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Coevolutionary Continuous Discrete Diffusion: Make Your Diffusion Language Model a Latent Reasoner

arXiv:2510.03206v2 Announce Type: replace-cross Abstract: Diffusion language models, especially masked discrete diffusion models, have achieved great success recently. While there are some theoretical

applicationsarxiv-cs-cl

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Combining On-Policy Optimization and Distillation for Long-Context Reasoning in Large Language Models

DGX agent

arXiv:2605.12227v1 Announce Type: new Abstract: Adapting large language models (LLMs) to long-context tasks requires post-training methods that remain accurate and coherent over thousands of tokens. E

safetyarxiv-cs-cl

13 May 2026

Compositional Neural Operators for Multi-Dimensional Fluid Dynamics

arXiv:2605.11691v1 Announce Type: new Abstract: Partial differential equations (PDEs) govern diverse physical phenomena, yet high-fidelity numerical solutions are computationally expensive and Machine

Computational Design of a Low-Visibility UAV Using a Human-Aligned Perceptual Metric

arXiv:2605.11296v1 Announce Type: new Abstract: We introduce Phantom Twist, a type of single-propeller UAV designed to achieve low visibility through high-speed spinning and the exploitation of motion

researcharxiv-cs-ro

Concepts in Motion: Temporal Concept Bottleneck Model for Interpretable Video Classification

arXiv:2509.20899v3 Announce Type: replace Abstract: Concept Bottleneck Models (CBMs) enable interpretable image classification by structuring predictions around human-understandable concepts, but exte

researcharxiv-cs-cv

Concordance Comparison as a Means of Assembling Local Grammars

arXiv:2605.11862v1 Announce Type: new Abstract: Named Entity Recognition for person names is an important but non-trivial task in information extraction. This article uses a tool that compares the con

applicationsarxiv-cs-cl

Constrained Stochastic Spectral Preconditioning Converges for Nonconvex Objectives

arXiv:2605.11850v1 Announce Type: cross Abstract: In this work, we develop proximal preconditioned gradient methods with a focus on spectral gradient methods providing a proximal extension to the Muon

Context Convergence Improves Answering Inferential Questions

arXiv:2605.12370v1 Announce Type: new Abstract: While Large Language Models (LLMs) are widely used in open-domain Question Answering (QA), their ability to handle inferential questions-where answers m

researcharxiv-cs-cl

Context Steering: A New Paradigm for Compression-based Embeddings by Synthesizing Relevant Information Features

arXiv:2508.14780v2 Announce Type: replace Abstract: Compression-based dissimilarities (CD) offer a flexible and domain-agnostic means of measuring similarity by identifying implicit information throug

Continuous Discovery of Vulnerabilities in LLM Serving Systems with Fuzzing

arXiv:2605.11202v1 Announce Type: cross Abstract: LLM inference and serving systems have become security-critical infrastructure; however, many of their most concerning failures arise from the serving

Contrastive Learning under Noisy Temporal Self-Supervision for Colonoscopy Videos

arXiv:2605.12320v1 Announce Type: new Abstract: Learning robust representations of polyp tracklets is key to enabling multiple AI-assisted colonoscopy applications, from polyp characterization to auto

researcharxiv-cs-cv

Agents

Control Charts for Multi-agent Systems

arXiv:2605.11135v1 Announce Type: cross Abstract: Generative agents have proven to be powerful assistants in a wide variety of contexts. Given this success, users are now deploying agents with minimal

agentsarxiv-cs-lg

Control of Fully Actuated Aerial Vehicles: A Comparison of Model-based and Sensor-based Dynamic Inversion

model-releasesarxiv-cs-ro

arXiv:2605.12071v1 Announce Type: new Abstract: Fully actuated multirotor platforms decouple translational force generation from vehicle attitude, enabling independent control of position and orientat

Controllable User Simulation

arXiv:2605.11519v1 Announce Type: cross Abstract: Using offline datasets to evaluate conversational agents often fails to cover rare scenarios or to support testing new policies. This has motivated th

safetyarxiv-cs-cl

Cooperative Robotics Reinforced by Collective Perception for Traffic Moderation

arXiv:2605.11972v1 Announce Type: new Abstract: Collisions at non-line-of-sight (NLOS) intersections remain a major safety concern because drivers have limited visibility of approaching traffic. V2X b

safetyarxiv-cs-ro

Coordinated Diffusion: Generating Multi-Agent Behavior Without Multi-Agent Demonstrations

arXiv:2605.11485v1 Announce Type: new Abstract: Imitation learning powered by generative models has proven effective for modeling complex single-agent behaviors. However, teaching multi-agent systems,

safetyarxiv-cs-ro

CORE: Cyclic Orthotope Relation Embedding for Knowledge Graph Completion

arXiv:2605.11159v1 Announce Type: new Abstract: Knowledge graph completion (KGC) aims to automatically infer missing facts in multi-relational data by mapping entities and relations into continuous re

Correcting Selection Bias in Sparse User Feedback for Large Language Model Quality Estimation: A Multi-Agent Hierarchical Bayesian Approach

arXiv:2605.12177v1 Announce Type: new Abstract: [Abridged] Production LLM deployments receive feedback from a non-random fraction of users: thumbs sit mostly in the tails of the satisfaction distribut

Local Ai

COSMOS: Model-Agnostic Personalized Federated Learning with Clustered Server Models and Pseudo-Label-Only Communication

arXiv:2605.11165v1 Announce Type: new Abstract: Federated learning (FL) in heterogeneous environments remains challenging because client models often differ in both architecture and data distribution.

local-aiarxiv-cs-lg

Couple to Control: Joint Initial Noise Design in Diffusion Models

arXiv:2605.11311v1 Announce Type: cross Abstract: Diffusion models typically generate image batches from independent Gaussian initial noises. We argue that this independence assumption is only one cho

safetyarxiv-cs-cv

Courtroom-Style Multi-Agent Debate with Progressive RAG and Role-Switching for Controversial Claim Verification

arXiv:2603.28488v2 Announce Type: replace Abstract: Large language models (LLMs) remain unreliable for high-stakes claim verification due to hallucinations and shallow reasoning. While retrieval-augme

Covering Human Action Space for Computer Use: Data Synthesis and Benchmark

model-releasesarxiv-cs-cv

arXiv:2605.12501v1 Announce Type: new Abstract: Computer-use agents (CUAs) automate on-screen work, as illustrated by GPT-5.4 and Claude. Yet their reliability on complex, low-frequency interactions i

Crash Assessment via Mesh-Based Graph Neural Networks and Physics-Aware Attention

arXiv:2605.11784v1 Announce Type: cross Abstract: Full-vehicle crash simulations are computationally expensive, limiting their use in iterative design exploration. This work investigates learned hybri

Cross-Modal-Domain Generalization Through Semantically Aligned Discrete Representations

arXiv:2605.12145v1 Announce Type: new Abstract: Multimodal learning seeks to integrate information across diverse sensory sources, yet current approaches struggle to balance cross-modal generalizabili

safetyarxiv-cs-cv

CTFusion: A CTF-based Benchmark for LLM Agent Evaluation

arXiv:2605.11504v1 Announce Type: new Abstract: Recent advances in Large Language Models (LLMs) have enabled agentic systems for complex, multi-step tasks; cybersecurity is emerging as a prominent app

Curriculum Learning-Guided Progressive Distillation in Large Language Models

arXiv:2605.11260v1 Announce Type: new Abstract: Knowledge distillation is a key technique for transferring the capabilities of large language models (LLMs) into smaller, more efficient student models.

DAG: A Dual Correlation Network for Time Series Forecasting with Exogenous Variables

arXiv:2509.14933v3 Announce Type: replace Abstract: Time series forecasting is essential in various domains. Compared to relying solely on endogenous variables (i.e., target variables), considering ex

DarkQA: Benchmarking Vision-Language Models on Visual-Primitive Question Answering in Low-Light Indoor Scenes

model-releasesarxiv-cs-cv

arXiv:2512.24985v4 Announce Type: replace Abstract: Vision Language Models (VLMs) are increasingly adopted as central reasoning modules for embodied agents. Existing benchmarks evaluate their capabili

Debiased Model-based Representations for Sample-efficient Continuous Control

arXiv:2605.11711v1 Announce Type: new Abstract: Model-based representations recently stand out as a promising framework that embeds latent dynamics information into the representations for downstream

Debiasing Message Passing to Mitigate Popularity Bias in GNN-based Collaborative Filtering

arXiv:2605.11145v1 Announce Type: cross Abstract: Collaborative filtering (CF) models based on graph neural networks (GNNs) achieve strong performance in recommender systems by propagating user-item s

Decomposing Evolutionary Mixture-of-LoRA Architectures: The Routing Lever, the Lifecycle Penalty, and a Substrate-Conditional Boundary

arXiv:2605.11153v1 Announce Type: new Abstract: We decompose an evolutionary mixture-of-LoRA system on a from-scratch ~150M-parameter widened-D substrate (D=1536, V=32000; D/V approx 0.048; the 'widen

Decomposing the Generalization Gap in PROTAC Activity Prediction: Variance Attribution and the Inter-Laboratory Ceiling

arXiv:2605.11764v1 Announce Type: new Abstract: Machine-learning predictors of biochemical activity often exhibit large random-split-to-leave-one-target-out generalisation gaps that have been document

DeconDTN-Toolkit: A Library for Evaluation and Enhancement of Robustness to Provenance Shift

arXiv:2605.11237v1 Announce Type: new Abstract: Despite the burgeoning body of work on distribution shifts, provenance shift-where the relationship between data source and label changes at deployment-

Deep Learning for Protein Complex Prediction and Design

arXiv:2605.11189v1 Announce Type: new Abstract: Accurately modeling and designing protein complex structures is a central problem in computational structural biology, with broad implications for under

Deep Minds and Shallow Probes

arXiv:2605.11448v1 Announce Type: new Abstract: Neural representations are not unique objects. Even when two systems realize the same downstream computation, their hidden coordinates may differ by rep

Deep Probabilistic Unfolding for Quantized Compressive Sensing

arXiv:2605.11475v1 Announce Type: new Abstract: We propose a deep probabilistic unfolding model to address the classical quantized compressive sensing problem that leverages an unfolding framework to

researcharxiv-cs-cv

Agents

Deep Reasoning in General Purpose Agents via Structured Meta-Cognition

arXiv:2605.11388v1 Announce Type: new Abstract: Humans intuitively solve complex problems by flexibly shifting among reasoning modes: they plan, execute, revise intermediate goals, resolve ambiguity t

agentsarxiv-cs-cl

Delay-Empowered Causal Hierarchical Reinforcement Learning

arXiv:2605.12261v1 Announce Type: new Abstract: Many real-world tasks involve delayed effects, where the outcomes of actions emerge after varying time lags. Existing delay-aware reinforcement learning

Delightful Gradients Accelerate Corner Escape

arXiv:2605.11908v1 Announce Type: new Abstract: Softmax policy gradient converges at O(1/t), but its transient behavior near sub-optimal corners of the simplex can be exponentially slow. The bottlenec

Local Ai

DemaFormer: Damped Exponential Moving Average Transformer with Energy-Based Modeling for Temporal Language Grounding

arXiv:2312.02549v2 Announce Type: replace-cross Abstract: Temporal Language Grounding seeks to localize video moments that semantically correspond to a natural language query. Recent advances employ t

local-aiarxiv-cs-cl

Demystifying When Pruning Works via Representation Hierarchies

arXiv:2603.24652v3 Announce Type: replace Abstract: Network pruning, which removes less important parameters or architectures, is often expected to improve efficiency while preserving performance. How

researcharxiv-cs-cl

Tutorials

DenseTRF: Texture-Aware Unsupervised Representation Adaptation for Surgical Scene Dense Prediction

arXiv:2605.11265v1 Announce Type: new Abstract: Dense prediction tasks in surgical computer vision, such as segmentation and surgical zone prediction, can provide valuable guidance for laparoscopic an

tutorialsarxiv-cs-cv

Deploying Self-Supervised Learning for Real Seismic Data Denoising

model-releasesarxiv-cs-cv

arXiv:2605.11109v1 Announce Type: cross Abstract: Self-supervised learning (SSL) has emerged as a promising approach to seismic data denoising as it does not require clean reference data. In this work

Design Your Ad: Personalized Advertising Image and Text Generation with Unified Autoregressive Models

arXiv:2605.12138v1 Announce Type: cross Abstract: Generating realistic and user-preferred advertisements is a key challenge in e-commerce. Existing approaches utilize multiple independent models drive

researcharxiv-cs-cl

Detecting Data Contamination in LLMs via In-Context Learning

arXiv:2510.27055v2 Announce Type: replace Abstract: We present Contamination Detection via Context (CoDeC), a practical and accurate method to detect and quantify training data contamination in large

Detecting In-Person Conversations in Noisy Real-World Environments with Smartwatch Audio and Motion Sensing

arXiv:2507.12002v2 Announce Type: replace Abstract: Social interactions play a crucial role in shaping human behavior, relationships, and societies. It encompasses various forms of communication, such

Detecting overfitting in Neural Networks during long-horizon grokking using Random Matrix Theory

arXiv:2605.12394v1 Announce Type: new Abstract: Training Neural Networks (NNs) without overfitting is difficult; detecting that overfitting is difficult as well. We present a novel Random Matrix Theor

DexTwist: Dexterous Hand Retargeting for Twist Motion via Mixed Reality-based Teleoperation

arXiv:2605.12182v1 Announce Type: new Abstract: Dexterous teleoperation via Mixed Reality (MR)-based interfaces offers a scalable paradigm for transferring human manipulation skills to dexterous robot

applicationsarxiv-cs-ro