Search: “research”

Type-Balanced Federated Learning for Visual Analog Meter Reading

arXiv:2609.31998v1 Announce Type: new Abstract: Analog dial meters are widely deployed in industrial applications and utility sites, where environments and meter types vary and inspection data may be

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Uncertainty-Aware Selection of Online Algorithms with Simulator Ensembles

DGX agent

arXiv:2609.32170v1 Announce Type: new Abstract: The performance of online reinforcement learning depends critically on design choices, especially those that affect exploration. These choices are often

researcharxiv-cs-lg

29 Sept 2026

Understanding Quantization of Optimizer States in LLM Pre-training: Dynamics of State Staleness and Effectiveness of State Resets

arXiv:2603.16731v2 Announce Type: replace Abstract: Quantizing optimizer states is becoming an important ingredient of memory-efficient large-scale pre-training, but the resulting optimizer dynamics r

Unified Visual-Tactile-Action Modeling from Human Demonstrations for Dexterous Manipulation

arXiv:2609.34182v1 Announce Type: new Abstract: Dexterous manipulation requires tactile feedback.However, robot tactile demonstrations are difficult to scale,because dexterous-hand teleoperation provi

researcharxiv-cs-ro

Unifying Distributional Training for One-Step Visual Generation

arXiv:2609.35763v1 Announce Type: new Abstract: Distributional training provides collective supervision for one-step visual generation by matching real and generated features in frozen representation

Universal Approximation of Measure-to-Measure Operators by Pushforwards

arXiv:2609.35483v1 Announce Type: new Abstract: Many learning tasks map an input distribution to an output distribution. A natural way to model such an operator is to transform each input sample using

Universality and Generalization of Causal Transformers Across Context Lengths

arXiv:2609.35055v1 Announce Type: new Abstract: Long contexts are central to modern transformer systems, but most expressivity results choose a different network for each fixed sequence length. We stu

Unlocking Geodesic Gromov-Wasserstein Distances for 3D Modeling

arXiv:2609.32824v1 Announce Type: new Abstract: extit{Gromov-Wasserstein Distances} (GWDs) provide quantitative ways of comparing probabilistic distributions defined on different metric spaces by appl

Unveiling Implicit Advantage Symmetry: Why GRPO Struggles with Exploration and Difficulty Adaptation

arXiv:2602.05548v4 Announce Type: replace Abstract: Reinforcement Learning with Verifiable Rewards (RLVR), particularly GRPO, has become the standard for eliciting LLM reasoning. However, its efficien

Using Machine Learning to Investigate Predictors of Fasting Blood Glucose: Insights into Circadian Timing and Age Interactions

arXiv:2609.32386v1 Announce Type: new Abstract: Impaired glucose regulation is a major contributor to metabolic dysfunction and type 2 diabetes. This study developed an interpretable machine-learning

VC Dimension and Expressivity of Real-Valued Transformers

arXiv:2609.31999v1 Announce Type: new Abstract: Whereas previous results on abilities and limitations of transformers have restricted the definition of transformers in various ways, here we study soft

Verifiable Visual Rewards Transfer from Synthetic Scenes to Natural Prompts

arXiv:2609.35641v1 Announce Type: cross Abstract: Precise instruction following in image generation, such as satisfying object counts and spatial relations, remains an open challenge at least in part

Video, Ergo Genero: Unifying Video Tasks via Spatiotemporal Analogy

arXiv:2609.33935v1 Announce Type: new Abstract: Adapting video models to new tasks typically requires dedicated data curation and fine-tuning. While visual analogy provides a training-free alternative

Video-to-Music Generation for Gameplay Videos

arXiv:2609.31810v1 Announce Type: cross Abstract: Video-to-music models have advanced considerably in the last few years, particularly in film and music video applications. In this paper, we investiga

VisionLogic: Discovering and Grounding Decision-Relevant Visual Concepts

arXiv:2503.10547v3 Announce Type: replace Abstract: Concept-based explanations help users understand vision models through recognizable visual patterns. However, existing methods often rely on correla

VL-AcneSeg: A Vision-Language Framework for Region-Aware Acne Lesion Segmentation

arXiv:2609.34472v1 Announce Type: new Abstract: Acne assessment is crucial for clinical decision-making, yet traditional grading and counting are subjective and fail to account for lesion size. While

Wasserstein Convergence of ODE-Based Samplers in Decentralized Diffusion Model via Velocity Field Decomposition

arXiv:2606.15835v2 Announce Type: replace Abstract: Diffusion models have achieved impressive empirical success in generative tasks, and their convergence theory is now relatively well understood. Mot

What Must a World Model Distinguish for Planning?

arXiv:2609.33030v1 Announce Type: new Abstract: World models simulate the consequences of action candidates, but good planning need not preserve every physical distinction required for accurate predic

What Next-Event Accuracy Cannot See: Closed-Loop Evaluation of Emergency Department Trajectory Simulators

arXiv:2609.31635v1 Announce Type: new Abstract: Clinical trajectory models are usually evaluated by next-event accuracy on observed histories. Simulation is different: models must condition on their o

What Survives the Codec Shift: Pooled No-Vocals Residuals for Speech Deepfake Detection

arXiv:2609.33375v1 Announce Type: cross Abstract: The transition from vocoder-based to neural-codec speech synthesis makes generalization more difficult for speech deepfake detectors, particularly tho

What Would Falsify It? A Variable Specific Evidence Standard for Mechanistic Claims About Self Explanation

arXiv:2609.32670v1 Announce Type: cross Abstract: When a language model explains an answer it has already given, does it reuse the computation that produced the answer or reconstruct a story from the

When Is an SAE Feature Interpretable? A Validation Ladder for EEG Foundation Models

arXiv:2609.34091v1 Announce Type: new Abstract: Sparse autoencoders (SAEs) decompose dense model activations into discrete latents, making individual features easy to interpret--and easy to misinterpr

When Less Data Favors Smaller Teachers: Rethinking Teacher Capacity and Data Selection for Knowledge Distillation

arXiv:2609.34489v1 Announce Type: new Abstract: Data pruning reduces the training cost of knowledge distillation (KD). However, the preferred teacher capacity changes with the data budget: smaller tea

When local gains fail to transfer: Frozen Earth-observation embeddings across wildfires

arXiv:2609.34602v1 Announce Type: new Abstract: Frozen Earth-observation embeddings are judged almost entirely by spatially blocked cross-validation inside one study region. We show that this number d

When Retrieval Hurts: Measuring and Explaining Retrieval-Induced Hallucination in Chest X-ray Report Generation

arXiv:2609.31733v1 Announce Type: new Abstract: Retrieval-augmented generation is an attractive way to improve chest X-ray reporting, because reports from similar prior studies supply clinical context

When Should a Satellite Estimate Be Changed? Stress-Testing Neural Corrections for Evapotranspiration

arXiv:2609.35314v1 Announce Type: new Abstract: Neural residuals can improve satellite evapotranspiration (ET) estimates, but selectors must predict when a correction helps and reject unsupported inpu

When Text Matters: Design Principles for Visual Token Pruning in Vision-Language Model

arXiv:2609.34861v1 Announce Type: new Abstract: Visual token pruning has been widely studied as a practical approach to reducing the computational cost of large vision-language models. However, it str

When to Evict, Not What to Keep: Draft-Guided Eviction for Training-Free KV-Cache Compression

arXiv:2609.33334v1 Announce Type: new Abstract: Training-free KV-cache compression methods such as SnapKV, H2O, and PyramidKV evict tokens at the end of prefill, aiming to preserve the attention mass

Where Does the Watermark Hide? Push-Pull Disentanglement for Invisible Watermark Removal

arXiv:2609.31722v1 Announce Type: new Abstract: Fixed image distortions do not cover an attacker that learns from paired clean and watermarked images. We study this paired-training threat with single-

Which Self-Improvements Should We Trust? Reliable Self-Improvement When Agents Reuse Their Benchmarks

arXiv:2609.33180v1 Announce Type: cross Abstract: As recursive self-improvement (RSI) rapidly advances, reliable evaluation becomes critical for guiding adaptive search. RSI typically relies on finite

Which the Eye Fears: Writing with Read-Blindness Explains Massive Activations in Transformers

arXiv:2609.35630v1 Announce Type: cross Abstract: Massive activation features (MAs) in Transformers are extreme-value residual-stream features that persist across layers despite the model's ability to

Who Gets a Token, and What Does It Carry? Unequal Name Support and Concept Access in Large Language Models

arXiv:2609.34065v1 Announce Type: cross Abstract: Names are personal identifiers, but they also carry social meaning and are widely used to evaluate how language models treat different people. Such ev

Who Is Left of Whom? Tracing Spatial Evidence and Role Binding in Relative-Position Reasoning

arXiv:2609.35486v1 Announce Type: cross Abstract: High instance-level accuracy can mask inconsistencies in spatial reasoning when objects exchange positions or their roles are reversed in the query. T

Why and When Deep is Better than Shallow: Implementation-Agnostic State-Transition Model of Deep Learning

arXiv:2505.15064v5 Announce Type: replace Abstract: We ask when adding hidden layers improves generalization, in a model that keeps the layers fixed and varies only their number. A hidden layer is a s

WM-VLM: Probing Internal World Models for Interleaved Visual-Textual Reasoning

arXiv:2609.34826v1 Announce Type: new Abstract: Humans often solve spatial problems by mentally simulating visual transformations. In contrast, conventional vision-language models (VLMs) reason primar

Word Similarity Datasets for Indian Languages: Annotation and Baseline Systems

arXiv:2609.34138v1 Announce Type: cross Abstract: With the advent of word representations, word similarity tasks are becoming increasing popular as an evaluation metric for the quality of the represen

World SLAM Model: Joint World Modeling for SLAM and Navigation

arXiv:2609.32626v1 Announce Type: cross Abstract: We introduce World SLAM Model (WSM), a unified framework that brings the SLAM paradigm directly into downstream navigation. Rather than treating SLAM

WorldPlay2: Extending Real-Time Interactive World Models in Control and Horizon

arXiv:2609.35560v1 Announce Type: new Abstract: Interactive world models require responding in real time to versatile controls and maintaining long-horizon consistency. However, modeling heterogeneous

Write Back the Delta: Revisiting the Same Tokens with Fresh Representations

arXiv:2609.32457v1 Announce Type: new Abstract: Transformers process information strictly forward through depth, preventing deeper computation from revisiting and refining earlier representations. To

A Benchmarking Framework for Context-aware XR Interfaces

arXiv:2609.30466v1 Announce Type: cross Abstract: Everyday Extended Reality (XR) systems aim to provide context-aware access to the right functionalities at the right time and place, with minimal manu

researcharxiv-cs-ai

A Comprehensive Study of Content Representations for Speech Synthesis

arXiv:2609.30975v1 Announce Type: cross Abstract: Speech content representations are central to voice conversion, speech-to-speech translation, and multimodal language models, yet they are rarely comp

A Flatness-Generalization Relation in the Teacher-Student Tree-Committee Machine

arXiv:2609.31101v1 Announce Type: cross Abstract: The flatness of the loss landscape at a minimizer is a widely used heuristic for reasoning about neural-network generalization, yet evidence for this

A Flow Matching Framework for Neural Representational Dissimilarity

arXiv:2609.31544v1 Announce Type: new Abstract: Neural representational dissimilarity quantifies differences between neural response distributions, and is essential for comparing neural codes across s

researcharxiv-cs-ai

A Long-Legged, Direct-Drive Monopedal Robot Achieves Exceptional Jump Height

arXiv:2609.30530v1 Announce Type: new Abstract: We demonstrate a jumping robot that reaches high (7.6 m) and fast (190 ms stance time) jumps from a single long leg driven by a direct-drive transmissio

researcharxiv-cs-ro

A New Non-archimedean Metric on Persistent Homology

arXiv:2012.02655v4 Announce Type: cross Abstract: In this article, we define a new non-archimedean metric structure, called cophenetic metric, on persistent homology classes of all degrees. We then sh

A Second Torque Port for Series Elastic Actuators: Parallel-Integrated Design and Time-Scale Torque Allocation

arXiv:2609.30873v1 Announce Type: new Abstract: A series elastic actuator has a single torque port and pays for it twice: the geared motor must swing its own reflected inertia through the spring, so t

researcharxiv-cs-ro

A Sharp Norm Inequality and Buzano's Inequality via Determinants

arXiv:2604.01525v2 Announce Type: replace-cross Abstract: We give a short linear-algebraic proof of the inequality $ |x|_1,|x|_infty le frac{1+sqrt{n}}{2},|x|_2^2, valid for every xinR^n. This inequal

A Synthetic Ground-Truth Framework for the Evaluation of Explainable AI Methods

arXiv:2609.30397v1 Announce Type: new Abstract: Evaluating explainable Artificial Intelligence (XAI) methods is a challenging task due to the lack of reliable evaluation procedures and, in particular,

researcharxiv-cs-ai