All entries

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

DGX agent

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

model-releasesarxiv-cs-cl

13 May 2026

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

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

CSP Allow-list Experiment

model-releasessimon-willison

Tool: CSP Allow-list Experiment An experiment that shows that you can load an app in a CSP-protected sandboxed iframe (see previous note) and have a custom fetch() that intercepts CSP errors and passe

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.

Customers like Decagon, Amplitude, BILT, and Snyk use development environments to let their agents handle tasks end-to-end. Learn more: http…

Cursor highlights that companies like Decagon, Amplitude, BILT, and Snyk leverage development environments within Cursor to enable AI agents to complete tasks independently from start to finish. This

agentscursor--x

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

Industry

Daredevil: Born Again S2 gives us a darker, grittier canvas

In Season 2, Mayor Wilson Fisk hunts down Daredevil while Matt Murdock fights back to tear down the Kingpin's corrupt empire. The season premiered on March 24, 2026, with eight episodes releasing week

industryars-technica

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

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

Industry

Data centers are coming for rural America

At its peak, the Androscoggin paper mill in Jay, Maine, a rural town about 67 miles northwest of Portland, employed about 1,500 people - until a pulp digester exploded in 2020, forcing the mill to clo

industrythe-verge-ai

Data quality is the AI strategy

Data quality is a foundational component of effective AI strategy, as high-quality training and operational data directly impacts model performance, reliability, and business outcomes. The article lik

applicationsdatabricks

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

model-releasesarxiv-cs-cl

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

applicationsarxiv-cs-lg

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

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

applicationsarxiv-cs-lg

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

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

model-releasesarxiv-cs-cl

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

applicationsarxiv-cs-lg

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

Devin can now build and run Android apps. We added Android Virtual Device (AVD) support for Devin’s machine, which means Devin can now auton…

Cognition AI has expanded Devin's capabilities to include Android app development and testing by integrating Android Virtual Device (AVD) support into Devin's machine environment. This enhancement ena

agentscognition-ai--x

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

Diabetic Retinopathy Classification using Downscaling Algorithms and Deep Learning

arXiv:2605.11430v1 Announce Type: new Abstract: Diabetic Retinopathy (DR) is an art and science of recording and classifying the retinal images of a diabetic patient. DR classification deals with clas

DiFaReli++: Diffusion Face Relighting with Consistent Cast Shadows

arXiv:2304.09479v5 Announce Type: replace Abstract: We introduce a novel approach to single-view face relighting in the wild, addressing challenges such as global illumination and cast shadows. A comm

Differentially Private Synthetic Text Generation for Retrieval-Augmented Generation (RAG)

arXiv:2510.06719v2 Announce Type: replace-cross Abstract: Retrieval-Augmented Generation (RAG) enhances large language models (LLMs) by grounding them in external knowledge. However, its application i

researcharxiv-cs-cl

DiffScore: Text Evaluation Beyond Autoregressive Likelihood

model-releasesarxiv-cs-cl

arXiv:2605.11601v1 Announce Type: new Abstract: Autoregressive language models are widely used for text evaluation, however, their left-to-right factorization introduces positional bias, i.e., early t

DiffSegLung: Diffusion Radiomic Distillation for Unsupervised Lung Pathology Segmentation

arXiv:2605.11758v1 Announce Type: cross Abstract: Unsupervised segmentation of pulmonary pathologies in CT remains an open challenge due to the absence of annotated multi pathology cohorts and the fai

Diffusion-State Policy Optimization for Masked Diffusion Language Models

arXiv:2602.06462v3 Announce Type: replace Abstract: Masked diffusion language models generate text through iterative masked-token filling, but terminal-only rewards on final completions provide coarse

safetyarxiv-cs-cl

DigiCert tackles AI’s trust crisis with identity, automation and cryptographic governance

Enterprise AI is moving faster than the digital trust systems built to govern it. As autonomous agents, synthetic content and machine identities spread across critical systems, organizations face a ne

agentssiliconangle

DIPSER: A Dataset for In-Person Student Engagement Recognition in the Wild

arXiv:2502.20209v3 Announce Type: replace Abstract: In this paper, a novel dataset is introduced, designed to assess student attention within in-person classroom settings. This dataset encompasses RGB

Dirichlet process mixtures of block g priors for model selection and prediction in linear models

arXiv:2411.00471v3 Announce Type: replace-cross Abstract: This paper introduces Dirichlet process mixtures of block g priors for model selection and prediction in linear models. These priors are exten

DisagMoE: Computation-Communication overlapped MoE Training via Disaggregated AF-Pipe Parallelism

arXiv:2605.11005v1 Announce Type: new Abstract: Mixture-of-experts (MoE) architectures enable trillion-parameter LLMs with sparsely activated experts. Expert parallelism (EP) is a widely adopted MoE t

Discrete Flow Matching for Offline-to-Online Reinforcement Learning

arXiv:2605.12379v1 Announce Type: new Abstract: Many reinforcement learning (RL) tasks have discrete action spaces, but most generative policy methods based on diffusion and flow matching are designed

Disentangled Sparse Representations for Concept-Separated Diffusion Unlearning

arXiv:2605.12122v1 Announce Type: cross Abstract: Unlearning specific concepts in text-to-image diffusion models has become increasingly important for preventing undesirable content generation. Among

Dissecting Discrete Soft Actor-Critic: Limitations and Principled Alternatives

arXiv:2509.09838v2 Announce Type: replace Abstract: While Soft Actor-Critic (SAC) is highly effective in continuous control, its discrete counterpart (DSAC) performs poorly on challenging discrete-act