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STyMo: Fast and Controllable Few-Shot Motion Style Transfer

arXiv:2609.04500v1 Announce Type: cross Abstract: Supporting a wide variety of motion styles is critical for creating diverse virtual characters, but current methods either require large stylized data

Substrate-Aware AI Agents: Execution Context as a First-Class Input

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DGX agent

arXiv:2609.05232v1 Announce Type: new Abstract: Autonomous AI agents increasingly select actions in environments whose memory, execution-time, runtime, compute, and operational constraints determine w

model-releasesarxiv-cs-ai

7 Sept 2026

Sustainable Edge Vision via Empirically Calibrated DVFS: Eliminating Thermal Throttling on Passively Cooled Hardware

arXiv:2609.04705v1 Announce Type: cross Abstract: Passive cooling eliminates the energy overhead and mechanical failure modes of fans, making it attractive for edge deployment, yet sustained Deep Neur

TacPAC: Tactile Prediction and Real-Time Action Correction in World-Action Models for Contact-Rich Manipulation

arXiv:2609.05266v1 Announce Type: new Abstract: World-action models guide action generation with predicted future observations, but vision-centric predictions miss the local contact cues that decide c

local-aiarxiv-cs-ro

Technical Manual for a Toolkit for Measuring Contextual Individuation in Transformer Language Models

arXiv:2609.05333v1 Announce Type: new Abstract: A transformer language model assigns a single, context-independent vector to a word type at its embedding layer, yet is widely believed to individuate t

local-aiarxiv-cs-ai

TeleTables: A Benchmark for Large Language Models in Telecom Table Interpretation

arXiv:2601.04202v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are increasingly applied to telecom engineering tasks, yet perform poorly on 3GPP specifications. These standards

Temporal Residual Neural Radiance Fields for Monocular Video Dynamic Human Body Reconstruction

arXiv:2609.04984v1 Announce Type: new Abstract: In the field of computer vision and graphics, high-quality reconstruction of the human body in static scenes has been achieved in recent years by a sing

Temporal Tactile Encoding and Compliance for Intent-Aware Robot-to-Human Bimanual Handover

model-releasesarxiv-cs-ro

arXiv:2609.05282v1 Announce Type: new Abstract: Reliable robot-to-human handover requires the robot to infer when the person is ready to receive the object, and release it safely, comfortably, and at

Test-Time Adaptation via Cache Personalization for Facial Expression Recognition in Videos

model-releasesarxiv-cs-cv

arXiv:2603.21309v4 Announce Type: replace Abstract: Facial expression recognition (FER) in videos requires model personalization to capture considerable variation across subjects. Vision-language mode

Agents

Testing Interchangeability in LLM Agent Teams

arXiv:2609.05279v1 Announce Type: new Abstract: Production multi-agent systems replace agents constantly, on the assumption that an agent filling a role is interchangeable with any other agent that ca

agentsarxiv-cs-ai

The Anatomy of an ASR Hallucination

arXiv:2609.04404v1 Announce Type: new Abstract: ASR systems sometimes produce fluent text that is unrelated to the speech they receive. We view these hallucinations as one possible consequence of a br

researcharxiv-cs-cl

The Geometry of Polynomial Group Convolutional Neural Networks

arXiv:2603.29566v2 Announce Type: replace Abstract: We study polynomial group convolutional neural networks (PGCNNs) for an arbitrary finite group G. In particular, we introduce a new mathematical fra

researcharxiv-cs-lg

The History Is the Detector: Executing CVE Patch History, End-to-End

arXiv:2609.05335v1 Announce Type: cross Abstract: Public vulnerability databases collect rich information about known software flaws, including their weakness types, affected components, and related p

The microscope is the mask: privileged views and labels from a cryo-ET forward model

model-releasesarxiv-cs-cv

arXiv:2609.04325v1 Announce Type: new Abstract: We explore the use of simulated data for training a model for protein annotation in crowded cryo-electron tomography volumes reconstructed from images c

Agents

The Mirror Agent Model: a Bayesian Architecture for Interpretable Agent Behavior

arXiv:2609.05190v1 Announce Type: new Abstract: In this paper we illustrate a novel architecture generating interpretable behavior and explanations. We refer to this architecture as the Mirror Agent M

agentsarxiv-cs-ai

The Sample Complexity of Learning Lipschitz Operators with respect to Gaussian Measures

arXiv:2410.23440v4 Announce Type: replace Abstract: Operator learning, the approximation of mappings between infinite-dimensional function spaces using machine learning, has gained increasing research

researcharxiv-cs-lg

The Struggle Between Continuation and Refusal: A Mechanistic Analysis of the Continuation-Triggered Jailbreak in LLMs

arXiv:2603.08234v2 Announce Type: replace Abstract: With the rapid advancement of large language models (LLMs), the safety of LLMs has become a critical concern. Despite significant efforts in safety

safetyarxiv-cs-ai

Think-Verify-Revise: Neuro-Symbolic Visual Reasoning with Vision-Language Models and Dynamic Logic Tensor Networks

model-releasesarxiv-cs-cv

arXiv:2609.05388v1 Announce Type: new Abstract: Visual reasoning tasks require a system to jointly perceive visual content and apply formal relational constraints---a combination that neither pure neu

TIER: Threat Implicitness Benchmark for Evaluating LLM Safety Behaviors

arXiv:2609.05117v1 Announce Type: cross Abstract: Current LLM safety benchmarks largely rely on binary metrics, overlooking how models respond to harmful prompts with varying threat implicitness. We i

TNFlow: Amortized Posterior Inference for Trans-Neptunian Object Surface Composition

arXiv:2609.04305v1 Announce Type: cross Abstract: We present TNFlow, a transformer and normalizing flow architecture for inferring the surface composition of Trans-Neptunian Objects (TNOs) from their

safetyarxiv-cs-lg

TokenDial: Continuous Attribute Control for Text-to-Video Generation in Visual Dial Space

arXiv:2603.27520v2 Announce Type: replace Abstract: In video diffusion transformers, visual patch tokens maintain explicit correspondence to space and time. We hypothesize that their channel dimension

Too Rare to Learn: Prescribed Cyclone Tracks Degrade a Bay of Bengal Ocean Emulator

arXiv:2609.04635v1 Announce Type: new Abstract: Neural ocean emulators are being proposed for regional forecasting in cyclone-exposed coastal seas, and a natural design choice is to hand the network t

tutorialsarxiv-cs-lg

Topology-Aware Training and Spatial Diagnostics for Fiber Bundle Segmentation in Tracer Histology

arXiv:2609.04454v1 Announce Type: new Abstract: Anatomic tracer studies reveal how axon bundles project from an injection site, branch into smaller groups of axons, and course through the brain to rea

tutorialsarxiv-cs-cv

ToPos: Automated Optimal Positioning on Topographic Manifolds using Constrained Geodesic Voronoi Decomposition

arXiv:2609.05084v1 Announce Type: new Abstract: Reliable autonomous mapping, environmental sampling, last-mile logistics, and infrastructure deployment depend on the optimal surface area-balanced dist

safetyarxiv-cs-ro

TourPhysics: Bringing Physics to World Models for Exploration and Manipulation from a Single Image

arXiv:2609.04911v1 Announce Type: new Abstract: Interactive visual world models must distinguish observation from physical intervention. Camera motion reveals new surfaces, whereas intervention change

Toward Context-Aware Exoskeleton Assistance: Integrating Computer Vision Payload Estimation with a Multi-Metric Optimization Space

arXiv:2508.06207v3 Announce Type: replace Abstract: Back-support exoskeletons mitigate musculoskeletal strain, yet current systems rely on reactive sensing and lack context-aware assistance modulation

researcharxiv-cs-ro

Towards a universal language of concepts: A survey

arXiv:2609.04528v1 Announce Type: new Abstract: Humans can learn and generalize novel concepts from sparse data because they express knowledge in rich structural formats. In this paper, we propose tha

tutorialsarxiv-cs-ai

Towards Efficient Evaluation of Evolutionary Transfer Optimization: Case Studies on Task-Parameterized Applications

arXiv:2609.05040v1 Announce Type: new Abstract: As evolutionary transfer optimization (ETO) scales to larger collections of related tasks, problem evaluation can become a major source of runtime growt

Towards Efficient Parametric State Estimation in Circulating Fuel Reactors with Shallow Recurrent Decoder Networks

arXiv:2503.08904v3 Announce Type: replace Abstract: The recent developments in data-driven methods have paved the way to new methodologies to provide accurate state reconstruction of engineering syste

researcharxiv-cs-lg

Towards Neuro-Symbolic Procedural Reasoning for Long-Horizon Vision-Language-Action Manipulation

arXiv:2609.05369v1 Announce Type: cross Abstract: Vision-language-action (VLA) models can execute short manipulation skills, but remain brittle in long-horizon procedures requiring persistent task sta

safetyarxiv-cs-cv

Towards Understanding Pause Token Fine-Tuning Dynamics: A Mode Retention Perspective

arXiv:2609.04489v1 Announce Type: cross Abstract: Pause-token methods improve LLM reasoning by inserting special tokens into sequences. Prior work explains these gains through computational expressivi

Agents

Trace2Tower: Transition-Aware EigenTrace Induction of Multi-Level Skills for LLM Agents

arXiv:2609.05261v1 Announce Type: new Abstract: Large language model agents increasingly rely on execution traces to master complex interactive tasks. However, current paradigms are bottlenecked by sh

agentsarxiv-cs-ai

Tracing Audio Grounding and Answer Selection in Audio LLMs

arXiv:2609.04637v1 Announce Type: cross Abstract: Audio Large Language Models (Audio LLMs) have advanced in audio understanding, yet they can still predict the answer by reasoning from textual cues or

Train What You Deploy:Token-Faithful Post-Training of a Production Coding

arXiv:2609.04678v1 Announce Type: new Abstract: Existing post-training pipelines for coding and terminal agents suffer severe token and control fidelity errors: simplified training environments mismat

safetyarxiv-cs-ai

Training-Free Halving of Activated Experts in Fine-Grained Mixture-of-Experts Models

arXiv:2609.04575v1 Announce Type: cross Abstract: Modern fine-grained Mixture-of-Experts (MoE) models route each token to a small number of experts and renormalize their router probabilities. We show

Training-Free Logical and Structural Anomaly Detection via Calibrated Fusion

arXiv:2609.05091v1 Announce Type: new Abstract: Industrial anomaly detection must handle two distinct defect families: structural anomalies, which manifest as local texture corruptions, and logical an

Training-Free Speech-Centric Omni Understanding with Frozen VLMs

arXiv:2609.04242v1 Announce Type: cross Abstract: Audio-visual understanding remains challenging because models must jointly interpret spoken content, visual events, and their temporal relationships.

safetyarxiv-cs-cv

Training Large Language Models for Small-Molecule Design with Synthetic Task Scaling

arXiv:2609.04735v1 Announce Type: new Abstract: Designing viable drug candidates requires searching a combinatorially large and rugged chemical space for molecules that satisfy multiple, often competi

tutorialsarxiv-cs-lg

TreeFI: Value-Aware Statistical Fault Injection for Deep Neural Networks

arXiv:2609.04912v1 Announce Type: cross Abstract: Reliability evaluation of deep neural networks under hardware faults commonly relies on fault injection, but exhaustive campaigns are intractable for

TRILOGUE: A Trilingual Spoken Dialogue Fact-Checking Benchmark with Evidence and Paired Audio

model-releasesarxiv-cs-cl

arXiv:2609.04452v1 Announce Type: new Abstract: Modern misinformation is often heard before it is read, yet fact-checking systems are still evaluated mainly on clean written claims. Spoken dialogue re

TROVE: Adaptive Agent Skill Orchestration via Trace-Grounded Route Validation and Editing

arXiv:2609.05019v1 Announce Type: new Abstract: Agents tend to optimize, select, or constrain execution structures before decisive runtime outcomes are observed. However, such pre-execution commitment

local-aiarxiv-cs-ai

TruthInsightBench: An Evidence-Grounded Benchmark for Automated Evaluation of Open-Ended Scientific Discovery Agents

arXiv:2609.05079v1 Announce Type: new Abstract: Autonomous coding agents are increasingly proposed as AI-scientist systems that conduct analyses and write research reports, but executing a prescribed

TSMini: A Simple Yet Highly Effective Trajectory Similarity Learning Model

arXiv:2502.00285v3 Announce Type: replace-cross Abstract: Trajectory similarity is fundamental to many spatio-temporal data mining applications. Recent studies propose deep learning models to approxim

tutorialsarxiv-cs-cv

Hardware

Tuning Collective Patterns to Alleviate Congestion in Shared AI Clusters

arXiv:2609.04417v1 Announce Type: cross Abstract: Distributed AI training involves recurring rounds of data exchange between multiple pairs of GPU nodes. Slowdown in even one flow due to congestion ca

hardwarearxiv-cs-lg

Ultrasound-Based Prediction of Cirrhosis Decompensation Using Large-Scale Computer Vision Models

arXiv:2609.04365v1 Announce Type: cross Abstract: Decompensation represents a critical transition in the course of cirrhosis, yet clinicians have limited non-invasive tools to reliably predict its ons

tutorialsarxiv-cs-ai

Uncensored Open-weight Models: Redistribution as the Persistence Layer

arXiv:2609.05241v1 Announce Type: new Abstract: A rapidly expanding ecosystem of actors is removing built-in safety guardrails from open-weight AI models. We profile this ecosystem by identifying key

local-aiarxiv-cs-ai

Uncertainty Signals for Network Intent Translation: Risk Ranking and Ambiguity Localization

model-releasesarxiv-cs-cl

arXiv:2609.04486v1 Announce Type: cross Abstract: Intent-based networking realization starts by translating high-level intents into low-level network configurations. Recent approaches have shifted tow

Unifying ICL, SFT, KL-Regularized RL Through a Bayesian Lens

arXiv:2609.05111v1 Announce Type: new Abstract: Large language models are now trained and evaluated under a diverse set of paradigms: supervised fine-tuning (SFT), few-shot in-context learning (ICL),