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Chain-of-thought obfuscation learned from output supervision can generalise to unseen tasks

arXiv:2601.23086v2 Announce Type: replace Abstract: Chain-of-thought (CoT) reasoning provides a significant performance uplift to LLMs by enabling planning, exploration, and deliberation of their acti

tutorialsarxiv-cs-ai

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Human DGX agent

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Check Your LLM's Secret Dictionary! Five Lines of Code Reveal What Your LLM Learned (Including What It Shouldn't Have)

DGX agent

arXiv:2605.22005v1 Announce Type: cross Abstract: We show that singular value decomposition of the lm_head} weight matrix of a transformer-based large language model -- requiring only five lines of Py

model-releasesarxiv-cs-cl

22 May 2026

Chinese sensorimotor and embodiment norms for 3,000 lexicalized concepts

arXiv:2605.22616v1 Announce Type: new Abstract: Understanding how conceptual knowledge is grounded in bodily experience, and to what extent machine systems can acquire such knowledge without direct se

ChronoMedKG: A Temporally-Grounded Biomedical Knowledge Graph and Benchmark for Clinical Reasoning

arXiv:2605.22734v1 Announce Type: new Abstract: Biomedical knowledge graphs (KGs) treat disease associations as static facts, but temporal information is crucial for clinical reasoning, e.g., a sympto

Circle-RoPE: Cone-like Decoupled Rotary Positional Embedding for Large Vision-Language Models

arXiv:2505.16416v3 Announce Type: replace Abstract: Rotary Position Embedding (RoPE) is widely adopted in large language models, but when applied to vision-language models (VLMs) it couples text and i

safetyarxiv-cs-cv

Claim-Selective Certification for High-Risk Medical Retrieval-Augmented Generation

arXiv:2605.21949v1 Announce Type: new Abstract: Medical RAG systems in high-risk QA settings are often evaluated through a single answer-or-abstain decision, but mixed evidence may support one claim,

Closed-Loop Sim-to-Real Reinforcement Learning for Deformable Microfiber Shape Control

arXiv:2605.21688v1 Announce Type: new Abstract: Autonomous contact-based micromanipulation is challenging because surface and interfacial interactions at the microscale are difficult to model accurate

safetyarxiv-cs-ro

Agents

COAgents: Multi-Agent Framework to Learn and Navigate Routing Problems Search Space

arXiv:2605.20618v1 Announce Type: new Abstract: Although Vehicle Routing Problems (VRP) are essential to many real-world systems, they remain computationally intractable at scale due to their combinat

agentsarxiv-cs-ai

COCOTree: A Dataset and Benchmark for Open Tree-Structured Visual Decomposition

arXiv:2605.22068v1 Announce Type: new Abstract: We formalize and enable the task of open tree decomposition, which segments an image into hierarchical trees of visual components with unconstrained gra

Code Researcher: Deep Research Agent for Large Systems Code and Commit History

arXiv:2506.11060v2 Announce Type: replace-cross Abstract: Large Language Model (LLM)-based coding agents have shown promising results on coding benchmarks, but their effectiveness on systems code rema

Applications

Codec-Robust Attacks on Audio LLMs

arXiv:2605.20519v1 Announce Type: cross Abstract: Prior attacks on Audio Large Language Models (Audio LLMs) demonstrated that carefully crafted waveform-domain perturbations can force targeted adversa

applicationsarxiv-cs-ai

Cohesion-6K: An Arabic Dataset for Analyzing Social Cohesion and Conflict in Online Discourse

arXiv:2605.22447v1 Announce Type: new Abstract: The study of online discourse has become central to understanding societal polarization. While much research has focused on detecting overt toxicity, th

Comparing LLM and Fine-Tuned Model Performance on NVDRS Circumstance Extraction with Varying Prompt Complexity

arXiv:2605.21845v1 Announce Type: new Abstract: Suicide is a leading cause of death in the United States, and understanding the circumstances that precede it requires extracting structured information

Conceptualizing Embeddings: Sparse Disentanglement for Vision-Language Models

arXiv:2605.22679v1 Announce Type: new Abstract: Vision-language models learn powerful multimodal embeddings, yet their internal semantics remain opaque. While sparse autoencoders (SAEs) can extract in

tutorialsarxiv-cs-cv

ConvNeXt-FD: A Fractal-Based Deep Model for Robust Biomedical Image Segmentation

arXiv:2605.22002v1 Announce Type: new Abstract: Biomedical image segmentation is a critical task in medical diagnosis and treatment planning, enabling precise delineation of anatomical structures and

CoRMA: Contrastive RMA for Contact-Rich Meta-Adaptation

model-releasesarxiv-cs-ro

arXiv:2605.22082v1 Announce Type: new Abstract: We present CoRMA(Contrastive Robotic Motor Adaptation), a context-based meta-adaptation framework that modifies RMA for force-dominant assembly. CoRMA r

CR4T: Rewrite-Based Guardrails for Adolescent LLM Safety

arXiv:2605.21609v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly embedded in adolescent digital environments, mediating information seeking, advice, and emotionally sensit

safetyarxiv-cs-cl

CritiSense: Critical Digital Literacy and Resilience Against Misinformation

arXiv:2603.16672v2 Announce Type: replace-cross Abstract: Misinformation on social media undermines informed decision-making and public trust. Prebunking offers a proactive complement by helping users

Cross-Domain Human Action Recognition from Multiview Motion and Textual Descriptions

arXiv:2605.22697v1 Announce Type: new Abstract: Robustness to domain changes is a key capability for effective deployment of human action recognition systems in real-world scenarios, where action cate

tutorialsarxiv-cs-cv

Cross-Lingual Consensus: Aligning Multilingual Cultural Knowledge via Multilingual Self-Consistency

arXiv:2605.22137v1 Announce Type: new Abstract: Although Large Language Models (LLMs) demonstrate strong capabilities across various tasks, they exhibit significant performance discrepancies across la

CrossVLA: Cross-Paradigm Post-Training and Inference Optimization for Vision-Language-Action Models

arXiv:2605.21854v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have rapidly converged on a small set of architectural patterns: discrete-token autoregression (e.g. OpenVLA) and co

Applications

CryoNet: A Deep Learning Framework for Multi-Modal Debris-Covered Glacier Mapping. A Case Study of the Poiqu Basin, Central Himalaya

arXiv:2605.21527v1 Announce Type: cross Abstract: Glaciers play a critical role as freshwater reserves and indicators of climate change, yet their automatic delineation, especially for debris-covered

applicationsarxiv-cs-cv

CTFExplorer: Evaluating LLM Offensive Agents Through Multi-Target Web CTF Benchmarking

arXiv:2602.08023v3 Announce Type: replace-cross Abstract: Existing benchmarks for LLM-based offensive security agents use isolated, single-target setups with a known vulnerable service and fixed objec

D3Seg: Dependency-Aware Diffusion for Brain Tumor Segmentation with Missing Modalities

arXiv:2605.22249v1 Announce Type: new Abstract: Accurate brain tumor segmentation using multiparametric MRI is critical for effective treatment planning. However, in clinical settings, complete acquis

Declarative Data Services: Structured Agentic Discovery for Composing Data Systems

arXiv:2605.20690v1 Announce Type: new Abstract: Agentic discovery has shown that LLM-driven search can find novel algorithms, designs, and code under benchmark conditions. Translating the paradigm to

Decoupling Ego-Motion from Target Dynamics via Dual-Interval Motion Cues for UAV Detection

arXiv:2605.22605v1 Announce Type: cross Abstract: Object detection from Unmanned Aerial Vehicles (UAVs) is challenged by severe ego-motion, camera jitter, and large scale variations. While modern dete

DecQ: Detail-Condensing Queries for Enhanced Reconstruction and Generation in Representation Autoencoders

arXiv:2605.22777v1 Announce Type: new Abstract: Representation Autoencoders (RAEs) leverage frozen vision foundation models (VFMs) as tokenizer encoders, providing robust high-level representations th

DeepWeb-Bench: A Deep Research Benchmark Demanding Massive Cross-Source Evidence and Long-Horizon Derivation

arXiv:2605.21482v1 Announce Type: new Abstract: Deep research, in which an agent searches the open web, collects evidence, and derives an answer through extended reasoning, is a prominent use case for

DeFacto: Counterfactual Thinking with Images for Enforcing Evidence-Grounded and Faithful Reasoning

arXiv:2509.20912v4 Announce Type: replace Abstract: Recent advances in multimodal language models (MLLMs) have made thinking with images a dominant paradigm for multimodal reasoning. However, existing

DeferMem: Query-Time Evidence Distillation via Reinforcement Learning for Long-Term Memory QA

arXiv:2605.22411v1 Announce Type: new Abstract: Large language model (LLM) agents still struggle with long-term memory question answering, where answer-supporting evidence is often scattered across lo

Applications

Demystifying Transition Matching: When and Why It Can Beat Flow Matching

arXiv:2510.17991v3 Announce Type: replace-cross Abstract: Flow Matching (FM) underpins many state-of-the-art generative models, yet recent results indicate that Transition Matching (TM) can achieve hi

applicationsarxiv-cs-cv

Depth Augmented and FE Free 3D/2D Liver Registration for Laparoscopic Liver AR

arXiv:2602.17517v2 Announce Type: replace Abstract: Augmented reality (AR) guidance in laparoscopic liver surgery requires accurate registration of preoperative 3D models to intraoperative 2D video, b

safetyarxiv-cs-cv

Designing Conversations with the Dead: How People Engage with Generative Ghosts

arXiv:2605.21390v1 Announce Type: cross Abstract: We examine how people experience two choices in the design of generative ghosts, AI systems that are trained on data of the dead: representation, wher

researcharxiv-cs-ai

Detecting Synthetic Political Narratives in Cross-Platform Social Media Discourse

arXiv:2605.21540v1 Announce Type: cross Abstract: The proliferation of large language models has introduced a new paradigm of synthetic political communication in which narratives may be generated, se

Detecting Trojaned DNNs via Spectral Regression Analysis

arXiv:2605.21146v1 Announce Type: cross Abstract: Modern DNNs are repeatedly fine-tuned to incorporate new data and functionality. This evolutionary workflow introduces a security risk when updated da

researcharxiv-cs-ai

Detection of Virus and Small Cell Patches in Foci Images Using Switchable Convolution and Feature Pyramid Networks

arXiv:2605.22290v1 Announce Type: new Abstract: Accurate detection and counting of virus patches in focus-forming unit (FFU) images, also known as foci images, are important for quantifying viral infe

Diagnosis Is Not Prescription: Linguistic Co-Adaptation Explains Patching Hazards in LLM Pipelines

arXiv:2605.21958v1 Announce Type: new Abstract: When a multi-module LLM agent fails, the module most responsible for the failure is not necessarily the best place to intervene. We demonstrate this Dia

safetyarxiv-cs-cl

Agents

Diffusion-guided Generalizable Enhancer for Urban Scene Reconstruction

arXiv:2605.22420v1 Announce Type: new Abstract: Urban scene reconstruction from real-world observations has emerged as a powerful tool for self-driving development and testing. While current neural re

agentsarxiv-cs-cv

Direct content-based retrieval from music scores images

arXiv:2605.22255v1 Announce Type: new Abstract: The digitization of musical scores plays a crucial role in their preservation and accessibility, yet information retrieval still depends mainly on metad

Discovering Implicit Large Language Model Alignment Objectives

arXiv:2602.15338v2 Announce Type: replace-cross Abstract: Large language model (LLM) alignment relies on complex reward signals that often obscure the specific behaviors being incentivized, creating c

safetyarxiv-cs-cl

Dissecting Embodied Abilities in Multimodal Language Models through Skill-level Evaluation and Diagnosis

arXiv:2510.08759v2 Announce Type: replace Abstract: Understanding the capability bottlenecks of embodied multimodal large language models (MLLMs) is crucial for improving embodied agents. However, exi

Distributed Image Compression with Multimodal Side Information at Extremely Low Bitrates

arXiv:2605.22061v1 Announce Type: new Abstract: Distributed Image Compression (DIC) is crucial for multi-view transmission, especially when operating at extremely low bitrates (< 0.1 bpp). Its core ch

safetyarxiv-cs-cv

Agents

Distributed Multi-Coverage for Robot Swarms

arXiv:2605.21686v1 Announce Type: new Abstract: Autonomous drone swarms deployed for surveillance, environmental monitoring, and infrastructure inspection must maintain reliable coverage of critical a

agentsarxiv-cs-ro

Diverge to Induce Prompting: Multi-Rationale Induction for Zero-Shot Reasoning

arXiv:2602.08028v1 Announce Type: cross Abstract: To address the instability of unguided reasoning paths in standard Chain-of-Thought prompting, recent methods guide large language models (LLMs) by fi

tutorialsarxiv-cs-ai

Diverse Yet Consistent: Context-Guided Diffusion with Energy-Based Joint Refinement for Multi-Agent Motion Prediction

arXiv:2605.22017v1 Announce Type: new Abstract: Deepgenerative models havebecomeapromisingapproach for human motion prediction due to their ability to capture multimodal distributions and represent di

Do Factual Recall Mechanisms Carry over from Text to Speech in Multimodal Language Models?

arXiv:2605.22170v1 Announce Type: new Abstract: In recent years, several Speech Language Models (SLMs) that represent speech and written text jointly have been presented. The question then emerges abo

Do Vision Models Encode Object-Level Semantic Relatedness? A Cognitive Psychology-Inspired Benchmark

arXiv:1709.03806v2 Announce Type: replace Abstract: Modern vision models have achieved strong object-recognition performance, yet it remains unclear whether their representations encode object-level s

Does Slightly Mean Somewhat? Measuring Vague Intensity Words in LLM Numeric Actions

arXiv:2605.21827v1 Announce Type: new Abstract: Do language models preserve the ordinal meaning of intensity words when those words must produce numeric actions? I study a researcher-constructed scale