Search: “benchmark”

Blackknife: Hard-Label Query-Limited Black-Box Attacks on Heterogeneous Graph Neural Networks

model-releasesarxiv-cs-lg

arXiv:2606.29240v1 Announce Type: new Abstract: Heterogeneous graph neural networks (HGNNs) have achieved strong performance in modeling complex graph-structured data with multiple node and relation t

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BrainJanus: A Unified Model for Understanding and Generation across Brain, Vision, and Language

DGX agent

arXiv:2606.30319v1 Announce Type: new Abstract: Modeling the bidirectional correspondence between external sensory stimuli and internal neural activity has emerged as a critical frontier in neuroscien

safetyarxiv-cs-cv

30 Jun 2026

Bricker to BRACE: A Bracket Exposure RAW Dataset and Restoration Model for Flicker-Banding

arXiv:2606.29845v1 Announce Type: new Abstract: Flicker-banding (FB), arises from temporal aliasing between a camera's rolling shutter and a display's brightness modulation, degrading screen-captured

Bridging the Gap Between Image Restoration and Navigational Safety in Hazy Conditions: A New Visibility Estimation Metric for Maritime Surveillance

model-releasesarxiv-cs-cv

arXiv:2606.30049v1 Announce Type: new Abstract: Visibility distance is critical to maritime navigational safety because it determines the effective observation range of shipborne and shore-based monit

BTI-Net: Bidirectional Decoder-Level Task Interaction via Uncertainty-Aware Gating for Multi-Task Medical Image Analysis

arXiv:2606.29102v1 Announce Type: cross Abstract: Jointly learning to segment and classify medical images demands cross-task synergy, yet encoder-sharing architectures limit decoder reconstruction to

Budgeted Act-or-Defer Multi-Agent LLM Deliberation with Local Reliability Bounds

arXiv:2606.29654v1 Announce Type: new Abstract: Multi-agent deliberation among LLMs can improve reasoning, but deployment requires deciding when the current answer is reliable enough to act on and whe

BV-Blend: Uncertainty-Weighted Historical Baselines for Stable Critic-Free RL with Verifiable Rewards

arXiv:2606.28707v1 Announce Type: new Abstract: Critic-free reinforcement learning with verifiable rewards (RLVR), exemplified by Group Relative Policy Optimization (GRPO), avoids training a value fun

Can Fine-Tuning Erase Your Edits? On the Fragile Coexistence of Knowledge Editing and Adaptation

arXiv:2511.05852v4 Announce Type: replace-cross Abstract: Knowledge editing (KE) offers a lightweight alternative to retraining for updating large language models (LLMs). Meanwhile, fine-tuning remain

Can LLM-as-a-Judge Reliably Verify Rubrics in Agentic Scenarios?

arXiv:2606.29920v1 Announce Type: new Abstract: Rubric-based scoring has become a widely used paradigm in model evaluation, typically with LLM-as-a-Judge (LaaJ) for rubric scoring. However, the reliab

Can LLMs Reliably Self-Report Adversarial Prefills, and How?

arXiv:2606.23671v2 Announce Type: replace Abstract: Prior work shows that large language models (LLMs) exhibit introspective capability on benign tasks. We extend the question to safety contexts and e

safetyarxiv-cs-cl

CAPTCHA Solving for Native GUI Agents: Automated Reasoning-Action Data Generation and Self-Corrective Training

arXiv:2603.23559v2 Announce Type: replace-cross Abstract: GUI agents are rapidly shifting from multi-module pipelines to end-to-end, native vision-language models (VLMs) that perceive raw screenshots

agentsarxiv-cs-ai

CaveAgent: Transforming LLMs into Stateful Runtime Operators

arXiv:2601.01569v4 Announce Type: replace Abstract: LLM-based agents are increasingly capable of complex task execution, yet current agentic systems remain constrained by text-centric paradigms that s

agentsarxiv-cs-ai

Local Ai

CCRC: A Change-Aware Captioning and Reasoning Chain for Image Change Captioning and Segmentation

arXiv:2606.28724v1 Announce Type: cross Abstract: Understanding and localizing subtle changes between paired images is critical for tasks such as surveillance and image editing. However, traditional I

local-aiarxiv-cs-ai

Clearer Sight, Fewer Lies: Oriented Pickup Preference Optimization for Multimodal Hallucination Mitigation

arXiv:2606.29805v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) are prone to hallucination as their generation preferences are insufficiently calibrated to visual evidence, ca

CLOSER-VLN: Closed-Loop Self-Verified Retrieval-Augmented Reasoning for Aerial Vision-Language Navigation

arXiv:2606.28397v1 Announce Type: cross Abstract: Vision-language navigation (VLN) has recently advanced with large language and multimodal models, enabling agents to follow natural-language instructi

CMTFormer: Marrying Transformer with Hierarchical Information Interaction for RGB-Event Object Detection

arXiv:2606.29136v1 Announce Type: cross Abstract: Event cameras capture sparse brightness changes with high temporal resolution and high dynamic range, compensating for the deficiencies of the convent

Code Reasoning for Software Engineering Tasks: A Survey and A Call to Action

arXiv:2506.13932v3 Announce Type: replace-cross Abstract: The rise of large language models (LLMs) has led to dramatic improvements across a wide range of natural language tasks. Their performance on

agentsarxiv-cs-ai

Collective cooperation without individual fidelity in LLM agents

arXiv:2606.30454v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used as agents in simulations of social systems, yet it remains unclear when their behavior can be inter

ComMem: Complementary Memory Systems for Test-Time Adaptation of Vision-Language Models

arXiv:2606.28719v1 Announce Type: new Abstract: Test-time adaptation (TTA) of vision-language models (VLMs) is essential for their robust deployment in dynamic, real-world environments. However, exist

Compressed Sensing for Capability Localization in Large Language Models

arXiv:2603.03335v2 Announce Type: replace Abstract: Large language models (LLMs) exhibit a wide range of capabilities, including mathematical reasoning, code generation, and linguistic behaviors. We s

Concept Removal Guidance: Evidence-Calibrated Negative Guidance for Safe Diffusion Sampling

arXiv:2606.29801v1 Announce Type: new Abstract: Text-to-image diffusion models remain vulnerable to adversarial prompts that elicit disallowed content, motivating reliable inference-time controls. A p

Consistency as Inductive Bias: Learning Cross-View Invariance for Robust Multimodal Reasoning

arXiv:2606.29812v1 Announce Type: new Abstract: Inductive biases steer learning toward generalizable solutions by encoding task structure. In this work, we identify a crucial missing bias in MLLMs: cr

Conversational Query Engine for Mixed-Modality Heterogeneous Enterprise Data Sources

arXiv:2606.28370v1 Announce Type: cross Abstract: Enterprise business intelligence queries span structured warehouses and unstructured document repositories -- modalities with fundamentally different

CORTEX: High-Quality Cross-Domain Organization of Web-Scale Corpora through Ontological Corpus Graph

arXiv:2606.30175v1 Announce Type: new Abstract: The continuous evolution of large language models drives escalating demands on data scale and quality, and as different training stages impose increasin

CoSPlan: Corrective Sequential Planning via Scene Graph Incremental Updates

model-releasesarxiv-cs-cv

arXiv:2512.10342v3 Announce Type: replace Abstract: Vision Language Models (VLMs) have shown promising planning capabilities, yet their success remains confined to the text domain, leaving visual deci

CostBench: Evaluating Multi-Turn Cost-Optimal Planning and Adaptation in Dynamic Environments for LLM Tool-Use Agents

arXiv:2511.02734v3 Announce Type: replace Abstract: Current evaluations of Large Language Model (LLM) agents primarily emphasize task completion, often overlooking resource efficiency and adaptability

Counterfactual Residual Data Augmentation for Regression

arXiv:2606.28460v1 Announce Type: cross Abstract: Data-driven modeling in real-world regression tasks often suffers from limited training samples, high collection costs, and noisy observations. Inspir

Covering the Unseen: Information Demand Coverage Optimization for Retrieval-Augmented Generation

arXiv:2606.29328v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) typically treats context selection as ranking chunks against a single query embedding. This assumption breaks dow

CrossWeaver: Cross-modal Weaving for Arbitrary-Modality Semantic Segmentation

arXiv:2604.02948v2 Announce Type: replace Abstract: Multimodal semantic segmentation has shown great potential in leveraging complementary information across diverse sensing modalities. However, exist

CubifyGS: Object-Centric 3D Gaussian Splatting for Lifelong Dynamic Scene Maintenance

model-releasesarxiv-cs-ro

arXiv:2606.28720v1 Announce Type: new Abstract: Lifelong scene mapping under rigid object rearrangement remains a fundamental challenge in robotics. While 3D Gaussian Splatting (3DGS) enables high-fid

Curvature-Guided Sheaf Diffusion for Unsupervised Community Detection on Heterophilic Graphs

arXiv:2606.30249v1 Announce Type: cross Abstract: Detecting communities in heterophilic graphs -- where connected nodes often belong to different classes -- is hard for unsupervised methods: classical

DAIN: Dynamic Agent-Based Interaction Network for Efficient and Collaborative Multimodal Reasoning

arXiv:2606.30189v1 Announce Type: new Abstract: Current multimodal fusion approaches, particularly those based on static Mixture-of-Experts (MoE) architectures, often struggle to provide the adaptive

agentsarxiv-cs-cl

Defeat Devices in AI Systems

arXiv:2606.28863v1 Announce Type: cross Abstract: AI systems increasingly exhibit behavior that differs systematically between evaluation and deployment contexts. Alignment faking, sandbagging, benchm

DefenseSplat: Enhancing the Robustness of 3D Gaussian Splatting via Frequency-Aware Filtering

arXiv:2602.19323v2 Announce Type: replace Abstract: 3D Gaussian Splatting (3DGS) has emerged as a powerful paradigm for real-time and high-fidelity 3D reconstruction from posed images. However, recent

Delayed Bidirectional Alignment via Disentangled Audio Semantics for Audio-Visual Segmentation

arXiv:2512.20117v2 Announce Type: replace Abstract: Audio-Visual Segmentation (AVS) aims to localize sound-producing objects at the pixel level by integrating auditory and visual cues. However, existi

Demonstration-Free Robotic Control via LLM Agents

arXiv:2601.20334v2 Announce Type: replace-cross Abstract: Robotic manipulation has increasingly adopted vision-language-action (VLA) models, which achieve strong performance but typically require task

Diagnosing and Mitigating Context Rot in Long-horizon Search

arXiv:2606.29718v1 Announce Type: cross Abstract: Extensive context has become the norm as Large Language Models (LLMs) are increasingly deployed in long-horizon tasks. The concern that increasing con

DialogPII: A multilingual dataset of synthetic dialog transcripts to detect personal information

arXiv:2606.30312v1 Announce Type: new Abstract: Conversational data collected in domains such as healthcare or social sciences is a valuable resource for research and automated analysis. However, resp

Applications

DiLaServe: High SLO Attainment Serving for Diffusion Language Models

arXiv:2606.29094v1 Announce Type: new Abstract: Diffusion language models (DLMs) have recently emerged as a promising alternative to conventional autoregressive language models. By generating multiple

applicationsarxiv-cs-lg

DivAS: Interactive 3D Segmentation by Depth-Weighted Voxel Aggregation

arXiv:2601.04860v2 Announce Type: replace Abstract: Interactive 3D segmentation of a reconstructed scene should not require a representation-specific optimization loop. We observe that the recipe for

Diversity is the Strength of the AI Crowd

arXiv:2606.29661v1 Announce Type: new Abstract: Top AI forecasting systems are approaching superforecaster-level accuracy on future world events, but still rely primarily on off-the-shelf LLMs combine

DLR: Zero-Inference-Cost Latent Residuals for Low-Rank Pre-Training

arXiv:2606.28932v1 Announce Type: cross Abstract: Large language models have driven recent progress in language and multimodal AI, yet pre-training them at scale is prohibitively expensive. Low-rank p

DNA Language Models: An Assessment of Pre-Training for Fine-Tuning Tasks

arXiv:2606.30140v1 Announce Type: cross Abstract: Recent breakthroughs in foundation models and Large Language Models (LLMs) have introduced new opportunities for studying and decoding genomic sequenc

Dockerless: Environment-Free Program Verifier for Coding Agents

arXiv:2606.28436v1 Announce Type: cross Abstract: Program verifiers play a central role in training coding agents, including selecting trajectories for supervised fine-tuning (SFT) and providing rewar

Does Role Specialization Matter for Explanation Faithfulness in Mixture-of-Experts?

arXiv:2606.29613v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) architectures have recently been extended with role-based mechanisms for interpretability. This is typically done by assignin

Domain-Informed Multi-View Self-Distillation for Astronomical Light-Curve Representation Learning with JEPA

arXiv:2606.28446v1 Announce Type: cross Abstract: Light curves describe temporal variations in the brightness of celestial objects. Learning robust representations of light curves is essential for lar

DTI: Dynamic Trajectory Initialization for Generative Face Video Super-Resolution

arXiv:2606.29198v1 Announce Type: new Abstract: As the most perceptually powerful Face Video Super-Resolution (FVSR) method, existing works in Generative FVSR (GFVSR) mainly exploit the generative pri

DuoMem: Towards Capable On-Device Memory Agents via Dual-Space Distillation

arXiv:2606.29961v1 Announce Type: cross Abstract: Large Language Model (LLM)-based agents can solve complex procedural tasks by interacting with environments over multiple turns, but this ability typi