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UniMate: One Unified Model to Animate Diverse Skeletons

arXiv:2609.05415v1 Announce Type: new Abstract: Recent advances in automatic rigging now deliver animation-ready 3D assets at scale, yet generating the motion to drive them remains a bottleneck. Exist

safetyarxiv-cs-cv

Variational Continuation for Double Pendulum Periodic Orbits

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DGX agent

arXiv:2609.05337v1 Announce Type: new Abstract: We present a Hessian-based approach to numerically continue periodic orbits in dynamical systems. A loop (periodic orbit candidate) is parametrized as a

researcharxiv-cs-lg

7 Sept 2026

Vectorizing Classical Tamil: Representation Learning for Verse-Commentary Pairs

arXiv:2609.04755v1 Announce Type: new Abstract: We construct a corpus of 1,262 verse-commentary (urai) pairs from five Classical Tamil source sections, ranging from technical grammatical prose to mode

researcharxiv-cs-cl

VERGE: Verification-Enhanced Refinement for Grounded Extraction of Early-Onset Colorectal Cancer Symptoms in Clinical Notes

arXiv:2609.04366v1 Announce Type: new Abstract: Early-onset colorectal cancer is increasing among younger adults, yet red-flag symptoms in this age group have no evidence-based guidelines for follow-u

agentsarxiv-cs-cl

VICAL: Vicinal Consistency Alignment for Long-Tailed Visual Recognition

arXiv:2609.04948v1 Announce Type: cross Abstract: Multi-expert models have become the dominant paradigm for long-tailed learning, largely attributed to their presumed ability to benefit from expert di

VISTA: Dense Multi-Label Classroom Coding with Vision-Language Models

arXiv:2609.04550v1 Announce Type: new Abstract: Video-language benchmarks are usually constructed by the dataset authors without published reliability statistics, leaving the noise floor of the constr

VLA-Precision: Asymmetric Co-Bootstrapping for Efficient Real-World Online RL of Vision-Language-Action Models

arXiv:2609.04355v1 Announce Type: cross Abstract: Pretrained vision-language-action (VLA) models enable broad manipulation but remain unreliable in tasks demanding precision and repeatability. Applyin

VoxelFix: Post-Hoc Semantic Correction of Completed 3D Voxel Maps

arXiv:2609.05114v1 Announce Type: new Abstract: Semantic 3D maps are increasingly constructed automatically for aerial robotics by integrating learned semantic predictions into 3D representations. Whi

local-aiarxiv-cs-cv

Water Reflection Detection Using Symmetric Attention

arXiv:2607.10749v2 Announce Type: replace Abstract: Reflections of water pose a significant challenge for computer vision systems, as standard deep learning models frequently confuse objects with thei

Applications

WaveletDiff: Multilevel Wavelet Diffusion For Time Series Generation

arXiv:2510.11839v3 Announce Type: replace Abstract: Time series are ubiquitous in many applications that involve forecasting, classification and causal inference tasks, such as healthcare, finance, au

applicationsarxiv-cs-lg

WeAgent-MMGenEdit: A Full-Stack Recipe for Multimodal Agentic Image Generation and Editing

arXiv:2609.05171v1 Announce Type: new Abstract: Image generation and editing models have advanced rapidly, yet remain unreliable when prompts require external world knowledge. Bounded and long-tail pa

Tutorials

WeakMCN: Multi-task Collaborative Network for Weakly Supervised Referring Expression Comprehension and Segmentation

arXiv:2505.18686v3 Announce Type: replace Abstract: Weakly supervised referring expression comprehension(WREC) and segmentation(WRES) aim to learn object grounding based on a given expression using we

tutorialsarxiv-cs-cv

WearableQA: A Benchmark for Health Reasoning over Real-World Wearable Data

model-releasesarxiv-cs-cl

arXiv:2609.05405v1 Announce Type: new Abstract: Recent advances in wearable sensing enable continuous monitoring of physiological and behavioral signals, yet existing benchmarks rarely evaluate whethe

Weather-Conditioned Depth Anything

arXiv:2609.04827v1 Announce Type: new Abstract: Monocular depth estimation foundation models, such as the Depth Anything series, have achieved remarkable performance across diverse domains. However, t

WEECFP-SuRGE: Wide Embedded Extended Connectivity Fingerprint with Substructure Rotary Graph-distance Encoding

arXiv:2609.04672v1 Announce Type: new Abstract: We introduce WEECFP, a parameter-free 1024-dimensional continuous molecular fingerprint that scatters each Morgan substructure across roughly thirty-two

What Attention Recalls and Recurrence Controls in Hybrid Language Models

arXiv:2609.04434v1 Announce Type: new Abstract: Hybrid language models combine attention with a fixed-size recurrent state, but the role of each channel remains unclear. We introduce two cache-level i

researcharxiv-cs-cl

What Does Multi-Harness RL Learn? Credit Assignment and Portability in Coding Agents

arXiv:2609.04518v1 Announce Type: new Abstract: Agent reinforcement learning (RL) increasingly runs through full execution harnesses, and a multi-harness recipe mixes two choices: exposing the policy

What Matters in On-Policy Distillation? A Perspective on Data Efficiency and Data Selection

arXiv:2609.05198v1 Announce Type: new Abstract: On-Policy Distillation (OPD) has emerged as a widely adopted post-training paradigm for enhancing large language models in reasoning domains. However, t

What Matters, When? Diagnosing and Improving Conditional Visual Grounding in Visuomotor Imitation Policies

arXiv:2609.05376v1 Announce Type: cross Abstract: Visuomotor imitation policies can achieve high performance under in-distribution visual conditions yet fail when visually similar objects or receptacl

What Moves? Localized Motion Representations for Compositional Scene Control

arXiv:2609.04383v1 Announce Type: cross Abstract: Real-world dynamics are inherently compositional: multiple entities move simultaneously within a shared scene, each exhibiting distinct motion pattern

local-aiarxiv-cs-ai

When Do Internal Probes Beat Reading the Answer? Miscalibrated Readouts and Behavior-Concealed Knowledge in Language Models

arXiv:2609.04582v1 Announce Type: cross Abstract: A 0.6B language model, asked to verify 1,200 logical conclusions (half valid, half corrupted by a single semantic edit), answers YES every time. Judge

When Does an Interpretation Count as Established? The Formation, Evaluation, and Responsibility of Interpretation in Generative AI

arXiv:2609.04766v1 Announce Type: cross Abstract: Generative AI research has increasingly evaluated factuality, citation, coverage, and report structure. Yet passing such local checks does not by itse

When Financial Fine-tuning Fails: A Three-Level Detectability Analysis of Numerical Hallucination in Domain-Adapted Language Models

arXiv:2609.04806v1 Announce Type: new Abstract: Financial large language models are increasingly deployed for summarization of reports and disclosures, where numerical hallucination poses significant

researcharxiv-cs-ai

When Genomic Masking Priors Fail to Transfer: Strong Variant Prediction, Weak Functional Generation

arXiv:2609.04861v1 Announce Type: new Abstract: Bidirectional discrete diffusion model appears naturally suited to genomic modeling because it can reconstruct missing sequence from both flanks. We dev

When LLM Decompilers Recompile More and Preserve Less

arXiv:2609.05370v1 Announce Type: cross Abstract: Decompilation recovers high-level source from compiled machine code and serves as a foundation for security tasks such as vulnerability detection and

researcharxiv-cs-ai

When Load-Balancing Goes Too Far: Expert Pruning in Over-Dispersed Mixture-of-Experts Models

arXiv:2609.04453v1 Announce Type: cross Abstract: Expert pruning reduces the memory and serving cost of Mixture-of-Experts (MoE) models by removing low-importance experts identified by the router, ass

When Quantization Breaks Memory: Recurrent-State Write-Back in Low-Precision Temporal Inference

arXiv:2609.04490v1 Announce Type: new Abstract: Quantization is widely used to reduce the computational and memory demands of neural-network inference. In recurrent networks, however, the quantized st

researcharxiv-cs-ai

When Seeing Overrides Knowing: Visual Dominance and Deferral-Based Method for Personalized Safety in VLMs

arXiv:2609.04281v1 Announce Type: cross Abstract: Vision-language models (VLMs) are increasingly deployed in high-stakes settings, where a response that is reasonable in general may still be unsafe fo

Where Appearance Fails, Geometry Recognizes: A CAD-Free 3D Shape Prior That Complements Vision Foundation Models

arXiv:2609.04381v1 Announce Type: cross Abstract: Recognizing specific objects onboarded without a labeled training set recurs across manufacturing and service robotics, yet the conventional renderabl

Where to Look Matters: Learning Influential Views for VLM-based 3D Visual Grounding

arXiv:2609.04741v1 Announce Type: new Abstract: Recent zero-shot 3D visual grounding methods leverage vision-language models (VLMs) to localize objects in 3D scenes from natural language queries. Howe

local-aiarxiv-cs-cv

Tutorials

Who Should Grade My Work? Student Perspectives on Transparent AI-Assisted Writing Assessment in Higher Education

arXiv:2609.05346v1 Announce Type: new Abstract: The integration of GenAI tools into higher education assessment raises important questions about how students understand, interpret, and respond to AI-m

tutorialsarxiv-cs-ai

Whose record is this? Diagnosing and authorizing record use in personalized multimodal models

arXiv:2609.04801v1 Announce Type: new Abstract: Contextualized visual personalization can retrieve a true record yet apply it to the wrong visual subject. We formalize when a record may condition an a

Why Better Models Can Create Riskier Systems: Evidence from LLM Agents in Financial Markets

arXiv:2609.04373v1 Announce Type: new Abstract: Large language models (LLMs) are being deployed at scale in consequential real-world systems, from financial markets to content moderation to hiring. We

Tutorials

Why We Care About Understanding: Competence through Predictive Compression

arXiv:2609.04962v1 Announce Type: new Abstract: What is the relation between understanding and compression, and why does human understanding take such a heavily compressed form? Across information the

tutorialsarxiv-cs-ai

Applications

Wireless Foundation Models: State-of-the-Art and Open Challenges

arXiv:2609.04707v1 Announce Type: cross Abstract: Wireless foundation models (WFMs) have emerged as a promising approach for learning reusable representations from large-scale wireless data and adapti

applicationsarxiv-cs-ai

WorldSculpt: Generating Compositional Worlds from Grounded Videos

arXiv:2609.05416v1 Announce Type: new Abstract: We study the problem of generating a compositional 3D representation of a cluttered scene containing hundreds of objects. The goal is to represent the s

YOLO with Kolmogorov-Arnold networks and vision-language foundation models for interpretable object detection with trustworthy multimodal AI in computer vision perception

arXiv:2603.23037v2 Announce Type: replace-cross Abstract: The trustworthy object detection capabilities of a novel Kolmogorov-Arnold network framework are examined here. The approach addresses a key l

You Really Didn't Get That? Benchmarking Social Pragmatic Inference for Indirect and Playful Chinese Online Comments

arXiv:2609.04384v1 Announce Type: cross Abstract: Chinese online comments often convey social meaning through indirect and playful language that is hard to interpret without context. Existing evaluati

A Blind Trust, the Bloody Thrust: When Attacker-Controlled Hook Updates Steer AI Agent Harnesses towards Malicious Behaviors

arXiv:2609.03884v1 Announce Type: cross Abstract: Modern AI agent harnesses expose lifecycle hooks that bind shell commands to runtime events such as session start, tool calls, and file edits. These c

A Case Study on Emergent Cheating and Whistleblowing in Autonomous Research Swarms

arXiv:2609.04170v1 Announce Type: new Abstract: Multi-agent AI science ecosystems rely on agents possessing tools that allow them to communicate, coordinate, and build on each other's work. Yet this s

A cautionary tale on the cost-effectiveness of collaborative AI in real-world medical applications

arXiv:2412.06494v2 Announce Type: replace Abstract: Background. Federated learning (FL) has gained wide popularity as a collaborative learning paradigm enabling collaborative AI in sensitive healthcar

A Circuit for Plural Reference: How LLMs Represent and Retrieve Singular and Plural Entities

arXiv:2609.03687v1 Announce Type: new Abstract: Coreference resolution is an important task in contextual reasoning. In this paper, we investigate the mechanism for representing and retrieving singula

researcharxiv-cs-cl

A Closed-Form Formula for Consistent Lipschitz Regression on Metric Spaces with Sparse Neural Network Realizations

arXiv:2609.03129v1 Announce Type: cross Abstract: Several classical machine-learning methods, such as KRRs and SVRs, are both computationally and analytically tractable since their estimators either a

A comparative study on the accuracy & repeatability of mobile robotic platforms for the delivery of precision NDE measurement

arXiv:2609.03794v1 Announce Type: new Abstract: Mobile robotic platforms offer a flexible alternative to fixed manipulators for non-destructive evaluation (NDE) of large aerospace structures, but thei

safetyarxiv-cs-ro

A computable representation of the physical laboratory enables verifiable workflows

arXiv:2609.03621v1 Announce Type: new Abstract: Making science computable requires representations of both scientific knowledge and the physical world in which scientific claims are tested. A computab

A Computationally Feasible Framework for Causal Probabilistic Explanation

arXiv:2609.04177v1 Announce Type: new Abstract: Explaining why a specific outcome occurred, and which inputs deserve the blame or credit, is central to philosophical, scientific, and policy analysis.

A hybrid pipeline for dynamic ontology-based semantic mapping

arXiv:2609.03891v1 Announce Type: new Abstract: Semantic mapping plays a crucial role in the ability of a robot to interact with objects, operate and navigate a complex environment. The most common pi

local-aiarxiv-cs-ro

A Large Open Multi-Energy Corpus of Soil Compaction Tests, with Machine-Learning Baselines

arXiv:2609.03337v1 Announce Type: new Abstract: Every engineered fill is specified by a maximum dry density and an optimum moisture content. Each determination needs a full Proctor test. Published cor