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CineMesh4D: Personalized 4D Whole Heart Reconstruction from Sparse Cine MRI

arXiv:2605.13994v1 Announce Type: cross Abstract: Accurate 3D+t whole-heart mesh reconstruction from cine MRI is a clinically crucial yet technically challenging task. The difficulty of this task aris

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ClawForge: Generating Executable Interactive Benchmarks for Command-Line Agents

DGX agent

arXiv:2605.14133v1 Announce Type: new Abstract: Interactive agent benchmarks face a tension between scalable construction and realistic workflow evaluation. Hand-authored tasks are expensive to extend

model-releasesarxiv-cs-ai

15 May 2026

ClickRemoval: An Interactive Open-Source Tool for Object Removal in Diffusion Models

arXiv:2605.14461v1 Announce Type: new Abstract: Existing object removal tools often rely on manual masks or text prompts, making precise removal difficult for non-expert users in complex scenes and of

Closing the Gap on the Sample Complexity of 1-Identification

arXiv:2601.15620v2 Announce Type: replace Abstract: The 1-identification problem is a fundamental pure-exploration problem in multi-armed bandits. An agent aims to determine whether there exists an ar

agentsarxiv-cs-lg

CLOVER: Closed-Loop Value Estimation & Ranking for End-to-End Autonomous Driving Planning

arXiv:2605.15120v1 Announce Type: cross Abstract: End-to-end autonomous driving planners are commonly trained by imitating a single logged trajectory, yet evaluated by rule-based planning metrics that

Co-Me: Confidence-Guided Token Merging for Visual Geometric Transformers

arXiv:2511.14751v2 Announce Type: replace Abstract: We propose Confidence-Guided Token Merging (Co-Me), an acceleration mechanism for visual geometric transformers without retraining or finetuning the

COAL: Counterfactual and Observation-Enhanced Alignment Learning for Discriminative Referring Multi-Object Tracking

arXiv:2605.14795v1 Announce Type: new Abstract: Referring Multi-Object Tracking (RMOT) faces a fundamental structural contradiction between the high-discriminability demand and the sparse semantic sup

safetyarxiv-cs-cv

CoCo-InEKF: State Estimation with Learned Contact Covariances in Dynamic, Contact-Rich Scenarios

arXiv:2605.15122v1 Announce Type: cross Abstract: Robust state estimation for highly dynamic motion of legged robots remains challenging, especially in dynamic, contact-rich scenarios. Traditional app

applicationsarxiv-cs-lg

CoCoEdit: Content-Consistent Image Editing via Region Regularized Reinforcement Learning

model-releasesarxiv-cs-cv

arXiv:2602.14068v2 Announce Type: replace Abstract: Image editing has achieved impressive results with the development of large-scale generative models. However, existing models mainly focus on the ed

Coding Agent Is Good As World Simulator

arXiv:2605.14398v1 Announce Type: new Abstract: World models have emerged as a powerful paradigm for building interactive simulation environments, with recent video-based approaches demonstrating impr

Cognitive-Uncertainty Guided Knowledge Distillation for Accurate Classification of Student Misconceptions

arXiv:2605.14752v1 Announce Type: cross Abstract: Accurately identifying student misconceptions is crucial for personalized education but faces three challenges: (1) data scarcity with long-tail distr

Collaborative Yet Personalized Policy Training: Single-Timescale Federated Actor-Critic

arXiv:2605.14423v1 Announce Type: cross Abstract: Despite the popularity of the actor-critic method and the practical needs of collaborative policy training, existing works typically either overlook e

Collider-Bench: Benchmarking AI Agents with Particle Physics Analysis Reproduction

arXiv:2605.13950v1 Announce Type: cross Abstract: Autonomous language-model agents are increasingly evaluated on long-horizon tool-use tasks, but existing benchmarks rarely capture the complexity and

Communication-Efficient Federated Fine-Tuning

model-releasesarxiv-cs-lg

arXiv:2505.04535v3 Announce Type: replace Abstract: Federated Learning (FL) enables the utilization of vast, previously inaccessible data sources. At the same time, pre-trained Language Models (LMs) h

Comparative Evaluation of Machine Learning Approaches for Minority-Class Financial Distress Prediction Under Class Imbalance Constraints

arXiv:2605.14067v1 Announce Type: new Abstract: Financial distress prediction remains a significant challenge in enterprise risk analysis due to the highly imbalanced nature of real-world financial da

applicationsarxiv-cs-lg

Comparing Developer and LLM Biases in Code Evaluation

arXiv:2603.24586v2 Announce Type: replace-cross Abstract: As LLMs are increasingly used as judges in code applications, they should be evaluated in realistic interactive settings that capture partial

safetyarxiv-cs-cl

Complacent, Not Sycophantic: Reframing Large Language Models and Designing AI Literacy for Complacent Machines

arXiv:2605.14544v1 Announce Type: new Abstract: Large language models are often described as sycophantic, in the sense that they appear to flatter users or mirror their beliefs. We argue that this lab

Composable Crystals: Controllable Materials Discovery via Concept Learning

arXiv:2605.14769v1 Announce Type: new Abstract: De novo crystal generation, a central task in materials discovery, aims to generate crystals that are simultaneously valid, stable, unique, and novel. E

local-aiarxiv-cs-lg

Compositional Sparsity as an Inductive Bias for Neural Architecture Design

arXiv:2605.14764v1 Announce Type: cross Abstract: Identifying the structural priors that enable Deep Neural Networks (DNNs) to overcome the curse of dimensionality is a fundamental challenge in machin

Compositional Video Generation via Inference-Time Guidance

arXiv:2605.14988v1 Announce Type: new Abstract: Text-to-video diffusion models generate realistic videos, but often fail on prompts requiring fine-grained compositional understanding, such as relation

Computational Imaging Priors for Wireless Capsule Endoscopy: Monte Carlo-Guided Hemoglobin Mapping for Rare-Anomaly Detection

arXiv:2605.15062v1 Announce Type: new Abstract: Background. RGB-trained capsule-endoscopy classifiers underperform on small-vessel vascular findings by conflating hemoglobin contrast with bile and ill

Concurrency without Model Changes: Future-based Asynchronous Function Calling for LLMs

arXiv:2605.15077v1 Announce Type: cross Abstract: Function calling, also known as tool use, is a core capability of modern LLM agents but is typically constrained by synchronous execution semantics. U

Conditional Attribute Estimation with Autoregressive Sequence Models

arXiv:2605.14004v1 Announce Type: new Abstract: Generative models are often trained with a next-token prediction objective, yet many downstream applications require the ability to estimate or control

local-aiarxiv-cs-ai

Confidence Estimation for LLMs in Multi-turn Interactions

arXiv:2601.02179v2 Announce Type: replace Abstract: While confidence estimation is a promising direction for mitigating hallucinations in Large Language Models (LLMs), current research overwhelmingly

researcharxiv-cs-cl

Conformal Prediction for Multimodal Regression

arXiv:2410.19653v3 Announce Type: replace Abstract: This paper introduces multimodal conformal regression. Traditionally confined to scenarios with solely numerical input features, conformal predictio

researcharxiv-cs-lg

Conformal Thinking: Risk Control for Reasoning on a Compute Budget

arXiv:2602.03814v2 Announce Type: replace Abstract: Reasoning Large Language Models (LLMs) enable test-time scaling, with dataset-level accuracy improving as the token budget increases, motivating ada

Consciousness as Uncommon Self-Knowledge: A Synergistic Information Framework

arXiv:2605.13884v1 Announce Type: cross Abstract: We propose uncommon self-knowledge (USK) as a candidate criterion for consciousness: synergistic information a system carries about itself that exists

Contestable Multi-Agent Debate with Arena-based Argumentative Computation for Multimedia Verification

arXiv:2605.14495v1 Announce Type: cross Abstract: Multimedia verification requires not only accurate conclusions but also transparent and contestable reasoning. We propose a contestable multi-agent fr

ContextFlow: Context-Aware Flow Matching For Trajectory Inference From Spatial Omics Data

arXiv:2510.02952v3 Announce Type: replace Abstract: Inferring trajectories from longitudinal spatially-resolved omics data is fundamental to understanding the dynamics of structural and functional tis

local-aiarxiv-cs-lg

Contrastive Multi-Modal Hypergraph Reasoning for 3D Crowd Mesh Recovery

arXiv:2605.13854v1 Announce Type: new Abstract: Multi-person 3D reconstruction is pivotal for real-world interaction analysis, yet remains challenging due to severe occlusions and depth ambiguity. Cur

applicationsarxiv-cs-cv

Conversion of Lexicon-Grammar tables to LMF. Application to French

arXiv:2605.14816v1 Announce Type: new Abstract: We describe the first experiment of conversion of Lexicon-Grammar tables for French verbs into the Lexical Markup Framework (LMF) format. The Lexicon-Gr

researcharxiv-cs-cl

CoralLite: {mu}CT Reconstruction of Coral Colonies from Individual Corallites

arXiv:2605.15093v1 Announce Type: new Abstract: The life history of an individual coral is archived within the accreting skeleton of the colony. While reef-forming coral colonies (e.g. massive Porites

CoRDS: Coreset-based Representative and Diverse Selection for Streaming Video Understanding

arXiv:2605.14310v1 Announce Type: new Abstract: Streaming video understanding with large vision-language models (VLMs) requires a compact memory that can support future reasoning over an ever-growing

CoReDiT: Spatial Coherence-Guided Token Pruning and Reconstruction for Efficient Diffusion Transformers

arXiv:2605.14191v1 Announce Type: new Abstract: Diffusion Transformers (DiTs) deliver remarkable image and video generation quality but incur high computational cost, limiting scalability and on-devic

local-aiarxiv-cs-cv

COREKG: Coreset-Guided Personalized Summarization of Knowledge Graphs

arXiv:2605.14900v1 Announce Type: new Abstract: Knowledge Graphs (KGs) are extensively used across different domains and in several applications. Often, these KGs are very large in size. Such KGs beco

Correctness-Aware Repository Filtering Under Maximum Effective Context Window Constraints

arXiv:2605.14362v1 Announce Type: cross Abstract: Context window efficiency is a practical constraint in large language model (LLM)-based developer tools. Paulsen [12] shows that all tested models deg

COTCAgent: Preventive Consultation via Probabilistic Chain-of-Thought Completion

arXiv:2605.15016v1 Announce Type: cross Abstract: As large language models empower healthcare, intelligent clinical decision support has developed rapidly. Longitudinal electronic health records (EHR)

CounselBench: A Large-Scale Expert Evaluation and Adversarial Benchmarking of Large Language Models in Mental Health Question Answering

model-releasesarxiv-cs-cl

arXiv:2506.08584v4 Announce Type: replace Abstract: Medical question answering (QA) benchmarks often focus on multiple-choice or fact-based tasks, leaving open-ended answers to real patient questions

Covariance-aware sampling for Diffusion Models

arXiv:2605.13910v1 Announce Type: cross Abstract: We present a covariance-aware sampler that improves the quality of pixel-space Diffusion Model (DM) sampling in the few-step regime. We hypothesize th

CRANE: Constrained Reasoning Injection for Code Agents via Nullspace Editing

arXiv:2605.14084v1 Announce Type: cross Abstract: Code agents must both reason over long-horizon repository state and obey strict tool-use protocols. In paired Instruct/Thinking checkpoints, these cap

CreFlow: Corrective Reflow for Sparse-Reward Embodied Video Diffusion RL

arXiv:2605.14274v1 Announce Type: new Abstract: Video generation models trained on heterogeneous data with likelihood-surrogate objectives can produce visually plausible rollouts that violate physical

Critic-Driven Voronoi-Quantization for Distilling Deep RL Policies to Explainable Models

arXiv:2605.14897v1 Announce Type: cross Abstract: Despite many successful attempts at explaining Deep Reinforcement Learning policies using distillation, it remains difficult to balance the performanc

Critical Challenges and Guidelines in Evaluating Synthetic Tabular Data: A Systematic Review

arXiv:2504.18544v3 Announce Type: replace-cross Abstract: Generating synthetic tabular health data is challenging, and evaluating their quality is equally, if not more, complex. This systematic review

Croissant Baker: Metadata Generation for Discoverable, Governable, and Reusable ML Datasets

arXiv:2605.15079v1 Announce Type: new Abstract: Croissant has emerged as the metadata standard for machine learning datasets, providing a structured, JSON-LD-based format that makes dataset discovery,

researcharxiv-cs-lg

Cross-Domain Few-Shot Segmentation via Ordinary Differential Equations over Time Intervals

arXiv:2509.01299v2 Announce Type: replace Abstract: Cross-domain few-shot segmentation (CD-FSS) aims to segment unseen categories with very limited samples while alleviating the negative effects of do

applicationsarxiv-cs-cv

Cross-Linguistic Transcription and Phonological Representation in the Huitongguanxi Huayiyiyu

arXiv:2605.14480v1 Announce Type: new Abstract: Purpose: This study investigates the transcription principles underlying Huitongguanxi Huayiyiyu (HHY), a series of multilingual glossaries compiled by

researcharxiv-cs-cl

Crys-JEPA: Accelerating Crystal Discovery via Embedding Screening and Generative Refinement

arXiv:2605.14759v1 Announce Type: new Abstract: De novo crystal generation seeks to discover materials that are not merely realistic, but also stable and novel. However, most existing generative model

researcharxiv-cs-lg

CrystalReasoner: Reasoning and RL for Property-Conditioned Crystal Structure Generation

arXiv:2605.14344v1 Announce Type: new Abstract: Generative modeling has emerged as a promising approach for crystal structure discovery. However, existing LLM-based generative models struggle with low