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The Shape of Speech: A Geometric Measure of Coarticulation for Speech-Driven 3D Facial Animation

arXiv:2610.03436v1 Announce Type: cross Abstract: Speech-driven 3D facial animation can reproduce recognizable mouth poses. However, it can simplify the motion between them, and that motion carries co

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Research

The Surprising Effectiveness of Shared Memory in Looped Transformers

DGX agent

arXiv:2610.02383v1 Announce Type: cross Abstract: Looped Transformers apply the same layers several times per token, adding compute to improve quality without more parameters. Each recursion, however,

researcharxiv-cs-ai

5 Oct 2026

Theoretical Lower Bounds on the Robustness of Deep ReLU Networks

arXiv:2602.18674v2 Announce Type: replace Abstract: We present a theoretical study of the robustness of parameterized neural networks to random input perturbations. Specifically, we analyze local robu

THPL: A Vision-to-Language Decision Support Framework for Rainbow Trout Feeding Management in RAS

arXiv:2610.02378v1 Announce Type: new Abstract: In Recirculating Aquaculture Systems (RAS), precision feeding is critical for minimizing costs and improving fish welfare. However, existing methods lac

safetyarxiv-cs-ai

Threat-Preserving Representation Sensitivity in Agent-Security Benchmarks

arXiv:2610.03585v1 Announce Type: cross Abstract: Security benchmarks for LLM-based agents often report the attack success rate (ASR) as a measure of model robustness and use these scores to compare d

Threshold-Aware Conformal Routing

arXiv:2610.02487v1 Announce Type: new Abstract: High-fidelity simulations are essential to scientific and engineering design, but can be expensive to run repeatedly. Learned surrogates offer a faster

Applications

Time Series Forecasting Benchmarks Need Scenario-Grounded Stress Testing

arXiv:2610.02608v1 Announce Type: new Abstract: Time series forecasting (TSF) increasingly drives decisions in transportation, energy, finance, healthcare, and infrastructure, yet current evaluation r

applicationsarxiv-cs-ai

To Explore The Strange New World Beyond Data Distribution: System Behavior, Causality Tax, and Non-causal Base Model

arXiv:2610.02839v1 Announce Type: cross Abstract: We show that the causality of language models (LMs) may not be necessary nor optimal. This is the case when system behavior (denoted as S) is incorpor

researcharxiv-cs-cl

To Jev or Not? Evaluating the Accuracy and Efficiency of Structured Decision Models for Hate-Speech Moderation

arXiv:2610.03324v1 Announce Type: new Abstract: The scale of online content makes hate-speech moderation challenging, while Large Language Models (LLMs) enable harmful material to be produced and adap

researcharxiv-cs-cl

Tutorials

Toward Controlling Biology with Language:Offline Learning of Prompt-Conditioned Interventions for Cells, Organoids, and Biobots

arXiv:2610.02247v1 Announce Type: cross Abstract: Artificial intelligence increasingly serves as a natural-language interface to complex technical systems, letting people accomplish sophisticated task

tutorialsarxiv-cs-ai

Tutorials

Toward Omni Multimodal Graph Foundation Model: A Topology-Driven Binding Approach

arXiv:2610.02881v1 Announce Type: new Abstract: Multimodal graph foundation models (MGFMs) seek to learn generalizable representations from large-scale graphs with heterogeneous node modalities. Howev

tutorialsarxiv-cs-lg

Agents

Toward SLM-based agentic task-tool intent matching

arXiv:2610.03213v1 Announce Type: new Abstract: Tool-equipped AI agents use tool calls to access data and act on external systems. Horizontal growth of agentic systems increases the number of these in

agentsarxiv-cs-ai

Towards Unified Music Emotion Recognition across Dimensional and Categorical Models

arXiv:2502.03979v3 Announce Type: replace-cross Abstract: One of the most significant challenges in Music Emotion Recognition (MER) comes from the fact that emotion labels can be heterogeneous across

TPBench: A Turning-Point Benchmark for Dialogue Compression

arXiv:2610.02736v1 Announce Type: cross Abstract: A compressor can keep the facts of a dialogue and still drop the turn that changed them. A user corrects a price, reverses a choice, or adds a constra

TRAC: Trajectory-aware Reuse and Adaptive Correction for Efficient Autoregressive Video Generation

arXiv:2610.02779v1 Announce Type: new Abstract: In this paper, we present trajectory-aware reuse and adaptive correction (TRAC), a training-free framework for efficient autoregressive (AR) video gener

researcharxiv-cs-cv

TRACE: A Reproducible Benchmark for Electricity Price Forecasting with Official Operational Text

model-releasesarxiv-cs-lg

arXiv:2610.02256v1 Announce Type: new Abstract: Electricity price forecasting (EPF) supports scheduling, bidding, and risk management in electricity markets, yet existing benchmarks focus mainly on nu

Trading Strategy Optimization via Textual Gradient

arXiv:2610.03128v1 Announce Type: new Abstract: Quantitative trading strategy design aims to discover trading programs from historical data that remain effective in future markets, which can be viewed

Trained Agentic Context Management

arXiv:2610.02404v1 Announce Type: cross Abstract: We study long context language models. Instead of training long context natively, or designing a long context harness, we train a model over the simpl

Training-Loss Guarantees for Muon with Finite-Step Newton--Schulz Orthogonalization

arXiv:2610.03306v1 Announce Type: cross Abstract: Existing convergence analyses of Muon either assume exact orthogonalization or analyze classical Newton--Schulz polynomials, and guarantee only statio

Transcriptome-informed multi-modal AI for predicting neoadjuvant therapy response from breast cancer biopsies

arXiv:2610.03693v1 Announce Type: new Abstract: Scarcity of labeled data limits development of deep learning biomarkers in oncology. We develop a two-stage AI model predicting pathological complete re

Traversing the Satisfaction-Diversity Frontier in Text-to-Image Diffusion

arXiv:2610.02372v1 Announce Type: new Abstract: Text-to-image generation enables users to explore several images generated from the same prompt. For these generated images to be useful, each one must

Tropical Reinforcement Learning

arXiv:2610.02478v1 Announce Type: new Abstract: Reinforcement learning for large language models typically maximizes expected return, adding up the probabilities of all successful trajectories. Howeve

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TSGuard: A Real-Time Framework for Detecting and Imputing Missing Data in Streaming Time Series

arXiv:2610.03147v1 Announce Type: cross Abstract: Streaming sensor applications routinely suffer from delayed or missing observations caused by faults, communication losses, or environmental interfere

Turnover-Orthogonal Credit Assignment for Open-Team Multi-Agent Reinforcement Learning

model-releasesarxiv-cs-lg

arXiv:2610.02847v1 Announce Type: cross Abstract: Open-team multi-agent reinforcement learning studies cooperative systems in which agents may join, leave, or be replaced during an episode. In such se

ULTRADISCOVERY: Abductive Exploration in an Interconnected, Epistemically Open Universe

arXiv:2610.03092v1 Announce Type: cross Abstract: Scientific discovery often begins when scattered clues call for a new way of describing the world. Such abductive exploration can require constructing

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Uncertainty as a Proxy for Semantic Correctness in Diffusion-Based Medical Image Synthesis

arXiv:2610.03224v1 Announce Type: cross Abstract: Diffusion models can synthesise contrast-enhanced CT (CECT) from non-contrast CT (NCCT), avoiding contrast administration and its environmental and pa

Applications

Uncertainty Quantification for Flow-Based Generalist Robot Policies

arXiv:2606.18043v2 Announce Type: replace-cross Abstract: Generalist robot policies, such as vision-language-action models (VLAs) and world-action models (WAMs), combine powerful pretrained backbones

applicationsarxiv-cs-lg

Uncovering EEG Patterns Consistently Associated with Cybersickness Discomfort Using Deep Learning Interpretability Maps

arXiv:2512.20620v3 Announce Type: replace-cross Abstract: Uncomfortable sensations similar to motion sickness, called cybersickness, can develop when using Virtual Reality (VR) head-mounted displays.

Understanding Affective Adaptation in Multimodal Foundation Models: Emergent Functional Specialization

model-releasesarxiv-cs-cv

arXiv:2601.15906v2 Announce Type: replace Abstract: Despite rapid progress in multimodal affective foundation models, how affective capabilities emerge within their internal architectures remains poor

Understanding Clinical Cognitive Dialogues Using Large Language Models

arXiv:2609.34125v2 Announce Type: replace Abstract: In-person cognitive assessment is both a test and an interaction. Clinicians explain tasks, repair misunderstandings, and adapt to patient responses

Understanding Enrichment in Reinforcement Learning

arXiv:2610.02846v1 Announce Type: new Abstract: When rewards are sparse, reinforcement learning with verifiable rewards (RLVR) often uses hints or intermediate guidance to generate more successful rol

safetyarxiv-cs-lg

Understanding Trajectory Heterogeneity in Federated World Model Learning

arXiv:2610.02957v1 Announce Type: cross Abstract: World models learn state evolution from trajectories, making access to temporal context a central training requirement. Federated learning can use dis

UniDynamics: Event-RGB Fusion for Unified Future 4D Dynamic Scene Generation

arXiv:2610.03473v1 Announce Type: new Abstract: We propose UniDynamics, a diffusion-based framework for future 4D dynamic scenes (RGB, depth, and optical flow) generation from a single event-RGB pair,

researcharxiv-cs-cv

UniIntervene++: An Adaptive Intervention Agent for Efficient Real-World Reinforcement Learning

arXiv:2610.03620v1 Announce Type: new Abstract: Online reinforcement learning (RL) enables robot policies to improve through physical interaction, but the assistance they require changes as their comp

safetyarxiv-cs-lg

Unmasking Propaganda: A Comparative Analysis of Masked and Causal Language Models

arXiv:2610.03077v1 Announce Type: new Abstract: Propaganda detection is an essential task in natural language processing (NLP), particularly in the context of manipulative political communications. Ho

Tutorials

Validated Data Onboarding for AI Demand Forecasting on U.S. Building Meter Data: Design, Controlled Evaluation, and a Corrected Negative Result

arXiv:2610.02397v1 Announce Type: new Abstract: Electric utilities and grid operators increasingly rely on machine-learning models to forecast next-day demand, and those models learn from meter data t

tutorialsarxiv-cs-lg

Variance-reduced accelerated methods for decentralized stochastic double-regularized nonconvex strongly-concave minimax problems

arXiv:2307.07113v2 Announce Type: replace-cross Abstract: In this paper, we consider the decentralized, stochastic nonconvex strongly-concave (NCSC) minimax problem with nonsmooth regularization terms

VDOT++: Unified Few-Step Video Generation via Unbalanced Optimal Transport Distillation

model-releasesarxiv-cs-cv

arXiv:2610.03221v1 Announce Type: new Abstract: Video creation spans text-to-video (T2V), image-to-video (I2V), and condition-based generation, yet video diffusion models remain costly because they re

Verifiable, Articulable, and Tacit Components of Preference

arXiv:2610.03025v1 Announce Type: new Abstract: What makes a short story gripping; a news article newsworthy; or a math proof elegant? These constructs resist articulation or verification; their meani

Agents

VERSE: Verified Self-Evolving Optimizer for Agent Harnesses

arXiv:2610.02616v1 Announce Type: new Abstract: Harness evolution improves an LLM agent's prompts, tools, and workflow, while the optimizer's own tools and procedures often remain fixed. We study whet

agentsarxiv-cs-ai

VIDiff: Translating Videos via Multi-Modal Instructions with Diffusion Models

arXiv:2311.18837v2 Announce Type: replace-cross Abstract: Diffusion models have achieved significant success in image and video generation. This motivates a growing interest in video editing tasks, wh

VIGOR: Zero-Shot Visual Generalization via Latent-Space Consistency in Model-Based Reinforcement Learning

arXiv:2610.02801v1 Announce Type: new Abstract: Model-based reinforcement learning (MBRL) achieves strong sample efficiency by planning within learned latent dynamics, yet its performance degrades sub

VisAudit: Evaluating Multimodal Agents for Visual Diagnosis and Repair

model-releasesarxiv-cs-lg

arXiv:2610.02399v1 Announce Type: new Abstract: Multimodal agents are increasingly used for data visualization tasks but remain limited in autonomous review. Unlike humans, they may fail to recognize

VisionMX: Unlocking Microscaling Post-Training Quantization for Vision Models

arXiv:2610.03218v1 Announce Type: new Abstract: Microscaling (MX) formats are emerging as a hardware-supported approach to efficient training and inference. They combine low-precision elements with sh

safetyarxiv-cs-cv

ViTok: Improving Dense Semantics in AM-RADIO-Style Multi-Teacher Distillation with PHI-S and Masked Image Modelling

model-releasesarxiv-cs-cv

arXiv:2610.02903v1 Announce Type: new Abstract: We study how to consolidate the current VITOK progress into a single multi-teacher distillation recipe that jointly preserves global recognition and den

VTBench: Evaluating Visual Tokenizers for Autoregressive Image Generation

arXiv:2505.13439v2 Announce Type: replace-cross Abstract: Autoregressive (AR) models have recently shown strong performance in image generation, where a critical component is the visual tokenizer (VT)

WakeKV: Reactive, Reversible KV Residency for Heads That Change Their Minds

arXiv:2610.02713v1 Announce Type: new Abstract: Most KV-cache compression methods classify attention heads once, either offline or during prefill, and keep this classification fixed throughout generat

WAMpy: Efficient Synthesis of Prolog Programs in Python

arXiv:2610.03234v1 Announce Type: cross Abstract: We present WAMpy, a Python framework optimized for synthesizing Prolog programs. Unlike general-purpose Prolog systems, WAMpy targets workloads that r