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Causely: A Causal Intelligence Layer for Enterprise AI A Benchmark Study on SRE and Reliability Workflows

arXiv:2605.18327v1 Announce Type: new Abstract: AI agents deployed into SRE workflows currently derive their understanding of environment state from raw observability telemetry at query time, paying a

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CAVE: A Structured Credit Assignment Approach for Fragmented Visual Evidence Reasoning

DGX agent

arXiv:2605.16416v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) have achieved strong performance on general multimodal reasoning, yet remain challenged in integrating nonlocal visual i

tutorialsarxiv-cs-ai

19 May 2026

CayleyPy RL: Pathfinding and Reinforcement Learning on Cayley Graphs

model-releasesarxiv-cs-lg

arXiv:2502.18663v3 Announce Type: replace Abstract: This paper is the second in a series of studies on developing efficient artificial intelligence-based approaches to pathfinding on extremely large g

CBT-Audio: Evaluating Audio Language Models for Patient-Side Distress Intensity Estimation in CBT Session Recordings

arXiv:2605.17370v1 Announce Type: new Abstract: Cognitive behavioural therapy is widely used to help patients understand and manage psychological distress. It is often delivered through spoken convers

tutorialsarxiv-cs-ai

Hardware

Charon: A Unified and Fine-Grained Simulator for Large-Scale LLM Training and Inference

arXiv:2605.17164v1 Announce Type: cross Abstract: Deploying large-scale LLM training and inference with optimal performance is exceptionally challenging due to a complex design space of parallelism st

hardwarearxiv-cs-ai

ChartDesign: Towards LLM Designer of Data Visualization

arXiv:2605.16274v1 Announce Type: cross Abstract: Charts are the dominant medium for visualizing data, discovering patterns and trends, and communicating data driven insights, yet designing them still

CheckSupport: A Local LLM-Powered Tool for Automated Manuscript Submission Checklist Selection and Completion

arXiv:2605.16377v1 Announce Type: cross Abstract: Transparent and standardized reporting is essential for reproducible scientific research, yet adherence to reporting guidelines remains inconsistent b

local-aiarxiv-cs-ai

ChemVA: Advancing Large Language Models on Chemical Reaction Diagrams Understanding

arXiv:2605.17214v1 Announce Type: new Abstract: While Large Language Models (LLMs) have revolutionized scientific text processing, they exhibit a significant capability gap when interpreting chemical

CHI-Bench: Can AI Agents Automate End-to-End, Long-Horizon, Policy-Rich Healthcare Workflows?

arXiv:2605.16679v1 Announce Type: cross Abstract: End-to-end automation of realistic healthcare operations stresses three capabilities underrepresented in current benchmarks: policy density, decisions

ChronoSC: Task-Oriented Semantic Communication via Temporal-to-Color Encoding

arXiv:2605.16388v1 Announce Type: new Abstract: Semantic communication (SC) aims to reduce transmission overhead by conveying task-relevant information rather than raw data. However, existing SC appro

Applications

CineMatte: Background Matting for Virtual Production and Beyond

arXiv:2605.18328v1 Announce Type: new Abstract: LED Virtual Production (VP) uses large LED volumes to render backgrounds in real time, enabling in-camera visual effects but making post-shot changes la

applicationsarxiv-cs-cv

ClaHF: A Human Feedback-inspired Reinforcement Learning Framework for Improving Classification Tasks

arXiv:2605.17458v1 Announce Type: new Abstract: Text classification models are typically trained via supervised fine-tuning (SFT). However, SFT essentially performs behavior cloning from instance-wise

safetyarxiv-cs-lg

CLAP: Contrastive Latent-space Prompt Optimization for End-to-end Autonomous Driving

arXiv:2605.17284v1 Announce Type: cross Abstract: End-to-end autonomous driving systems powered by Vision-Language-Action (VLA) models achieve strong performance on common driving scenarios, yet remai

ClawArena: Benchmarking AI Agents in Evolving Information Environments

arXiv:2604.04202v2 Announce Type: replace-cross Abstract: AI agents deployed as persistent assistants must maintain correct beliefs as their information environment evolves. In practice, evidence is s

CLEAR-HPV: Interpretable Concept Discovery for HPV-Associated Morphology in Whole-Slide Histologyhttps://arxiv.org/submit/7596892/preview

arXiv:2602.05126v2 Announce Type: replace Abstract: Human papillomavirus (HPV) status is a critical determinant of prognosis and treatment response in head and neck and cervical cancers. Although atte

Clipped Gradient Methods for Nonsmooth Convex Optimization under Heavy-Tailed Noise: A Refined Analysis

arXiv:2512.23178v3 Announce Type: replace-cross Abstract: Optimization under heavy-tailed noise has become popular recently, since it better fits many modern machine learning tasks, as captured by emp

researcharxiv-cs-lg

Closing the Gap at CRAC 2026: Two-Stage Adaptation for LLM-Based Multilingual Coreference Resolution

model-releasesarxiv-cs-cl

arXiv:2605.16984v1 Announce Type: new Abstract: We present our submission to the LLM track of the 2026 Computational Models of Reference, Anaphora and Coreference (CRAC 2026) shared task. With an aver

CMAG: Concept-Scaffolded Retrieval for Marketplace Avatar Generation

arXiv:2605.18680v1 Announce Type: new Abstract: Metaverse platforms rely on creator-driven marketplaces where avatars are assembled from discrete, taxonomy-labeled 3D assets (e.g., tops, bottoms, shoe

local-aiarxiv-cs-cv

Coarse Semantic Injection for LLM-Conditioned Structured Indoor Prediction

arXiv:2605.16832v1 Announce Type: new Abstract: Large language models (LLMs) have recently been used as structured decoders for indoor understanding from 3D point-token inputs. However, point cloud en

Code as Agent Harness

arXiv:2605.18747v1 Announce Type: cross Abstract: Recent large language models (LLMs) have demonstrated strong capabilities in understanding and generating code, from competitive programming to reposi

Code-as-Room: Generating 3D Rooms from Top-Down View Images via Agentic Code Synthesis

model-releasesarxiv-cs-cv

arXiv:2605.18451v1 Announce Type: new Abstract: Designing realistic and functional 3D indoor rooms is essential for a wide range of applications, including interior design, virtual reality, gaming, an

CodeBind: Decoupled Representation Learning for Multimodal Alignment with Unified Compositional Codebook

arXiv:2605.18257v1 Announce Type: cross Abstract: Multimodal representation alignment is pivotal for large language models and robotics. Traditional methods are often hindered by cross-modal informati

CodeScaler: Scaling Code LLM Training and Test-Time Inference via Reward Models

arXiv:2602.17684v2 Announce Type: replace-cross Abstract: Reinforcement Learning from Verifiable Rewards (RLVR) has driven recent progress in code large language models by leveraging execution-based f

CogBlender: Towards Continuous Cognitive Intervention in Text-to-Image Generation

arXiv:2603.09286v2 Announce Type: replace Abstract: Beyond conveying semantic information, images also possess cognitive properties that elicit specific psychological responses from viewers, such as m

Collaborative Learning for Semi-Supervised LiDAR Semantic Segmentation

arXiv:2605.17135v1 Announce Type: new Abstract: Annotating large-scale LiDAR point clouds for 3D semantic segmentation is costly and time-consuming, which motivates the use of semi-supervised learning

safetyarxiv-cs-cv

Collision-Resistant Single-Pass Method for Unsupervised Fine-Grained Image Hashing

arXiv:2605.18288v1 Announce Type: new Abstract: Unsupervised fine-grained image hashing aims to learn compact binary codes that preserve subtle visual differences among highly similar instances withou

tutorialsarxiv-cs-cv

CoLLM-NAS: Collaborative Large Language Models for Efficient Knowledge-Guided Neural Architecture Search

arXiv:2509.26037v2 Announce Type: replace Abstract: The integration of Large Language Models (LLMs) with Neural Architecture Search (NAS) has introduced new possibilities for automating the design of

tutorialsarxiv-cs-ai

Color as the Impetus: Transforming Few-Shot Learner

arXiv:2507.22136v3 Announce Type: replace Abstract: Humans possess innate meta-learning capabilities, partly attributable to their exceptional color perception. In this paper, we pioneer an innovative

COLSON: Controllable Learning-Based Social Navigation via Diffusion-Based Reinforcement Learning

arXiv:2503.13934v2 Announce Type: replace-cross Abstract: Mobile robot navigation in dynamic environments with pedestrian traffic is a key challenge in the development of autonomous mobile service rob

CommitDistill: A Lightweight Knowledge-Centric Memory Layer for Software Repositories

arXiv:2605.18284v1 Announce Type: cross Abstract: Software repositories accumulate large amounts of unstructured knowledge in commit messages, pull-request discussions, and issue threads, but develope

CompactAttention: Accelerating Chunked Prefill with Block-Union KV Selection

model-releasesarxiv-cs-cl

arXiv:2605.16839v1 Announce Type: new Abstract: Chunked prefill has become a widely adopted serving strategy for long-context large language models, but efficient attention computation in this regime

Agents

Compass: SLO-aware Query Planner for Compound AI Serving at Scale

arXiv:2504.16397v2 Announce Type: replace-cross Abstract: The rise of compound AI serving that integrates multiple operators in a pipeline enables end-user applications such as generative AI-powered m

agentsarxiv-cs-lg

CompassAD: Intent-Driven 3D Affordance Grounding in Functionally Competing Objects

model-releasesarxiv-cs-cv

arXiv:2604.02060v2 Announce Type: replace Abstract: When told to 'cut the cake,' a robot must choose the knife over nearby scissors, despite both objects affording the same cutting function. In real-w

Compositional Adversarial Training for Robust Visual Watermarking

arXiv:2605.16720v1 Announce Type: new Abstract: Robust watermarking is typically trained with random post-processing augmentation, but random sampling under-covers the combinatorial space of realistic

Compounding Disadvantage: Auditing Intersectional Bias in LLM-Generated Explanations Across Indian and American STEM Education

model-releasesarxiv-cs-cl

arXiv:2601.14506v3 Announce Type: replace-cross Abstract: Large language models are increasingly deployed in STEM education for personalized instruction and feedback across institutions in high- and l

Compress the Context, Keep the Commitments: A Formal Framework for Verifiable LLM Context Compression

arXiv:2605.17304v1 Announce Type: cross Abstract: LLM context is not just tokens; it is a set of commitments. Long-running conversations accumulate goals, constraints, decisions, preferences, tool res

safetyarxiv-cs-cl

Computational Challenges in Token Economics: Bridging Economic Theory and AI System Design

arXiv:2605.17410v1 Announce Type: new Abstract: Token economics has emerged as a useful lens for understanding resource allocation, value creation, and pricing in large language model systems. While r

Concepts Worth Having: Refining VLM-Guided Concept Bottleneck Models with Minimal Annotations

arXiv:2605.16405v1 Announce Type: new Abstract: Concept-bottleneck models (CBMs) are neural classifiers that compute predictions from high-level concepts extracted from the input. CBMs ensure stakehol

Concise and Logically Consistent Conformal Sets for Neuro-Symbolic Concept-Based Models

arXiv:2605.18202v1 Announce Type: cross Abstract: Neuro-Symbolic Concept-based Models (NeSy-CBMs) are a family of architectures that integrate neural networks with symbolic reasoning for enhanced reli

Confidence-Gated Robot Autonomy: When Does Uncertainty Actually Help?

arXiv:2605.18045v1 Announce Type: cross Abstract: Robotic systems often use predictive uncertainty to decide whether to act autonomously or defer to a fallback policy. In threshold-gated autonomy, unc

Confidence Geometry Reveals Trace-Level Correctness in Large Language Model Reasoning

arXiv:2605.16824v1 Announce Type: cross Abstract: Large language models (LLMs) generate not only reasoning text, but also token-level confidence trajectories that record how uncertainty evolves during

researcharxiv-cs-cl

ConflictRAG: Detecting and Resolving Knowledge Conflicts in Retrieval Augmented Generation

arXiv:2605.17301v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) systems implicitly assume mutual consistency among retrieved documents -- an assumption that frequently fails in

Consent Chain Degradation in Embodied Multi-Agent Systems: Bridging the Gap Between AI Agent Governance and Robot Ethics

arXiv:2605.16300v1 Announce Type: cross Abstract: Robotic systems are moving from isolated platforms to interconnected multi-agent ecosystems that operate in human environments. This shift raises a go

Conservative AI for Safety-Sensitive Medical Image Restoration: Residual-Bounded CT-CTA Enhancement for Intracranial Aneurysm-Relevant Signal Recovery

arXiv:2605.16458v1 Announce Type: cross Abstract: Image restoration models are increasingly applied to degraded medical scans, but in safety-sensitive settings they must improve image quality without

local-aiarxiv-cs-ai

Consistency of Learned Sparse Grid Quadrature Rules using NeuralODEs

arXiv:2507.01533v2 Announce Type: replace-cross Abstract: We prove consistency of a recently proposed scheme that evaluates expected values by composing a learned transport map with Clenshaw--Curtis s

tutorialsarxiv-cs-lg

Constrained Code Generation with Discrete Diffusion

arXiv:2605.16829v1 Announce Type: new Abstract: Discrete diffusion models are a powerful, emerging paradigm for code generation. They construct programs through iterative refinement of partially corru

local-aiarxiv-cs-cl

Constrained Policy Optimization via Sampling-Based Weight-Space Projection

model-releasesarxiv-cs-lg

arXiv:2512.13788v2 Announce Type: replace Abstract: Safety-critical learning requires policies that improve performance without leaving the safe operating regime. We study constrained policy learning

Content-Style Identification via Differential Independence

arXiv:2605.17827v1 Announce Type: cross Abstract: Generative analysis often models multi-domain observations as nonlinear mixtures of domain-invariant content variables and domain-specific style varia