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Unsupervised Detection of Underground Tunnels in Ground-Penetrating Radar Using Depth-Restricted Reconstruction Scoring

arXiv:2607.04882v1 Announce Type: new Abstract: Clandestine tunneling beneath oil and gas pipelines enables fuel theft, smuggling, and sabotage, yet conventional monitoring detects damage only after a

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Research

Unsupervised Features Mining via Activation Geometry

DGX agent

arXiv:2607.04222v1 Announce Type: new Abstract: Interpretability methods aim to reveal the features represented inside large language models (LLMs). Many existing methods begin with labeled examples o

researcharxiv-cs-ai

7 Jul 2026

Unsupervised Pixel-Level Semantic Left-Right Understanding of In-the-Wild Images

arXiv:2607.05006v1 Announce Type: new Abstract: While various works address reflective symmetry understanding in 3D data and images, pixel-level semantic left-right prediction of in-the-wild images re

Agents

Untrusted Content Masking for Web Agents with Security Guarantees

arXiv:2607.05277v1 Announce Type: cross Abstract: Defenses that provide security guarantees against prompt injection attacks rely on strict isolation between trusted instructions and untrusted data. I

agentsarxiv-cs-lg

Unveiling the Unborn: Advancing Fetal Health Classification through Machine Learning

arXiv:2310.00505v3 Announce Type: replace-cross Abstract: Fetal health classification is a critical task in obstetrics, enabling early identification and management of potential health problems. Howev

applicationsarxiv-cs-ai

URSA: Chemistry-Aware Benchmark for Utilitarian Retrosynthesis Assessment

arXiv:2607.04688v1 Announce Type: cross Abstract: Synthesis planning aiming to find pathways of reactions for a target molecule is one of the most important and challenging tasks in drug discovery. Re

USE: A Unified Self-Ensembling Framework for Test-Time Prompt Tuning

arXiv:2607.03900v1 Announce Type: new Abstract: Test-time adaptation (TTA) has emerged as a popular paradigm for improving the performance of vision-language models (e.g., CLIP) on downstream tasks. A

Using Mechanistic Interpretability to Craft Adversarial Attacks against Large Language Models

arXiv:2503.06269v3 Announce Type: replace-cross Abstract: Traditional white-box methods for creating adversarial perturbations against LLMs typically rely only on gradient computation from the targete

Agents

Utonia: Toward One Encoder for All Point Clouds

arXiv:2603.03283v2 Announce Type: replace Abstract: We dream of a future where point clouds from all domains can come together to shape a single model that benefits them all. Toward this goal, we pres

agentsarxiv-cs-cv

Validation-Induced Shapley Shifts: How Validation Structure Distorts Data Valuation

arXiv:2607.03675v1 Announce Type: new Abstract: Shapley values are widely used to attribute value to training data based on their marginal contribution to performance on a validation set. Existing pra

Variable Bit-width Quantization: Learning Per-Group Precision for 'Bigger-but-Smaller' Language Models

model-releasesarxiv-cs-cl

arXiv:2607.02893v1 Announce Type: cross Abstract: Low-bit quantization shrinks language models but treats precision as a single global hyper-parameter: every weight uses the same bit-width. We introdu

Variational Sparse Paired Autoencoders (vsPAIR) for Inverse Problems and Uncertainty Quantification

arXiv:2602.02948v3 Announce Type: replace Abstract: Inverse problems are fundamental to many scientific and engineering disciplines; they arise when one seeks to reconstruct hidden, underlying quantit

VCB Bench: An Evaluation Benchmark for Audio-Grounded Large Language Model Conversational Agents

model-releasesarxiv-cs-cl

arXiv:2510.11098v5 Announce Type: replace-cross Abstract: Recent advances in large audio language models (LALMs) have greatly enhanced multimodal conversational systems. However, existing benchmarks r

Verifier-free Test-Time Sampling for Vision-Language-Action Models

arXiv:2510.05681v2 Announce Type: replace-cross Abstract: Vision-Language-Action models (VLAs) have demonstrated remarkable performance in robot control. However, they remain fundamentally limited in

tutorialsarxiv-cs-ai

VERITAS: Towards a General-Purpose Replication Tool for Scientific Research

arXiv:2607.02931v1 Announce Type: new Abstract: AI tools are accelerating scientific publication while the systems that review it struggle to keep up, and independent verification of published researc

VesselTok: Tokenizing Vessel-like 3D Biomedical Graph Representations for Reconstruction and Generation

arXiv:2603.18797v2 Announce Type: replace Abstract: Spatial graphs provide a lightweight and elegant representation of curvilinear anatomical structures such as blood vessels, lung airways, and neuron

tutorialsarxiv-cs-cv

Video-based detection of cessation of breathing in pre-term infants using machine learning

arXiv:2607.05230v1 Announce Type: new Abstract: Pre-term infants are susceptible to potentially harmful apnoea-related cessations of breathing due to immature respiratory control. However, reliable re

Video Generation Models Are Inherent Lighting Estimators

arXiv:2607.04674v1 Announce Type: new Abstract: Recovering dynamic environment maps from a single in-the-wild video is crucial for photorealistic rendering, yet remains a challenge. Recent video gener

VideoSearcher: Empowering Video Deep Research with Multi-Tool Agentic Reasoning via Reinforcement Learning

arXiv:2607.02927v1 Announce Type: cross Abstract: Video understanding is moving beyond closed-context perception toward open-world evidence exploration, a paradigm formalized as Video Deep Research (V

Vidu S1: A Real-Time Interactive Video Generation Model

arXiv:2607.03118v1 Announce Type: new Abstract: We introduce Vidu S1, a real-time interactive video generation model supporting voice control of digital characters. Users can control video generation

ViPo-MLLM: Visual-Pose Multimodal LLM for Gloss-Free Sign Language Translation

arXiv:2607.03657v1 Announce Type: cross Abstract: Gloss-free Sign Language Translation (SLT) translates sign language videos into spoken-language sentences without gloss annotations, avoiding costly l

Virtual Category-Guided Continual Generalized Category Discovery

arXiv:2607.04984v1 Announce Type: new Abstract: Continual Generalized Category Discovery (C-GCD) aims to incrementally identify novel categories from sequential unlabeled data while preserving recogni

safetyarxiv-cs-cv

Vision Non-Causal Trapezoidal Mamba: Eliminating Directional Scanning in Vision SSMs with Second-Order Dynamics

arXiv:2607.03589v1 Announce Type: new Abstract: State Space Models (SSMs) have emerged as an alternative to Vision Transformers, yet most vision SSMs inherit directional token scanning from causal seq

safetyarxiv-cs-cv

Vision Pretraining for Dense Spatial Perception

arXiv:2607.05247v1 Announce Type: new Abstract: Dense spatial perception is essential for physical intelligence, where visual systems are expected to recover structured, metric, and actionable represe

Vision Token Manipulation Attacks on Cloud-Edge Inference of Large Vision-Language Models

arXiv:2607.02819v1 Announce Type: cross Abstract: Cloud-edge Large Vision-Language Model (LVLM) inference enables efficient deployment by splitting computation between edge devices and cloud servers.

VISOR++: Universal Visual Inputs based Steering for Large Vision Language Models

arXiv:2509.25533v2 Announce Type: replace-cross Abstract: As Vision Language Models (VLMs) are deployed across safety-critical applications, understanding and controlling their behavioral patterns has

VISOR: Visual Input-based Steering for Output Redirection in Vision-Language Models

arXiv:2508.08521v2 Announce Type: replace-cross Abstract: Vision Language Models (VLMs) are increasingly being used in a broad range of applications, bringing their security and behavioral control to

VISTA: Auditing Semantic Divergence in Vision-Language Models

arXiv:2607.02995v1 Announce Type: cross Abstract: Vision-language models can exhibit visual concept-conditioned divergence: given images containing demographic features, corporate logos, or ideologica

VKnowU: Evaluating Visual Knowledge Understanding in Multimodal LLMs

model-releasesarxiv-cs-cv

arXiv:2511.20272v2 Announce Type: replace Abstract: While Multimodal Large Language Models (MLLMs) have become adept at recognizing objects, they often lack the intuitive, human-like understanding of

VLA Grounder: Language-Conditioning Space Optimization for Black-Box VLA Models

arXiv:2607.04517v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models are commonly treated as end-to-end action policies conditioned on natural-language task descriptions. In practice, h

VLM-CASE: Vision-Language Model Enabled Context-Adaptive Safety Envelopes for Anticipatory Safe Autonomous Driving

arXiv:2607.05180v1 Announce Type: cross Abstract: Adverse driving conditions, such as bad weather, remain a principal barrier to autonomous driving because they degrade two things at once: what the ve

safetyarxiv-cs-cv

VLMEvalKit: An Open-Source Toolkit for Evaluating Large Multi-Modality Models

model-releasesarxiv-cs-cv

arXiv:2407.11691v5 Announce Type: replace Abstract: We present VLMEvalKit: an open-source toolkit for evaluating large multi-modality models based on PyTorch. The toolkit aims to provide a user-friend

VLMGuard: Bootstrapping Malicious Prompt Detectors from Unlabeled Vision-Language Prompts in the Wild

arXiv:2410.00296v2 Announce Type: replace Abstract: Vision-language Models (VLMs) are essential for contextual understanding of both visual and textual information. However, their vulnerability to adv

VLRC: Vision-Language Reprojection Consistency as a scalable signal for better feed-forward 3D pretraining

arXiv:2607.02707v1 Announce Type: new Abstract: Feed-forward 3D models are commonly trained using either expensive geometric supervision or self-supervised photometric objectives, both of which provid

Walma: Learning to See Memory Corruption in WebAssembly

arXiv:2603.24167v2 Announce Type: replace-cross Abstract: WebAssembly's (Wasm) monolithic linear memory turns a single memory-corruption bug into a bidirectional threat: a compromised module can attac

Walrus: A Cross-Domain Foundation Model for Continuum Dynamics

arXiv:2511.15684v2 Announce Type: replace-cross Abstract: Foundation models have transformed machine learning for language and vision, but achieving comparable impact in physical simulation remains a

WAM4D: Fast 4D World Action Model via Spatial Register Tokens

arXiv:2606.14048v2 Announce Type: replace Abstract: World action models (WAMs) have recently shown promise in jointly modeling future observations and executable robot actions. However, most existing

applicationsarxiv-cs-cv

Hardware

Wan-Streamer v0.2: Higher Resolution, Same Latency

arXiv:2607.04443v1 Announce Type: cross Abstract: We present Wan-Streamer v0.2, a latency-preserving upgrade of the native-streaming, end-to-end audio-visual interaction model. v0.2 keeps the v0.1 mod

hardwarearxiv-cs-ai

Wasserstein Residuals: Learning Gradient Flows from Population Dynamics

arXiv:2607.04738v1 Announce Type: cross Abstract: Reconstructing population dynamics is a central problem in the physical and data sciences. Often, the dynamics are modeled as a Wasserstein gradient f

Wavelet Scattering Transform for Interpretable Schizophrenia Biomarker Discovery and Classification from Resting-State EEG

arXiv:2607.05282v1 Announce Type: cross Abstract: Schizophrenia is a debilitating neuropsychiatric disorder characterized by profound cortical network dysregulation, for which objective, clinically tr

Weak-to-Strong Generalization via Direct On-Policy Distillation

arXiv:2607.05394v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) is a powerful recipe for improving language-model reasoning, but it is expensive to repeat on ev

Weakly Guided and Autoregressive Beamformer Parameterization for Generalizable Moving Speaker Extraction in Higher-Order Ambisonics

arXiv:2607.04471v1 Announce Type: cross Abstract: Linear spatial filters (beamformers) enable robust, generalizable and interpretable speech enhancement with performance guarantees under ideal paramet

Weave: Verified Netlist-to-Schematic Conversion via Layered Graph Layout

arXiv:2607.03835v1 Announce Type: cross Abstract: Converting a SPICE netlist into a human-readable schematic is a longstanding problem in electronic design automation: simulators and machine-learning

Agents

Web-CogReasoner: Towards Multimodal Knowledge-Induced Cognitive Reasoning for Web Agents

arXiv:2508.01858v3 Announce Type: replace-cross Abstract: Multimodal large-scale models have significantly advanced the development of web agents, enabling perception and interaction with digital envi

agentsarxiv-cs-ai

WeightCLIP: Aligning Datasets and Models for Weight Space Learning

arXiv:2607.03551v1 Announce Type: new Abstract: Weight space learning aims to learn representations of neural network (NN) weights, enabling different downstream tasks. Existing approaches show promis

tutorialsarxiv-cs-lg

Weighted Conformal Prediction for Lab-to-Track Thermal Transfer in EV Motorsport Powertrains

arXiv:2607.02722v1 Announce Type: new Abstract: Predicting thermal volatility in high-performance EV powertrains is difficult as internal temperatures are rarely observable outside the lab, and models

What Does a Discrete Diffusion Model Learn?

arXiv:2607.05381v1 Announce Type: cross Abstract: What does a discrete diffusion model learn: a denoiser, a score ratio, or a bridge plug-in predictor? At the level of jump rates, these are one object

tutorialsarxiv-cs-ai

What is Left for Us? Second Scholarship Against the Degradation of Research by AI

arXiv:2607.04049v1 Announce Type: new Abstract: We argue that generative AI can degrade research by eroding the very practices through which scholarly judgement is formed and academic trust is built.

applicationsarxiv-cs-ai