All entries

Citation-Closure Retrieval and Per-Rule Attribution for Real-World Regulatory Compliance Question Answering

arXiv:2605.29742v1 Announce Type: new Abstract: Deploying Large Language Models (LLMs) for regulatory compliance demands rigorous traceability via comprehensive citations across multi-tiered authority

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Research

City-Mesh3R: Simulation-Ready City-Scale 3D Mesh Reconstruction from Multi-View Images

DGX agent

arXiv:2605.30310v1 Announce Type: cross Abstract: City-scale 3D surface reconstruction from multiview images for downstream 3D simulation, poses highly challenging problems due to the scale and comple

researcharxiv-cs-ai

29 May 2026

CityGen: Structure-Guided City-Style Synthesis for Cross-City Autonomous Driving

arXiv:2605.29935v1 Announce Type: cross Abstract: Autonomous driving systems are commonly trained and evaluated within limited geographic regions, which hinders their scalability when deployed in new

Local Ai

Classification of non-analyzable word types in web documents to implement an effective Korean e-learning system

arXiv:2605.29638v1 Announce Type: new Abstract: E-learning systems should deliver contents that reflect various phenomena of the language as it is used. In addition to formal Korean, e-learning system

local-aiarxiv-cs-cl

CLUBench: A Clustering Benchmark

model-releasesarxiv-cs-lg

arXiv:2605.29933v1 Announce Type: new Abstract: Clustering is a fundamental problem in data science with a long-standing research history, yielding numerous insightful algorithms. Despite this progres

Cluster-Level Attention-Guided Parallel Decoding for Masked Diffusion Language Models

arXiv:2605.29607v1 Announce Type: new Abstract: Masked diffusion language models (MDLMs) enable parallel decoding by predicting all masked positions at each denoising step, yet existing training-free

Coarse-Grained Boltzmann Generators

arXiv:2602.10637v2 Announce Type: replace Abstract: Sampling equilibrium molecular configurations from the Boltzmann distribution is a longstanding challenge. Boltzmann Generators (BGs) address this b

Code-QA-Bench: Separating Code Reasoning from Documentation Memorization in Repository-Level QA

arXiv:2605.29277v1 Announce Type: cross Abstract: We present Code-QA-Bench, a fully automated framework for synthesizing repository-level code understanding benchmarks that separates genuine code comp

agentsarxiv-cs-ai

CodeEvolve: an open source evolutionary coding agent for algorithmic discovery and optimization

arXiv:2510.14150v5 Announce Type: replace Abstract: We introduce CodeEvolve, an open-source framework that couples large language models with island-based evolutionary search for end-to-end algorithmi

Cognitive Loop of Thought: Reversible Hierarchical Markov Chain for Efficient Mathematical Reasoning

arXiv:2604.06805v2 Announce Type: replace Abstract: Multi-step Chain-of-Thought (CoT) has significantly advanced the mathematical reasoning capabilities of LLMs by leveraging explicit reasoning steps.

researcharxiv-cs-cl

CogniVerse: Revolutionizing Multi-Modal Retrieval-Augmented Generation with Cognitive Reflection and Geometric Reasoning

arXiv:2605.29602v1 Announce Type: new Abstract: Multi-modal Retrieval-Augmented Generation (MMRAG) has emerged as a powerful paradigm for enhancing Multimodal Large Language Models in knowledge-intens

researcharxiv-cs-cv

CoHyDE: Iterative Co-Training of LLM Rewriter & Dense Encoder for Tool Retrieval

arXiv:2605.29271v1 Announce Type: new Abstract: Tool retrieval over large API catalogs is a core bottleneck for LLM agents: user queries arrive in colloquial, often underspecified language, while the

Collaborative Threshold Watermarking

arXiv:2602.10765v2 Announce Type: replace Abstract: In federated learning (FL), K clients jointly train a model without sharing raw data. Because each participant invests data and compute, clients nee

Safety

Colored Noise Diffusion Sampling

arXiv:2605.30332v1 Announce Type: new Abstract: Diffusion models achieve state-of-the-art image synthesis, with their generative trajectories fundamentally exhibiting a spectral bias, resolving low-fr

safetyarxiv-cs-cv

Combating Data Laundering in LLM Training

arXiv:2604.01904v2 Announce Type: replace-cross Abstract: Data rights owners can detect unauthorized data use in large language model (LLM) training by querying with proprietary samples. Often, superi

COMET: Concept Space Dissection of the Modality Gap in Audio-Text Multimodal Contrastive Embeddings

arXiv:2605.29628v1 Announce Type: cross Abstract: Contrastive Language-Audio Pretraining (CLAP) models are widely used for audio understanding and support modality-agnostic condition swapping in many

Comment on 'Spin-1/2 Kagome Heisenberg Antiferromagnet: Machine Learning Discovery of the Spinon Pair-Density-Wave Ground State'

arXiv:2605.28861v1 Announce Type: cross Abstract: A recent article [Phys. Rev. X 15, 011047 (2025)] utilizes group-equivariant convolutional neural networks to study the ground state of the kagome Hei

CommunityFact: A Dynamic, Multilingual, Multi-domain Benchmark for Misinformation Detection in the Wild

arXiv:2605.30241v1 Announce Type: new Abstract: Misinformation verification increasingly occurs in public, fast-moving, and multilingual online settings, where static benchmarks provide an incomplete

Comparative Evaluation of Machine Translation Systems on Images with Text

arXiv:2605.29476v1 Announce Type: new Abstract: This work presents a comparative evaluation of machine translation systems applied to images containing textual information, a task that lies at the int

Safety

Comparative evaluation of photogrammetric reconstruction methods and 3D Gaussian Splatting for road surface roughness analysis

arXiv:2605.29452v1 Announce Type: new Abstract: Image-based 3D reconstruction offers a low-cost alternative to traditional sensor-based techniques for road surface assessment. This study compares four

safetyarxiv-cs-cv

Comparing Post-Hoc Explainable AI Methods for Interpreting Black-Box EEG Models in Depression Detection

arXiv:2605.28977v1 Announce Type: cross Abstract: Recent advances in deep learning have enabled increasingly accurate electroencephalography (EEG)-based classification of Major Depressive Disorder (MD

Compass: Navigating Global Marine Lead Data Integration through Expert-Guided LLM Agent

arXiv:2605.29966v1 Announce Type: new Abstract: Marine lead (Pb) and its isotopes are critical tracers for ocean circulation and anthropogenic pollution, yet in-situ observations remain costly and spa

agentsarxiv-cs-ai

CompilerDream: Learning a Compiler World Model for General Code Optimization

arXiv:2404.16077v4 Announce Type: replace-cross Abstract: Effective code optimization in compilers is crucial for computer and software engineering. The success of these optimizations primarily depend

agentsarxiv-cs-lg

COMPOSE: Composing Future Theorems from Citations and Formal Structure

arXiv:2605.30333v1 Announce Type: new Abstract: A plausible future mathematical claim must satisfy two constraints: it should follow the direction of prior work and respect the formal dependencies tha

Composing Non-Conjugate Factor Graphs with Closed-Form Variational Inference

arXiv:2605.29467v1 Announce Type: cross Abstract: Stacking probabilistic building blocks into deeper architectures typically breaks closed-form inference. We show that closed-form inference can be pre

Computational Modeling of Antibody-Antigen Complexes: PLM-Based and MSA-Based Approaches

arXiv:2605.28886v1 Announce Type: cross Abstract: Antibodies play a central role in the immune response by specifically recognizing and neutralizing antigens, and therapeutic antibodies have become ma

Computationally Efficient Replicable Learning of Parities and Applications

arXiv:2602.09499v2 Announce Type: replace Abstract: We study the computational relationship between replicability (Impagliazzo et al. [STOC `22], Ghazi et al. [NeurIPS `21]) and other stability notion

Compute Allocation in Evolutionary Search: From Depth-Breadth to Multi-Armed Bandits

arXiv:2605.29268v1 Announce Type: cross Abstract: LLM-guided evolutionary search (Evolve systems) has reached state-of-the-art results on mathematical and combinatorial tasks, yet most existing system

CONCAT: Consensus- and Confidence-Driven Ad Hoc Teaming for Efficient LLM-Based Multi-Agent Systems

arXiv:2605.29612v1 Announce Type: cross Abstract: Although large language model (LLM) based multi-agent systems (MAS) show their capability to solve complex tasks and achieve higher performance over s

agentsarxiv-cs-cl

Conf-Gen: Conformal Uncertainty Quantification for Generative Models

arXiv:2605.28920v1 Announce Type: cross Abstract: Conformal prediction (CP) and its extension, conformal risk control (CRC), are established frameworks for quantifying uncertainty in supervised machin

Conformal Certification of Reasoning Trace Prefixes

arXiv:2605.30085v1 Announce Type: new Abstract: Language model reasoning traces are rarely all-or-nothing; they frequently contain valid intermediate steps before a critical error occurs. Existing unc

ConMoE: Expert-Pool Consolidation via Prototype Reassignment for MoE Compression

arXiv:2605.29350v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) language models reduce per-token computation but still require storing and serving all experts, making deployment memory-intens

Connecting Independently Trained Modes via Layer-Wise Connectivity

model-releasesarxiv-cs-lg

arXiv:2505.02604v5 Announce Type: replace Abstract: Empirical studies have shown that continuous low-loss paths can be constructed between independently trained neural network models. This phenomenon,

Constructing efficient channels for ideal observers using the conjugate gradient method

arXiv:2605.29415v1 Announce Type: cross Abstract: Task-based assessment of image quality (IQ) is critically important for the design and optimization of medical imaging systems. Ideal observers, inclu

researcharxiv-cs-cv

Context Distillation as Latent Memory Management

arXiv:2605.28889v1 Announce Type: cross Abstract: Context distillation compresses contextual information into model parameters, yet existing methods often ignore how multiple distilled latent memories

Continuity and Ordinality Matter: Constraining Time Series Tokens for Effective Time Series Analysis with Large Language Models

arXiv:2605.28866v1 Announce Type: cross Abstract: Token-based time series large language models (TS-LLMs) have emerged as a promising direction for time series analysis and reasoning. However, prior s

Contrastive Representation Regularization for Vision-Language-Action Models

model-releasesarxiv-cs-lg

arXiv:2510.01711v3 Announce Type: replace-cross Abstract: Vision-Language-Action (VLA) models have shown strong capabilities in robot manipulation by leveraging rich representations from pre-trained V

Controlling the Risk of Corrupted Contexts for Language Models via Early-Exiting

arXiv:2510.02480v3 Announce Type: replace Abstract: Large language models (LLMs) can be influenced by harmful or irrelevant context, which can significantly harm model performance on downstream tasks.

Convergence Theory for Iterative LLM-Based Neural Architecture Search: A Parametric Cross-Entropy Framework with Closed-Form Proxy Reliability

arXiv:2605.30103v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used as generators in iterative neural architecture search (NAS), yet no formal convergence theory exists

Converted, Not Equivalent: Benchmarking Codebase Conversion via Observational Equivalence

arXiv:2605.29054v1 Announce Type: cross Abstract: Coding agents increasingly act as codebase-scale collaborators that can assist with codebase conversion, but this progress has exposed a critical weak

Convex Basins in Single-Index Model Loss Landscapes: Applications to Robust Recovery under Strong Adversarial Corruption

arXiv:2605.29497v1 Announce Type: new Abstract: We study the problem of robustly learning Gaussian Single Index Models (SIMs) in the presence of heavy-tailed noise and a constant fraction of adversari

Cookie-Bench: Continuous On-screen Key Interaction Evaluation for Web Generation

arXiv:2605.30000v1 Announce Type: new Abstract: Front-end web code has become a core product surface for every frontier LLM release, yet evaluating these interactive applications at development speed

Tutorials

Cooperative Variance Estimation and Bayesian Neural Networks for Disentangling Aleatoric and Epistemic Uncertainties

arXiv:2505.02743v2 Announce Type: replace Abstract: Real-world data contains aleatoric uncertainty - irreducible noise arising from imperfect measurements or from incomplete knowledge about the data g

tutorialsarxiv-cs-lg

CORE-T: COherent REtrieval of Tables for Text-to-SQL

arXiv:2601.13111v2 Announce Type: replace-cross Abstract: Realistic text-to-SQL workflows often require joining multiple tables. As a result, accurately retrieving the relevant set of tables becomes a

CorPipe at CRAC 2026: Empty Nodes and Cross-Lingual Transfer in Multilingual Coreference Resolution

arXiv:2605.30133v1 Announce Type: new Abstract: We introduce CorPipe 26, our winning submission to the CRAC 2026 Shared Task on Multilingual Coreference Resolution. The fifth edition of this shared ta

researcharxiv-cs-cl

CosmicFish-HRM: Adaptive Reasoning via Hierarchical Recurrent Mechanisms in Compact Language Models

arXiv:2605.28919v1 Announce Type: cross Abstract: Large language models have achieved strong reasoning capabilities, though often at the cost of massive parameter counts and expensive inference. In th

Safety

Crafting Desirable Climate Trajectories with RL Explored Socio-Environmental Simulations

arXiv:2410.07287v2 Announce Type: replace-cross Abstract: Climate change poses an existential threat, necessitating effective climate policies to enact impactful change. Decisions in this domain are i

safetyarxiv-cs-ai

CRB-Guided Framework Design and Resource Allocation for Indoor mmWave ISCC Systems

arXiv:2605.29939v1 Announce Type: cross Abstract: Integrated sensing, communication, and computation (ISCC) provides a promising framework for indoor human-centric applications. In these applications,