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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

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Research

Conf-Gen: Conformal Uncertainty Quantification for Generative Models

DGX agent

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

researcharxiv-cs-ai

29 May 2026

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

model-releasesarxiv-cs-cl

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

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

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,

Local Ai

Create in ComfyUI a mini story

local-air-stablediffusion

ComfyUI's Mini Story Generator is a node designed to generate concise and engaging stories based on a given theme. The tool is versatile for creating succinct narratives with minimal user input, stand

CRITIC-R1: Learning Structured Critics for Retrieval-Augmented Generation

arXiv:2605.29886v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) improves knowledge-intensive question answering by incorporating external evidence. However, existing RAG methods

CriticalKV: Optimizing KV Cache Eviction from an Output Perturbation Perspective

model-releasesarxiv-cs-cl

arXiv:2502.03805v2 Announce Type: replace Abstract: Large language models have revolutionized natural language processing but face significant challenges of high storage and runtime costs, due to the

Agents

Croissant Tasks: A Metadata Format for Reproducible Machine Learning Evaluations

arXiv:2605.29786v1 Announce Type: new Abstract: Reproducibility is fundamental to the scientific method, yet remains a critical challenge in machine learning. Contributing factors include underspecifi

agentsarxiv-cs-ai

Cross-Chirality Generalization by Axial Vectors for Hetero-Chiral Protein-Peptide Interaction Design

arXiv:2602.20176v2 Announce Type: replace-cross Abstract: D-peptide binders targeting L-proteins have promising therapeutic potential. Despite rapid advances in machine learning-based target-condition

CrystalXRD-Bench: Benchmarking Vision-Language Models for XRD Peak Indexing Across Diverse Crystalline Materials

arXiv:2605.29446v1 Announce Type: new Abstract: Miller-index identification from powder XRD patterns requires capabilities untested by existing multimodal benchmarks: the model must read a narrow peak

Cycle Consistency in Video Object-Centric Learning

arXiv:2605.30211v1 Announce Type: new Abstract: Self-supervised video Object-Centric Learning (OCL) aims to discover distinct objects and associate them across time, whereas self-supervised Multi-Obje

safetyarxiv-cs-cv

Cycle-Space Informed Detection of Autoencoded Blind False Data Injection Attacks on Power Systems

arXiv:2605.28912v1 Announce Type: new Abstract: The rapid growth of AI-driven data centers and large-scale energy storage systems is increasing the reliance of power system operation on real-time meas

DAMEL: Dual-Axis Multi-Expert Learning for Class-Imbalanced Learning

arXiv:2605.30135v1 Announce Type: cross Abstract: Various algorithms have been proposed to address the challenges posed by class-imbalanced learning from real-world data with long-tailed distributions

Data filtering methods for training language models

arXiv:2605.29807v1 Announce Type: cross Abstract: Data quality is a critical factor in the effectiveness of machine learning models. Label errors, present even in widely used benchmarks, introduce noi

Industry

Databricks at SIGMOD 2026

Databricks announced its participation or contributions at SIGMOD 2026, a premier international conference on database systems and management. The blog post likely covers Databricks' research papers,

industrydatabricks

Tools

datasette 1.0a31

Release: datasette 1.0a31 Another significant alpha release, with two new headline features. Datasette now offers users with the necessary permissions the ability to both execute write queries against

toolssimon-willison

DCFO: Density-Based Counterfactuals for Outliers -- Additional Material

arXiv:2512.10659v3 Announce Type: replace Abstract: Outlier detection identifies data points that significantly deviate from the majority of the data distribution. Explaining outliers is crucial for u

Dear Grimes, Appreciate your candor, and I understand that your subjective impression is to believe that there is something there. But a. Th…

applicationsgary-marcus--x

Dear Grimes, Appreciate your candor, and I understand that your subjective impression is to believe that there is something there. But a. That’s the very Eliza illusion I am pointing out. It is possib

Decentralized LLM-Driven Coordination of Acoustic Robots for Contactless Object Manipulation

arXiv:2605.29378v1 Announce Type: new Abstract: Natural language interfaces can simplify interaction with multi-robot systems, especially when non-expert users need to issue high-level commands. Acous

applicationsarxiv-cs-ro

Decoupled Thrust-Axis Attitude Control Using Quaternions for Chandrayaan-3 Lunar Landing Mission

arXiv:2605.29409v1 Announce Type: cross Abstract: Chandrayaan-3 mission achieved a historic milestone with its successful soft landing near the lunar south pole, highlighting the critical role of the

researcharxiv-cs-ro

Deep Adaptive Dimension Reduction for Bayesian Inference in Inverse Problems

model-releasesarxiv-cs-lg

arXiv:2605.29373v1 Announce Type: new Abstract: Solving high-dimensional PDE-governed inverse problems is often challenging due to complex non-Gaussian posterior distributions, expensive forward model

Deep Agents v0.6 makes harness profiles a first-class abstraction. Now, you can get production-grade performance from models like @Kimi_Moon…

applicationsharrison-chase--x

Deep Agents v0.6 makes harness profiles a first-class abstraction. Now, you can get production-grade performance from models like @Kimi_Moonshot, @Alibaba_Qwen, and @DeepSeek_ai at 20x+ lower cost tha

Deep Optimal Individualized Treatment Rules for Bivariate Survival Outcomes via Adaptive Prediction-Powered Learning

arXiv:2605.29464v1 Announce Type: cross Abstract: In randomized trials involving multiple treatments, bivariate survival outcomes present significant analytical challenges for making decisions. This p

Tutorials

Deep Psychovisual Image Representations

arXiv:2605.29260v1 Announce Type: new Abstract: Psychovisual models suggest human vision decouples low-level feature extraction from higher cognition by first forming intermediate abstractions. In con

tutorialsarxiv-cs-cv

DeepFake Forensics AI: A Multi-Modal Detection and Blockchain-Anchored Evidence Management Platform

arXiv:2605.29353v1 Announce Type: cross Abstract: The proliferation of AI-generated synthetic media poses a critical threat to the integrity of digital evidence in legal and forensic contexts. Existin

applicationsarxiv-cs-cv

DeepSurvey: Enhancing Analytical Depth and Citation Reliability in Automated Survey Generation

arXiv:2605.29522v1 Announce Type: new Abstract: As scientific literature grows rapidly, automated survey generation has become a key capability for AI scientists and human researchers. However, existi

DeepTool: Scaling Interleaved Deliberation in Tool-Integrated Reasoning via Process-Supervised Reinforcement Learning

arXiv:2605.29568v1 Announce Type: new Abstract: Tool-Integrated Reasoning (TIR) extends LLM capabilities by leveraging external environments. However, existing methods lack the deliberation during seq

DefSynUS: Real-time Patient-specific Intrahepatic Vessel Identification via Deformation-Aware CT-US Domain Adaptation

arXiv:2605.29570v1 Announce Type: new Abstract: Purpose: Laparoscopic ultrasound (LUS) enhances the safety of liver surgery by visualizing intrahepatic vessels in real-time. Still, vessel identificati

safetyarxiv-cs-cv

Deja View: Looping Transformers for Multi-View 3D Reconstruction

arXiv:2605.30215v1 Announce Type: new Abstract: Recent feed-forward 3D reconstruction transformers have scaled to over a billion parameters, following the broader trend of increasing model capacity in

safetyarxiv-cs-cv

Industry

Dell stock closed up 32.81%, its best day ever, after reporting its fastest pace of revenue growth for any period since returning to the public market in 2018 (CJ Haddad/CNBC)

CJ Haddad / CNBC: Dell stock closed up 32.81%, its best day ever, after reporting its fastest pace of revenue growth for any period since returning to the public market in 2018 — Shares of Dell Techno

industrytechmeme

Hardware

DELOS: Detecting Shallow Transits in Kepler Photometry Using a Contrastive-Learning Framework

arXiv:2605.29428v1 Announce Type: cross Abstract: We present DEtection in phase-folded Light curves with cOntrastive Scoring (DELOS), a contrastive-learning-based framework designed to search for shal

hardwarearxiv-cs-ai

Local Ai

Demystifying Data Organization for Enhanced LLM Training

arXiv:2605.30334v1 Announce Type: new Abstract: Large Language Models (LLMs) have revolutionized various fields, yet their training efficiency is heavily reliant on effective data curation. While data

local-aiarxiv-cs-ai