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Are Reasoning Vision-Language Models Robust to Semantic Visual Distractions?

arXiv:2606.08894v1 Announce Type: new Abstract: Reasoning Vision-Language Models (VLMs) achieve strong performance on complex multimodal tasks, but reliable real-world application requires handling vi

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Model Releases

ArtiFact: A Large-Scale Multi-Modal Cultural Heritage Dataset

DGX agent

arXiv:2606.09648v1 Announce Type: cross Abstract: Multi-modal data management has emerged as a central research topic in the database community, spanning data integration, semantic query processing, a

model-releasesarxiv-cs-ai

9 Jun 2026

Artificial Intelligence for Mathematical Reasoning: An Integrated Survey of Language Models, Neuro-symbolic Systems, and Verified Discovery

arXiv:2606.08728v1 Announce Type: new Abstract: Mathematical reasoning has long served as a stringent test of machine intelligence; over the past decade, it has moved from a niche problem within NLP t

ATN3D: Density-Aware LiDAR-Radar Early 3D Object Detection Under Extreme Sparsity

arXiv:2606.09634v1 Announce Type: cross Abstract: 3D object detection is the backbone of perception for automated vehicles (AV) and broader intelligent transportation systems applications. Long-range

Auditable Graph-Guided Root Cause Analysis for Kubernetes Incidents

arXiv:2606.08590v1 Announce Type: cross Abstract: Kubernetes incidents are diagnosed reliably only when a root-cause system's reported gains come from incident evidence rather than scenario-specific s

Auditing Proprietary Alignment in Large Language Models: A Comparative Framework Without a Ground-Truth Standard

arXiv:2606.08381v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly released and deployed through opaque development and deployment pipelines, enabling model providers to i

Automatic Extraction of Structured Information from Brain MRI Reports Using an Open-Weight Large Language Model

arXiv:2606.07721v1 Announce Type: new Abstract: Objectives: Automatic data extraction from free-text radiology reports enables large-scale research, but few studies assessed the performance of large l

AutoMegaKernel: A Statically-Checked Agent Harness for Self-Retargeting Megakernel Synthesis

arXiv:2606.09682v1 Announce Type: new Abstract: AutoMegaKernel (AMK) compiles a HuggingFace Llama-family model into a single persistent cooperative CUDA kernel that runs the whole forward pass in one

AVI-Bench: Toward Human-like Audio-Visual Intelligence of Omni-MLLMs

arXiv:2606.07643v1 Announce Type: cross Abstract: Recent advances in Omni-Multimodal Large Language Models (Omni-MLLMs) have enabled strong integration of vision, audio, and language. However, their a

Bayesian Optimization of a Multi-Product Chemical Reactor Using Composite Models and Partial Physics Knowledge

arXiv:2606.08611v1 Announce Type: cross Abstract: We study data-driven real-time economic optimization of a multi-product chemical reactor when no reliable first-principles model is available beyond a

Bayesian Selective Latent Inference for Wastewater-First Influenza Monitoring

arXiv:2606.09433v1 Announce Type: new Abstract: Wastewater influenza surveillance can reveal community circulation before clinical reporting, but wastewater alone is not a fully identifiable proxy for

Benchmark Datasets for Lead-Lag Forecasting on Social Platforms

arXiv:2511.03877v2 Announce Type: replace Abstract: Social and collaborative platforms emit multivariate time-series traces in which early interactions -- such as views, likes, or downloads -- are fol

Benchmarking Empirical Privacy Protection for Adaptations of Large Language Models

arXiv:2606.09401v1 Announce Type: new Abstract: Recent work has applied differential privacy (DP) to adapt large language models (LLMs) for sensitive applications, offering theoretical guarantees. How

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents

arXiv:2606.08340v1 Announce Type: new Abstract: As language models are increasingly deployed as autonomous agents, they must coordinate with others over long horizons in open-ended interactive tasks.

Benchmarking Vision-Language-Action Models on SO-101: Failure and Recovery Analysis

arXiv:2606.08881v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have demonstrated strong generalization in robotic manipulation, yet existing evaluations are primarily conducted

Beyond Consistency: Preserving Temporal Structure in Zero-Shot Video Editing

arXiv:2606.08780v1 Announce Type: new Abstract: Existing zero-shot video editing methods rely on pre-trained diffusion models, successfully achieving spatial control and basic temporal consistency but

Beyond English benchmarks: clinical llm evaluation in Brazilian Portuguese

arXiv:2606.07853v1 Announce Type: cross Abstract: Large Language Models are transforming the support for clinical decision and their application in real scenarios. Yet, most benchmarks are conducted i

Beyond Goodhart's Law: A Dynamic Benchmark for Evaluating Compliance in Multi-Agent Systems

arXiv:2606.07805v1 Announce Type: new Abstract: The rapid evolution of Large Language Models (LLMs) from passive assistants to autonomous, execution-capable agents has introduced critical operational

Beyond Pass Rate: A Multilingual, Execution-Grounded Evaluation of Open Code LLMs

arXiv:2606.08840v1 Announce Type: new Abstract: Code generation models are typically compared using compact execution benchmarks and aggregate pass rates, but such summaries obscure how performance va

Beyond Pass/Fail: Using Process Mining to Understand How LLMs Resist (and Fail) Red Team Attacks

arXiv:2606.07833v1 Announce Type: cross Abstract: Standard AI red teaming evaluations reduce adversarial campaigns to a single binary outcome, attack success rate (ASR), not taking into account the se

Bidirectional Semantic Complementary Tool Retrieval for Remote Sensing Agents

arXiv:2606.07538v1 Announce Type: cross Abstract: Large language model (LLM)-based agents provide a novel paradigm for the automated processing of remote sensing(RS) data. Their success in complex RS

Bidirectional Small-Granularity Search between Code and Text

arXiv:2606.07519v1 Announce Type: cross Abstract: We introduce the novel task of bidirectional small-granularity search between code and text, where the queries are small snippets of text or code and

BioVid: Autoregressive Video Generation with Biological Behavior Semantic Comprehension

arXiv:2606.08674v1 Announce Type: cross Abstract: Existing video generation frameworks treat sequence duration as an externally prescribed parameter -- fixed frame counts or text prompts -- producing

BLUE: Toward Better Language Use in Efficient Vision-Language-Action Models for Autonomous Driving

arXiv:2606.08684v1 Announce Type: new Abstract: We present BLUE, a minimal method for better language use in vision-language-action (VLA) models for autonomous driving (AD). Through extensive analysis

Bokeh Diffusion: Defocus Blur Control in Text-to-Image Diffusion Models

arXiv:2503.08434v5 Announce Type: replace-cross Abstract: Recent advances in large-scale text-to-image models have revolutionized creative fields by generating visually captivating outputs from textua

Breaking the Bubble: Asynchronous Pipeline Parallel Training with Bounded Weight Inconsistency

arXiv:2606.07881v1 Announce Type: new Abstract: Pipeline parallelism is essential for training large neural networks, but existing schedules trade off throughput, memory, and optimization consistency.

Bridged SBI: Correcting Biased Low-Fidelity Posteriors for Cost-Efficient High-Fidelity Inference

model-releasesarxiv-cs-ro

arXiv:2606.09155v1 Announce Type: new Abstract: Accurate calibration of particle-based simulators is crucial for robotic earthwork simulation, but analytical calibration is challenging due to this tas

BSTabDiff: Block-Subunit Diffusion Priors for High-Dimensional Tabular Data Generation

arXiv:2606.09257v1 Announce Type: cross Abstract: High-Dimensional Low-Sample Size (HDLSS) tabular domains (e.g., omics) are characterized by n ll m, where n = number of samples, and m = number of fea

BUDDY: BUdget-Driven DYnamic Depth Routing for Adaptive Large Language Model Inference

arXiv:2606.09514v1 Announce Type: new Abstract: Large language models (LLMs) incur high inference cost due to their depth and parameter scale. Depth pruning can reduce latency by skipping redundant Tr

C3VD-DEFCOL: A Deformable Colonoscopy Dataset with Time-Resolved 3D Ground Truth and Realistic Appearance

arXiv:2606.07891v1 Announce Type: new Abstract: 3D reconstruction could improve colonoscopy by estimating mucosal coverage and alerting clinicians to missed regions during screening. However, algorith

Calibration of Structured Ignorance Certificates for Diagnosing Unknown Unknowns in Reasoning Models

arXiv:2606.08571v1 Announce Type: cross Abstract: Large language models frequently fail in a characteristic way: rather than acknowledging ignorance, they produce fluent but incorrect answers to quest

CamoSAM2: SAM2-oriented Prompt Auto-Refinement for Video Camouflaged Object Detection

arXiv:2504.00375v2 Announce Type: replace Abstract: The Segment Anything Model 2 (SAM2), a prompt-guided video foundation model, has remarkably performed in video object segmentation, drawing signific

Can Global XAI Methods Reveal Injected Behaviours in LLMs? SHAP vs Rule Extraction vs RuleSHAP

arXiv:2505.11189v3 Announce Type: replace Abstract: Large language models (LLMs) can amplify misinformation, undermining societal goals such as the UN SDGs. We study three documented drivers of misinf

Can we stabilize an inverted pendulum with feedback from a time-of-flight camera?

model-releasesarxiv-cs-ro

arXiv:2606.09237v1 Announce Type: new Abstract: Time-of-flight cameras are popular in robotics for providing direct depth information while being compact, inexpensive, and robust to lighting condition

Can You Trust What You See? Human and AI Detection of Synthetic Legal Evidence

arXiv:2606.07613v1 Announce Type: cross Abstract: Visual evidence has long been treated as a reliable form of legal proof, but advances in artificial intelligence (AI) are undermining that assumption.

CATPO: Critique-Augmented Tree Policy Optimization

arXiv:2606.08346v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) has become a dominant paradigm for improving the reasoning capabilities of large language models

Causal Agent Replay: Counterfactual Attribution for LLM-Agent Failures

arXiv:2606.08275v1 Announce Type: cross Abstract: When an LLM agent fails -- issues a refund it should not have, calls the wrong tool, leaks data -- existing tooling answers what happened (observabili

Causal Longitudinal Prior-Fitted Networks for Counterfactual Outcome Prediction

arXiv:2606.05797v2 Announce Type: replace Abstract: Longitudinal treatment decisions from multivariate time-series data require predicting potential outcomes under future treatment sequences in the pr

Chain of Flow: ECG-Conditioned 4D Cardiac Cine Generation from Patient-Specific Anatomical Anchor

arXiv:2602.22919v2 Announce Type: replace Abstract: Cardiac cine magnetic resonance imaging (MRI) is central to functional cardiac assessment, yet a full current cine sequence may not always be direct

CHIMERA-Bench: A Benchmark Dataset for Epitope-Specific Antibody Design

arXiv:2603.13431v3 Announce Type: replace-cross Abstract: Computational antibody design has seen rapid methodological progress, with dozens of deep generative methods proposed in the past three years,

ChinaHeritaQA: A Culturally-Grounded Visual Question Answering Dataset for World Heritage Sites in China

arXiv:2606.08959v1 Announce Type: new Abstract: We introduce ChinaHeritaQA, a multimodal benchmark dataset for evaluating the cultural reasoning abilities of vision-language models (VLMs) on UNESCO Wo

CHROMA: Detecting AI-Generated Images through Inter-Channel Color-Space Correlations

arXiv:2606.08864v1 Announce Type: new Abstract: The rapid adoption of diffusion and large-scale generative models has made it increasingly challenging to distinguish synthetic imagery from real photog

ChronoPhyBench: Do MLLMs Truly Understand the World or Merely Exploit Language Priors?

arXiv:2606.07962v1 Announce Type: new Abstract: Recent advancements in Multimodal Large Language Models (MLLMs) have demonstrated remarkable proficiency in open-world reasoning and understanding. Howe

CLASP: Language-Driven Robot Skill Selection and Composition using Task-Parameterized Learning

arXiv:2606.08169v1 Announce Type: cross Abstract: Enabling robots to understand and execute tasks from natural language commands while maintaining data efficiency remains challenging. Foundation model

Claude Code-Driving Scenario Mining for the Argoverse 2 Challenge

arXiv:2606.09180v1 Announce Type: new Abstract: We present our submission to the CVPR 2026 Argoverse 2 Scenario Mining Challenge. Our system uses a four-stage pipeline: (1) autonomous code generation

Closing the Sim-to-Real Gap: An Evaluation Framework for Autonomous Cyber Defense Configuration of Commercial EDR

arXiv:2606.08168v1 Announce Type: cross Abstract: Leading commercial endpoint detection and response (EDR) products have shifted from operator-configured rule sets to multi-component systems where aut

Coarse-to-Fine Hierarchical Alignment for UAV-based Human Detection using Diffusion Models

arXiv:2512.13869v3 Announce Type: replace Abstract: Training object detectors demands extensive, task-specific annotations, yet this requirement becomes impractical in UAV-based human detection due to

CodeTaste: Can LLMs Generate Human-Level Code Refactorings?

arXiv:2603.04177v2 Announce Type: replace-cross Abstract: LLM coding agents can generate working code, but their solutions often accumulate complexity, duplication, and architectural debt. Human devel