subserving unimodal and multimodal integration
The brain synthesizes meaningful interpretations out of the surrounding environment, by integrating sensory input collected by multiple senses. Learning base...

Pass-efficient Randomized Algorithms for Low-rank Approximation of Quaternion Matrices
Salman Ahmadi-Asl, Malihe Nobakht Kooshkghazi, Valentin Leplat
https://arxiv.org/abs/2507.13731

Pass-efficient Randomized Algorithms for Low-rank Approximation of Quaternion Matrices
Randomized algorithms for low-rank approximation of quaternion matrices have gained increasing attention in recent years. However, existing methods overlook pass efficiency, the ability to limit the number of passes over the input matrix-which is critical in modern computing environments dominated by communication costs. We address this gap by proposing a suite of pass-efficient randomized algorithms that let users directly trade pass budget for approximation accuracy. Our contributions include…

OpenLB-UQ: An Uncertainty Quantification Framework for Incompressible Fluid Flow Simulations
Mingliang Zhong, Adrian Kummerl\"ander, Shota Ito, Mathias J. Krause, Martin Frank, Stephan Simonis
https://arxiv.org/abs/2508.13867

OpenLB-UQ: An Uncertainty Quantification Framework for Incompressible Fluid Flow Simulations
Uncertainty quantification (UQ) is crucial in computational fluid dynamics to assess the reliability and robustness of simulations, given the uncertainties in input parameters. OpenLB is an open-source lattice Boltzmann method library designed for efficient and extensible simulations of complex fluid dynamics on high-performance computers. In this work, we leverage the efficiency of OpenLB for large-scale flow sampling with a dedicated and integrated UQ module. To this end, we focus on non-intr…

Effects of Dissipation Physics on High-frequency Quasi-periodic Oscillations in Black Hole X-ray Binaries
Theodore Dezen, Sergio Gomez, Kathryn Anawalt
https://arxiv.org/abs/2508.13508

Effects of Dissipation Physics on High-frequency Quasi-periodic Oscillations in Black Hole X-ray Binaries
We numerically investigate the effects of black hole spin and local dissipation profiles on high-frequency quasi-periodic oscillation (HFQPO) observed in black hole X-ray binaries (BHXB). Our HFQPO power spectra arise from self-consistent calculations that do not rely on ad-hoc assumptions regarding disk geometry. Our models combine radiative transfer and disk vertical structure equations with input motivated by first-principles three-dimensional simulations. We found that HFQPO power spectra m…

If you're on KDE and Wayland, I'm very sorry to hear that, but if in that case you'd still like to have some XScreenSavers you can try this on:
https://github.com/theodric/input_xss
I don't think I'm catching DBus events in the canonical manner, but it's working well en…

Ecocriticism
https://ift.tt/xzYIbe2
updated: Wednesday, August 20, 2025 - 10:36amfull name / name of organization: Marmara University in…
via Input 4 RELCFP https://ift…

Model Interpretability and Rationale Extraction by Input Mask Optimization
Marc Brinner, Sina Zarriess
https://arxiv.org/abs/2508.11388 https://arxiv.org/p…

Model Interpretability and Rationale Extraction by Input Mask Optimization
Concurrent to the rapid progress in the development of neural-network based models in areas like natural language processing and computer vision, the need for creating explanations for the predictions of these black-box models has risen steadily. We propose a new method to generate extractive explanations for predictions made by neural networks, that is based on masking parts of the input which the model does not consider to be indicative of the respective class. The masking is done using gradi…

NoHumansRequired: Autonomous High-Quality Image Editing Triplet Mining
Maksim Kuprashevich, Grigorii Alekseenko, Irina Tolstykh, Georgii Fedorov, Bulat Suleimanov, Vladimir Dokholyan, Aleksandr Gordeev
https://arxiv.org/abs/2507.14119

NoHumansRequired: Autonomous High-Quality Image Editing Triplet Mining
Recent advances in generative modeling enable image editing assistants that follow natural language instructions without additional user input. Their supervised training requires millions of triplets: original image, instruction, edited image. Yet mining pixel-accurate examples is hard. Each edit must affect only prompt-specified regions, preserve stylistic coherence, respect physical plausibility, and retain visual appeal. The lack of robust automated edit-quality metrics hinders reliable auto…

GDNSQ: Gradual Differentiable Noise Scale Quantization for Low-bit Neural Networks
Sergey Salishev, Ian Akhremchik
https://arxiv.org/abs/2508.14004 https://

GDNSQ: Gradual Differentiable Noise Scale Quantization for Low-bit Neural Networks
Quantized neural networks can be viewed as a chain of noisy channels, where rounding in each layer reduces capacity as bit-width shrinks; the floating-point (FP) checkpoint sets the maximum input rate. We track capacity dynamics as the average bit-width decreases and identify resulting quantization bottlenecks by casting fine-tuning as a smooth, constrained optimization problem. Our approach employs a fully differentiable Straight-Through Estimator (STE) with learnable bit-width, noise scale an…

Towards a DSL to Formalize Multimodal Requirements
Marcos Gomez-Vazquez, Jordi Cabot
https://arxiv.org/abs/2508.14631 https://arxiv.org/pdf/2508.14631

Towards a DSL to Formalize Multimodal Requirements
Multimodal systems, which process multiple input types such as text, audio, and images, are becoming increasingly prevalent in software systems, enabled by the huge advancements in Machine Learning. This triggers the need to easily define the requirements linked to these new types of user interactions, potentially involving more than one modality at the same time. This remains an open challenge due to the lack of languages and methods adapted to the diverse nature of multimodal interactions, wi…

Quantum Interference of Distinguishable Photons Based on Spatially-Resolved Measurements
Miguel Angel Gonzalez, Alejandra Alarc\'on, Andres Camilo Quintero, Daniel Sabogal, Luca Maggio, Vincenzo Tamma, Daniel F. Urrego, Alejandra Valencia
https://arxiv.org/abs/2508.14845

Quantum Interference of Distinguishable Photons Based on Spatially-Resolved Measurements
We present experimental results demonstrating the quantum interference of two photons distinguishable in their transverse momenta, each entering the input ports of a balanced beam splitter. This counterintuitive interference effect is made possible through spatially resolved measurements in the near field, i.e., by resolving the conjugate variable in which the photons are distinguishable. Our experimental findings agree with theoretical predictions. We contrast our results with a non-spatially …

Assessing the Value of Visual Input: A Benchmark of Multimodal Large Language Models for Robotic Path Planning
Jacinto Colan, Ana Davila, Yasuhisa Hasegawa
https://arxiv.org/abs/2507.12391

Assessing the Value of Visual Input: A Benchmark of Multimodal Large Language Models for Robotic Path Planning
Large Language Models (LLMs) show potential for enhancing robotic path planning. This paper assesses visual input's utility for multimodal LLMs in such tasks via a comprehensive benchmark. We evaluated 15 multimodal LLMs on generating valid and optimal paths in 2D grid environments, simulating simplified robotic planning, comparing text-only versus text-plus-visual inputs across varying model sizes and grid complexities. Our results indicate moderate success rates on simpler small grids, where …

Joint Motion, Angle, and Range Estimation in Near-Field under Array Calibration Imperfections
Ahmed Hussain, Asmaa Abdallah, Abdulkadir Celik, Ahmed M. Eltawil
https://arxiv.org/abs/2507.13463

Joint Motion, Angle, and Range Estimation in Near-Field under Array Calibration Imperfections
Ultra-massive multiple-input multiple-output MIMO (UM-MIMO) leverages large antenna arrays at high frequencies, transitioning communication paradigm into the radiative near-field (NF), where spherical wavefronts enable full-vector estimation of both target location and velocity. However, location and motion parameters become inherently coupled in this regime, making their joint estimation computationally demanding. To overcome this, we propose a novel approach that projects the received two-dim…

Power-Series Approach to Moment-Matching-Based Model Reduction of MIMO Polynomial Nonlinear Systems
Chao Huang, Alessandro Astolfi
https://arxiv.org/abs/2508.13595 https://

Power-Series Approach to Moment-Matching-Based Model Reduction of MIMO Polynomial Nonlinear Systems
The model reduction problem for high-order multi-input, multi-output (MIMO) polynomial nonlinear systems based on moment matching is addressed. The technique of power-series decomposition is exploited: this decomposes the solution of the nonlinear PDE characterizing the center manifold into the solutions of a series of recursively defined Sylvester equations. This approach allows yielding nonlinear reduced-order models in very much the same way as in the linear case (e.g. analytically). Algorit…

Adaptively Robust LLM Inference Optimization under Prediction Uncertainty
Zixi Chen, Yinyu Ye, Zijie Zhou
https://arxiv.org/abs/2508.14544 https://arxiv.or…

Adaptively Robust LLM Inference Optimization under Prediction Uncertainty
We study the problem of optimizing Large Language Model (LLM) inference scheduling to minimize total latency. LLM inference is an online and multi-task service process and also heavily energy consuming by which a pre-trained LLM processes input requests and generates output tokens sequentially. Therefore, it is vital to improve its scheduling efficiency and reduce the power consumption while a great amount of prompt requests are arriving. A key challenge in LLM inference scheduling is that whil…

Generating the Spanning Trees of Series-Parallel Graphs up to Graph Automorphism
Mithra Karamchedu, Lucas Bang
https://arxiv.org/abs/2508.13480 https://arx…

Generating the Spanning Trees of Series-Parallel Graphs up to Graph Automorphism
In this paper, we investigate the problem of generating the spanning trees of a graph $G$ up to the automorphisms or "symmetries" of $G$. After introducing and surveying this problem for general input graphs, we present algorithms that fully solve the case of series-parallel graphs, under two standard definitions. We first show how to generate the nonequivalent spanning trees of a oriented series-parallel graph $G$ in output-linear time, where both terminals of $G$ have been individually distin…

Innocence in the Crossfire: Roles of Skip Connections in Jailbreaking Visual Language Models
Palash Nandi, Maithili Joshi, Tanmoy Chakraborty
https://arxiv.org/abs/2507.13761

Innocence in the Crossfire: Roles of Skip Connections in Jailbreaking Visual Language Models
Language models are highly sensitive to prompt formulations - small changes in input can drastically alter their output. This raises a critical question: To what extent can prompt sensitivity be exploited to generate inapt content? In this paper, we investigate how discrete components of prompt design influence the generation of inappropriate content in Visual Language Models (VLMs). Specifically, we analyze the impact of three key factors on successful jailbreaks: (a) the inclusion of detailed…

ECHO: Frequency-aware Hierarchical Encoding for Variable-length Signal
Yucong Zhang, Juan Liu, Ming Li
https://arxiv.org/abs/2508.14689 https://arxiv.org/p…

ECHO: Frequency-aware Hierarchical Encoding for Variable-length Signal
Pre-trained foundation models have demonstrated remarkable success in vision and language, yet their potential for general machine signal modeling-covering acoustic, vibration, and other industrial sensor data-remains under-explored. Existing approach using sub-band-based encoders has achieved competitive results but are limited by fixed input lengths, and the absence of explicit frequency positional encoding. In this work, we propose a novel foundation model that integrates an advanced band-sp…

Tinker: Diffusion's Gift to 3D--Multi-View Consistent Editing From Sparse Inputs without Per-Scene Optimization
Canyu Zhao, Xiaoman Li, Tianjian Feng, Zhiyue Zhao, Hao Chen, Chunhua Shen
https://arxiv.org/abs/2508.14811

Tinker: Diffusion's Gift to 3D--Multi-View Consistent Editing From Sparse Inputs without Per-Scene Optimization
We introduce Tinker, a versatile framework for high-fidelity 3D editing that operates in both one-shot and few-shot regimes without any per-scene finetuning. Unlike prior techniques that demand extensive per-scene optimization to ensure multi-view consistency or to produce dozens of consistent edited input views, Tinker delivers robust, multi-view consistent edits from as few as one or two images. This capability stems from repurposing pretrained diffusion models, which unlocks their latent 3D …

Morse-based Modular Homology for Evolving Simplicial Complexes
Anqiao Ouyang
https://arxiv.org/abs/2508.14429 https://arxiv.org/pdf/2508.14429

Morse-based Modular Homology for Evolving Simplicial Complexes
The computation of homology groups for evolving simplicial complexes often requires repeated reconstruction of boundary operators, resulting in prohibitive costs for large-scale or frequently updated data. This work introduces MMHM, a Morse-based Modular Homology Maintenance framework that preserves homological invariants under local complex modifications. An initial discrete Morse reduction produces a critical cell complex chain-homotopy equivalent to the input; subsequent edits trigger locali…

Impact of quadrature measurement on quantum coherence
Luc\'ia \'Alvarez, Alfredo Luis
https://arxiv.org/abs/2507.13735 https://

Impact of quadrature measurement on quantum coherence
We examine the behavior of quadrature coherence under the measurement of the same field quadrature. This is carried out with the help of a beam splitter, that implies the contribution of the field state impinging at the other input port. We examine the case of Gaussian and number states.

A Unifying Approach to Picture Automata
Yvo Ad Meeres, Franti\v{s}ek Mr\'az
https://arxiv.org/abs/2509.12077 https://arxiv.org/pdf/2509.12077

A Unifying Approach to Picture Automata
A directed acyclic graph (DAG) can represent a two-dimensional string or picture. We propose recognizing picture languages using DAG automata by encoding 2D inputs into DAGs. An encoding can be input-agnostic (based on input size only) or input-driven (depending on symbols). Three distinct input-agnostic encodings characterize classes of picture languages accepted by returning finite automata, boustrophedon automata, and online tessellation automata. Encoding a string as a simple directed path …

Bureaucratic Modernism
https://ift.tt/KXMJsec
updated: Monday, August 18, 2025 - 1:51pmfull name / name of organization: Alexandra Irimia…
via Input 4 RELCFP https://if…

Context Steering: A New Paradigm for Compression-based Embeddings by Synthesizing Relevant Information Features
Guillermo Sarasa Dur\'an, Ana Granados Fontecha, Francisco de Borja Rodr\'iguez Ort\'iz
https://arxiv.org/abs/2508.14780

Context Steering: A New Paradigm for Compression-based Embeddings by Synthesizing Relevant Information Features
Compression-based distances (CD) offer a flexible and domain-agnostic means of measuring similarity by identifying implicit information through redundancies between data objects. However, as similarity features are derived from the data, rather than defined as an input, it often proves difficult to align with the task at hand, particularly in complex clustering or classification settings. To address this issue, we introduce "context steering," a novel methodology that actively guides the featur…

Joint AP Selection and Power Allocation for Unicast-Multicast Cell-Free Massive MIMO
Mustafa S. Abbas, Zahra Mobini, Hien Quoc Ngo, Hyundong Shin, Michail Matthaiou
https://arxiv.org/abs/2508.13771

Joint AP Selection and Power Allocation for Unicast-Multicast Cell-Free Massive MIMO
Joint unicast and multicast transmissions are becoming increasingly important in practical wireless systems, such as Internet of Things networks. This paper investigates a cell-free massive multiple-input multiple-output system that simultaneously supports both transmission types, with multicast serving multiple groups. Exact closed-form expressions for the achievable downlink spectral efficiency (SE) of both unicast and multicast users are derived for zero-forcing and maximum ratio precoding d…

MD-OFDM: An Energy-Efficient and Low-PAPR MIMO-OFDM Variant for Resource-Constrained Applications
Rahul Gulia
https://arxiv.org/abs/2507.13623 https://

MD-OFDM: An Energy-Efficient and Low-PAPR MIMO-OFDM Variant for Resource-Constrained Applications
Orthogonal Frequency Division Multiplexing (OFDM) combined with Multiple-Input Multiple-Output (MIMO) techniques forms the backbone of modern wireless communication systems. While offering high spectral efficiency and robustness, conventional MIMO-OFDM, especially with complex equalizers like Minimum Mean Square Error (MMSE), suffers from high Peak-to-Average Power Ratio (PAPR) and significant power consumption due to multiple active Radio Frequency (RF) chains. This paper proposes and mathemat…

Improved girth approximation in weighted undirected graphs
Avi Kadria, Liam Roditty, Aaron Sidford, Virginia Vassilevska Williams, Uri Zwick
https://arxiv.org/abs/2507.13869

Improved girth approximation in weighted undirected graphs
Let $G = (V,E,\ell)$ be a $n$-node $m$-edge weighted undirected graph, where $\ell: E \rightarrow (0,\infty)$ is a real \emph{length} function defined on its edges, and let $g$ denote the girth of $G$, i.e., the length of its shortest cycle. We present an algorithm that, for any input, integer $k \geq 1$, in $O(kn^{1+1/k}\log{n} + m(k+\log{n}))$ expected time finds a cycle of length at most $\frac{4k}{3}g$. This algorithm nearly matches a $O(n^{1+1/k}\log{n})$-time algorithm of \cite{KadriaRSWZ…

Improving Fairness in Graph Neural Networks via Counterfactual Debiasing
Zengyi Wo, Chang Liu, Yumeng Wang, Minglai Shao, Wenjun Wang
https://arxiv.org/abs/2508.14683 https://…

Improving Fairness in Graph Neural Networks via Counterfactual Debiasing
Graph Neural Networks (GNNs) have been successful in modeling graph-structured data. However, similar to other machine learning models, GNNs can exhibit bias in predictions based on attributes like race and gender. Moreover, bias in GNNs can be exacerbated by the graph structure and message-passing mechanisms. Recent cutting-edge methods propose mitigating bias by filtering out sensitive information from input or representations, like edge dropping or feature masking. Yet, we argue that such st…

EfficientUICoder: Efficient MLLM-based UI Code Generation via Input and Output Token Compression
Jingyu Xiao, Zhongyi Zhang, Yuxuan Wan, Yintong Huo, Yang Liu, Michael R. Lyu
https://arxiv.org/abs/2509.12159

EfficientUICoder: Efficient MLLM-based UI Code Generation via Input and Output Token Compression
Multimodal Large Language Models have demonstrated exceptional performance in UI2Code tasks, significantly enhancing website development efficiency. However, these tasks incur substantially higher computational overhead than traditional code generation due to the large number of input image tokens and extensive output code tokens required. Our comprehensive study identifies significant redundancies in both image and code tokens that exacerbate computational complexity and hinder focus on key UI…

Bureaucratic Modernism
https://ift.tt/KXMJsec
updated: Monday, August 18, 2025 - 1:51pmfull name / name of organization: Alexandra Irimia…
via Input 4 RELCFP https://if…

Toward Practical Fluid Antenna Systems: Co-Optimizing Hardware and Software for Port Selection and Beamforming
Sai Xu, Kai-Kit Wong, Yanan Du, Hanjiang Hong, Chan-Byoung Chae, Baiyang Liu, Kin-Fai Tong
https://arxiv.org/abs/2507.14035

Toward Practical Fluid Antenna Systems: Co-Optimizing Hardware and Software for Port Selection and Beamforming
This paper proposes a hardware-software co-design approach to efficiently optimize beamforming and port selection in fluid antenna systems (FASs). To begin with, a fluid-antenna (FA)-enabled downlink multi-cell multiple-input multiple-output (MIMO) network is modeled, and a weighted sum-rate (WSR) maximization problem is formulated. Second, a method that integrates graph neural networks (GNNs) with random port selection (RPS) is proposed to jointly optimize beamforming and port selection, while…

On the Gaussian Limit of the Output of IIR Filters
Yashaswini Murthy, Bassam Bamieh, R. Srikant
https://arxiv.org/abs/2508.12705 https://arxiv.org/pdf/2508…

On the Gaussian Limit of the Output of IIR Filters
We study the asymptotic distribution of the output of a stable Linear Time-Invariant (LTI) system driven by a non-Gaussian stochastic input. Motivated by longstanding heuristics in the stochastic describing function method, we rigorously characterize when the output process becomes approximately Gaussian, even when the input is not. Using the Wasserstein-1 distance as a quantitative measure of non-Gaussianity, we derive upper bounds on the distance between the appropriately scaled output and a …

100 Years of Wonder
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updated: Wednesday, August 20, 2025 - 10:45amfull name / name of organization: Science Fiction…
via Input 4 RELCFP https://if…

Design of a Gm-C Dynamic Amplifier with High Linearity and High Temperature and Power Supply Voltage Stability
Jinkun Yang, Pengbin Xu
https://arxiv.org/abs/2508.14637 https://

Design of a Gm-C Dynamic Amplifier with High Linearity and High Temperature and Power Supply Voltage Stability
This paper presents a Gm-C dynamic amplifier with high linearity and high temperature and power supply voltage stability. The main part of the amplifier employs two asymmetric differential pairs to enhance transconductance linearity. The amplifier maintains a nearly constant gain within a differential input range of -40 mV to 40 mV, and achieves a total harmonic distortion (THD) of 70.5 dB. The bias part of the amplifier adopts a constant-gm bias circuit, which improves the temperature and supp…

Replaced article(s) found for eess.SY. https://arxiv.org/list/eess.SY/new
[1/1]:
- Input-Output Extension of Underactuated Nonlinear Systems
Mirko Mizzoni, Amr Afifi, Antonio Franchi

Postcolonialism
https://ift.tt/mo8seZb
updated: Wednesday, August 20, 2025 - 10:08amfull name / name of organization: Marmara University in…
via Input 4 RELCFP https://…

Optimal Unpredictable Control for Linear Systems
Chendi Qu, Jianping He, Jialun Li, Xiaoming Duan
https://arxiv.org/abs/2508.14686 https://arxiv.org/pdf/25…

Optimal Unpredictable Control for Linear Systems
In this paper, we investigate how to achieve the unpredictability against malicious inferences for linear systems. The key idea is to add stochastic control inputs, named as unpredictable control, to make the outputs irregular. The future outputs thus become unpredictable and the performance of inferences is degraded. The major challenges lie in: i) how to formulate optimization problems to obtain an optimal distribution of stochastic input, under unknown prediction accuracy of the adversary; a…

Narrativising Infrastructure
https://ift.tt/1bgR7mi
updated: Tuesday, August 19, 2025 - 2:50pmfull name / name of organization: The Global South…
via Input 4 RELCFP https://

Women’s Studies Non-Thematic
https://ift.tt/8Ppf1RL
updated: Wednesday, August 20, 2025 - 10:38amfull name / name of organization: Jamia Millia…
via Input 4 RELCFP https://

Women’s Studies Non-Thematic
https://ift.tt/8Ppf1RL
updated: Wednesday, August 20, 2025 - 10:38amfull name / name of organization: Jamia Millia…
via Input 4 RELCFP https://

Call for Papers, ReFocus: Mira Nair
https://ift.tt/wbDCEPI
updated: Wednesday, August 6, 2025 - 9:01amfull name / name of organization: The University of…
via Input 4 RELCFP https://

India, Poverty, and Western Eyes
https://ift.tt/nLKNrsg
updated: Wednesday, August 20, 2025 - 10:04amfull name / name of organization: American Comparative…
via Input 4 RELCFP https://

India, Poverty, and Western Eyes
https://ift.tt/nLKNrsg
updated: Wednesday, August 20, 2025 - 10:04amfull name / name of organization: American Comparative…
via Input 4 RELCFP https://

Call for Papers: "Religion"
https://ift.tt/xZzU1lJ
University of Alaska - Fairbanks - Alaska & Polar Regions Area Studies Bibliographer & Curator of…
via Input 4 RELCFP htt…

Radical Imagination, Radical Equality
https://ift.tt/VRF7gWa
updated: Wednesday, August 20, 2025 - 10:37amfull name / name of organization: Vern Walkercontact…
via Input 4 RELCFP https://

ReFocus: The Films of Gerard Damiano
https://ift.tt/tmdpj1w
updated: Monday, August 11, 2025 - 7:48amfull name / name of organization: Calum Waddell, University…
via Input 4 RELCFP https://

Religions of Revolution Symposium
https://ift.tt/1GcdMN3
University of Alaska - Fairbanks - Alaska & Polar Regions Area Studies Bibliographer & Curator of…
via Input 4 RELCFP https:/…

Talking Records: Pollution in the Archive
https://ift.tt/PVo1RNH
updated: Friday, August 15, 2025 - 12:53pmfull name / name of organization: The National Archives,…
via Input 4 RELCFP https:…

Re - Defining Work, Issue VI, Perspectives - JDMC
https://ift.tt/zVmnRCI
updated: Friday, August 15, 2025 - 12:51pmfull name / name of organization: Janki Devi Memorial…
via Input 4 RELCFP h…

Blue, Green, and In-between: Critical Ecologies in South Asia
https://ift.tt/etmN2XI
updated: Friday, August 15, 2025 - 12:44pmfull name / name of organization: Nisarga…
via Input 4 RELCFP h…

Between Philosophy and Literature Panel at NeMLA 2026
https://ift.tt/AqSBQ5z
updated: Wednesday, August 20, 2025 - 10:37amfull name / name of organization: Joe Larioscontact…
via Input 4 RELCFP

Medieval Foremothers Society Honors Sharon Kinoshita
https://ift.tt/zioWXaI
updated: Friday, August 15, 2025 - 12:49pmfull name / name of organization: Society for Society for…
via Input 4 RELCFP

“Hush! Practicing Silence in Literature and Culture”
https://ift.tt/WzQRlUF
updated: Tuesday, August 5, 2025 - 12:41pmfull name / name of organization: Freiburg University…
via Input 4 RELCFP

ACLA 2026: Uses and Abuses of History in Literary Narratives
https://ift.tt/kVzvDfr
updated: Friday, August 15, 2025 - 12:54pmfull name / name of organization: ACLA 2026contact…
via Input 4 RELCFP

ACLA 2026: Uses and Abuses of History in Literary Narratives
https://ift.tt/kVzvDfr
updated: Friday, August 15, 2025 - 12:54pmfull name / name of organization: ACLA 2026contact…
via Input 4 RELCFP

Pasados Special Issue: Against the Past/Contra Pasados
https://ift.tt/vtWVey7
updated: Wednesday, August 20, 2025 - 10:51amfull name / name of organization: Pasados: Recovering…
via Input 4 RELCFP

Pasados Special Issue: Against the Past/Contra Pasados
https://ift.tt/vtWVey7
updated: Wednesday, August 20, 2025 - 10:51amfull name / name of organization: Pasados: Recovering…
via Input 4 RELCFP

Trace and Trajectory in East Asian Cultures Conference
https://ift.tt/ZXyzNgH
updated: Tuesday, August 5, 2025 - 2:35pmfull name / name of organization: The 3rd Graduate Student…
via Input 4 RELCFP

Call for Abstracts: Edited Volume on "Datafied Decision-Making"
https://ift.tt/dRL7Kxl
updated: Friday, August 15, 2025 - 12:45pmfull name / name of organization: Schaufler Lab@TU…
via Input 4 RELCFP

Robert Creeley at 100, A Celebration of His Life and Poetry
https://ift.tt/FmR1jMO
updated: Wednesday, August 20, 2025 - 10:51amfull name / name of organization: The Charles Olson…
via Input 4 RELCFP

Literature, Objects, and Society in 18th-century Asia (panel)
https://ift.tt/GWaoME7
updated: Friday, August 15, 2025 - 12:56pmfull name / name of organization: American Society for…
via Input 4 RELCFP

LECTURE> Prof. Mei Lin 梅林 - Dunhuang Cave 96
https://ift.tt/yM2OwsF
University of Alaska - Fairbanks - Alaska & Polar Regions Area Studies Bibliographer & Curator of…
via Input 4 RELCFP

RSA: Reimagining Disability through “Disability Intimacy”
https://ift.tt/Okpx58X
updated: Tuesday, August 5, 2025 - 12:42pmfull name / name of organization: Renaissance Society of…
via Input 4 RELCFP

Call for Guest Editors: Summer 2026 Composition Studies Special Issue
https://ift.tt/9OLdztF
updated: Wednesday, August 20, 2025 - 10:52amfull name / name of organization: Composition…
via Input 4 RELCFP

Translation Networks in the Decolonising World, 1950s–1970s
https://ift.tt/dXhKHSk
updated: Saturday, August 16, 2025 - 10:15amfull name / name of organization: Georgia Nasseh, King's…
via Input 4 RELCFP

CFP: Dime Novels and Juvenile Series Books Area, PCA Conference 2026
https://ift.tt/ITp69Jw
updated: Wednesday, August 20, 2025 - 10:02amfull name / name of organization: Popluar Culture…
via Input 4 RELCFP

Reproducing Motherhood: Between the Poles of Natality and Maternity
https://ift.tt/XuQmyZr
updated: Wednesday, August 20, 2025 - 10:03amfull name / name of organization: American Comparative…
via Input 4 RELCFP