Search: “models”

Membrane: A Self-Evolving Contrastive Safety Memory for LLM Agent Defense

arXiv:2606.05743v1 Announce Type: cross Abstract: Despite advances in safety alignment, large language models remain vulnerable to continuously evolving jailbreaks. Existing fine-tuned safety classifi

safetyarxiv-cs-cl

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Oklch+: A Three-Parameter Extension of Oklab for Improved Color Difference Prediction

DGX agent

arXiv:2606.05255v1 Announce Type: cross Abstract: Oklab and its cylindrical representation Oklch are widely adopted in interpolation and design workflows as perceptually motivated color spaces, but th

model-releasesarxiv-cs-cv

5 Jun 2026

OLIVE: Online Low-Rank Incremental Learning for Efficient Adaptive Exoskeletons

arXiv:2606.05234v1 Announce Type: new Abstract: Wearable exoskeleton systems hold promise for restoring mobility in individuals with physical impairments, yet most existing controllers rely on static

Operation-Guided Progressive Human-to-AI Text Transformation Benchmark for Multi-Granularity AI-Text Detection

arXiv:2606.06481v1 Announce Type: new Abstract: As AI writing assistants become increasingly integrated into real-world drafting and revision workflows, many documents are no longer purely human-writt

Parallel Jacobi Decoding for Fast Autoregressive Image Generation

arXiv:2606.05703v1 Announce Type: new Abstract: Autoregressive (AR) models have demonstrated remarkable performance in generating high-fidelity images. However, their inherently sequential next-token

researcharxiv-cs-cv

Physics-Guided Deep Unfolding for Blind Cross-Sensor Spectral Super-Resolution via Learning the Spectral Transformation Function

arXiv:2606.05759v1 Announce Type: new Abstract: Hyperspectral imaging provides rich spectral information for quantitative remote sensing, yet hyperspectral sensors remain costly and thus unavailable i

Reinforcement Learning Elicits Contextual Learning of Unseen Language Translation

arXiv:2606.06428v1 Announce Type: new Abstract: Prior work has shown that large language models (LLMs) can translate unseen or low-resource languages by undergoing continued training or even by encodi

ReSAGE-PAR: Representational Similarity Assessment for Generative Expansion in Pedestrian Attribute Recognition

arXiv:2606.06020v1 Announce Type: new Abstract: To address the limited diversity and data scarcity in Pedestrian Attribute Recognition (PAR), we explore image synthesis using diffusion models guided b

safetyarxiv-cs-cv

Tutorials

RhymeFlow: Training-Free Acceleration for Video Generation with Asynchronous Denoising Flow Scheduling

arXiv:2606.06309v1 Announce Type: new Abstract: Video generation models based on Diffusion Transformers (DiTs) have achieved remarkable performance in video synthesis, yet they suffer from high infere

tutorialsarxiv-cs-cv

RQUL-UIE: Revitalizing Quality-Unstable Labels for Underwater Image Enhancement via In-Dataset Self-Supervision

arXiv:2606.06176v1 Announce Type: new Abstract: Underwater Image Enhancement (UIE) is essential for mitigating degradations caused by water medium. Although learning-based methods have advanced signif

researcharxiv-cs-cv

Safe Embodied AI for Long-horizon Tasks: A Cross-layer Analysis of Robotic Manipulation

arXiv:2606.05660v1 Announce Type: new Abstract: Embodied AI systems are increasingly expected to reason and act over extended horizons in physical environments. This growing capability brings safety t

Tutorials

Second-order Gaussian directional derivative representations for image high-resolution corner detection

arXiv:2601.08182v2 Announce Type: replace Abstract: Corner detection is widely used in various computer vision tasks, such as image matching and 3D reconstruction. Our research indicates that there ar

tutorialsarxiv-cs-cv

ShotCrop^3: Cropping Human-Centric Images into Cinematic Triple-Shot Compositions

arXiv:2606.05635v1 Announce Type: new Abstract: Prior work on aesthetic composition typically produces a single aesthetically pleasing crop, overlooking the narrative value of composing multiple shots

Agents

SkillComposer: Learning to Evolve Agent Skills for Specification and Generalization

arXiv:2606.06079v1 Announce Type: new Abstract: Agent skills, which consist of reusable strategies that guide agent reasoning and action, have shown strong potential for improving model capability at

agentsarxiv-cs-cl

SoCRATES: Towards Reliable Automated Evaluation of Proactive LLM Mediation across Domains and Socio-cognitive Variations

arXiv:2606.05563v1 Announce Type: cross Abstract: Evaluating LLM mediators remains challenging, as mediation unfolds as a real-time trajectory shaped by disputants' shifting emotions, intentions, and

Statistically Reliable LLM-Based Ranking Evaluation via Prediction-Powered Inference

arXiv:2606.05308v1 Announce Type: cross Abstract: With PRECISE, we extended Prediction-Powered Inference to produce bias-corrected estimates of ranking evaluation metrics by combining a small human-la

StoryVideoQA: Scaling Deep Video Understanding with a Large-Scale, Multi-Genre and Auto-Generated Dataset

arXiv:2606.06338v1 Announce Type: new Abstract: Video question answering (VideoQA) aims to answer questions about given videos. While existing approaches excel on factoid VideoQA, they struggle with d

SubtleMemory: A Benchmark for Fine-Grained Relational Memory Discrimination in Long-Horizon AI Agents

arXiv:2606.05761v1 Announce Type: cross Abstract: Persistent AI assistants, such as OpenClaw, accumulate large collections of related memories over long-term interactions. As these memories grow, they

TempoVLA: Learning Speed-Controllable Vision-Language-Action Policies

arXiv:2606.06491v1 Announce Type: new Abstract: Robot manipulation alternates between low-risk transit phases that call for fast execution and high-risk contact stages that demand slow, precise motion

safetyarxiv-cs-ro

Three-Dimensional Retinal Microvasculature Restoration in OCT Angiography

arXiv:2606.05375v1 Announce Type: new Abstract: Optical coherence tomographic angiography (OCTA) is a powerful technique for imaging retinal microvasculature. However, acquiring reliable quantificatio

researcharxiv-cs-cv

Towards Accurate Heart Rate Measurement from Ultra-Short Video Clips via Periodicity-Guided rPPG Estimation and Signal Reconstruction

arXiv:2506.22078v2 Announce Type: replace Abstract: Many remote Heart Rate (HR) measurement methods focus on estimating remote photoplethysmography (rPPG) signals from video clips lasting around 10 se

Unifying Dataset Pruning and Distillation for Efficient Large-scale Compression

arXiv:2502.06434v2 Announce Type: replace Abstract: Dataset pruning (DP) and dataset distillation (DD) fundamentally differ in their outputs: DP selects original image subsets, while DD generates synt

UniPixie: Unified and Probabilistic 3D Physics Learning via Flow Matching

arXiv:2606.05399v1 Announce Type: new Abstract: Existing feed-forward networks excel at predicting a single set of physical properties from visual appearance, but this point-estimate paradigm fundamen

Unveiling the Unknown: Open Vocabulary Object Detection with Scene Graphs

arXiv:2606.05916v1 Announce Type: new Abstract: Open-vocabulary object detection seeks to identify novel object categories that were not part of the training data. Many knowledge distillation-based ap

safetyarxiv-cs-cv

Waypoints Matter: A Systematic Study for Sampling-Based Trajectory Planning

arXiv:2606.06366v1 Announce Type: new Abstract: Real-time autonomous driving commonly relies on sampling-based trajectory planners that link candidate trajectories to target waypoints along the road c

You Only Index Once: Cross-Layer Sparse Attention with Shared Routing

arXiv:2606.06467v1 Announce Type: new Abstract: Long-context inference in modern LLMs is increasingly constrained by decoding efficiency, especially in reasoning-heavy settings where models generate l

ANN Search: Recall What Matters

arXiv:2606.04522v1 Announce Type: cross Abstract: Approximate nearest neighbor (ANN) search has become a core primitive in information retrieval and modern machine learning tasks, from classification

AUDDT: A Unified Benchmark Toolkit for Audio and Speech Deepfake Detectors

arXiv:2509.21597v2 Announce Type: replace-cross Abstract: With the prevalence of artificial intelligence (AI)-generated content, such as audio deepfakes, a large body of recent work has focused on dev

Bayesian Membership Privacy for Graph Neural Networks

model-releasesarxiv-cs-lg

arXiv:2606.04069v1 Announce Type: cross Abstract: Existing privacy analyses for Graph Neural Networks (GNNs) largely inherit assumptions from non-graph settings, overlooking structural correlations an

BBOmix: A Tabular Benchmark for Hyperparameter Optimization of Unsupervised Biological Representation Learning

model-releasesarxiv-cs-lg

arXiv:2606.05139v1 Announce Type: new Abstract: The rapid advancement of high-throughput sequencing has led to large, high-dimensional omics datasets. Deep unsupervised learning architectures, particu

Agents

Beyond Correctness: Rewarding Faithful Reasoning in Retrieval-Augmented Generation

arXiv:2510.13272v3 Announce Type: replace Abstract: Inspired by the success of reinforcement learning (RL) in Large Language Model (LLM) training for domains like math and code, recent work has begun

agentsarxiv-cs-cl

BiasGRPO: Stabilizing Bias Mitigation in High-Variance Reward Landscapes via Group-Relative Policy Optimization

arXiv:2606.04807v1 Announce Type: new Abstract: Mitigating social bias in Large Language Models (LLMs) presents a distinct alignment challenge: unlike verifiable tasks, bias lacks a single ground trut

safetyarxiv-cs-ai

BioBlue: Systematic runaway-optimiser-like LLM failure modes on biologically and economically aligned AI safety benchmarks for LLMs with simplified observation format

arXiv:2509.02655v3 Announce Type: replace-cross Abstract: Many AI alignment discussions of 'runaway optimisation' focus on RL agents: unbounded utility maximisers that over-optimise a proxy objective

Boosting Self-Consistency with Ranking

arXiv:2606.05054v1 Announce Type: new Abstract: Self-consistency improves large language models by sampling multiple reasoning paths and selecting the most frequent answer, but majority voting often f

Agents

CADENCE: Predicting Realized MAPF Execution Time Beyond Sum of Costs

arXiv:2606.04746v1 Announce Type: new Abstract: Multi-Agent Path Finding (MAPF) algorithms are increasingly used to plan motion for robot teams in industrial warehouses and robotic shared workspaces,

agentsarxiv-cs-ro

Tutorials

Can Crowdsourcing Survive the LLM Era? A Community Survey on Human Data Collection

arXiv:2606.04924v1 Announce Type: new Abstract: The widespread use of Large Language Models (LLMs) as writing tools challenges the validity of crowdsourced data, as crowdworkers may outsource tasks to

tutorialsarxiv-cs-cl

Certified Neural Approximations of Nonlinear Dynamics

arXiv:2505.15497v3 Announce Type: replace Abstract: Neural networks hold great potential to act as approximate models of nonlinear dynamical systems, with the resulting neural approximations enabling

safetyarxiv-cs-lg

Continual Visual and Verbal Learning Through a Child's Egocentric Input

arXiv:2606.05115v1 Announce Type: cross Abstract: Children learn the meanings of words from a continuous, temporally structured stream of egocentric experience. Recent work shows that neural networks

CoPark: Learning Reactive Parking via Self-Play

arXiv:2606.04149v1 Announce Type: new Abstract: Learning a single policy that reaches a goal with high geometric precision while interacting safely with nearby agents poses conflicting objectives. Pre

Crafting Your Evolving Dreams: Concept-Incremental Versatile Customization

arXiv:2606.04797v1 Announce Type: new Abstract: Custom diffusion models (CDMs) have garnered significant interest owing to their remarkable capacity for generating personalized concepts. However, the

safetyarxiv-cs-cv

Curvature-aware dynamic precision approach for physics-informed neural networks

arXiv:2606.04736v1 Announce Type: cross Abstract: Physics-informed neural networks (PINNs) have become a promising framework for simulating partial differential equations (PDEs) by embedding physical

CyberGym-E2E: Scalable Real-World Benchmark for AI Agents' End-to-End Cybersecurity Capabilities

arXiv:2606.04460v1 Announce Type: cross Abstract: AI has the potential to transform cybersecurity by enabling systems that can autonomously detect, analyze, and remediate software vulnerabilities. How

Disentangling Answer Engine Optimization from Platform Growth: A Log-Based Natural Experiment on ChatGPT Referral Traffic

arXiv:2606.04362v1 Announce Type: cross Abstract: Large language model (LLM) 'answer engines' such as ChatGPT now send measurable referral traffic to the open web, and a practice analogous to search e

DuDi: Dual-Signal Distillation with Cross-Lingual Verbalizer

arXiv:2606.04694v1 Announce Type: new Abstract: Small language models (SLMs) are efficient and scalable, but their multilingual capabilities degrade severely at sub-billion scales, especially for Sout

safetyarxiv-cs-cl

Ekka: Automated Diagnosis of Silent Errors in LLM Inference

arXiv:2606.04594v1 Announce Type: cross Abstract: LLM serving frameworks are quickly evolving with a complex software stack and a vast number of optimizations. The rapid development process can introd

Entity Binding Failures in Speech LLM Reasoning: Diagnosis and Chain-of-Thought Intervention

arXiv:2606.04474v1 Announce Type: new Abstract: Speech Large Language Models (SLLMs) underperform their text counterparts on complex reasoning. We reveal that this modality gap is not a uniform cognit

Exploring the Topology and Memory of Consensus: How LLM Agents Agree, Fragment, or Settle When Forming Conventions

arXiv:2606.04197v1 Announce Type: cross Abstract: How much should an LLM agent remember, and how should multi-agent systems be connected when trying to reach consensus? We show these two design choice

Formal Semantics for Agentic Tool Protocols: A Process Calculus Approach

arXiv:2603.24747v2 Announce Type: replace Abstract: The emergence of large language model agents capable of invoking external tools has created urgent need for formal verification of agent protocols.

safetyarxiv-cs-ai