All entries

different tech terms and their closest emotion in english (vector similarity) you'll notice cryptocurrency being close to trust, which could…

different tech terms and their closest emotion in english (vector similarity) you'll notice cryptocurrency being close to trust, which could be because both trust and lack of trust are often discussed

agentsyohei-nakajima--x

Safety

Differentiable Evolutionary Reinforcement Learning

DGX agent

arXiv:2512.13399v2 Announce Type: replace Abstract: Crafting effective reward signals remains a central challenge in Reinforcement Learning (RL), especially for complex reasoning tasks. Existing autom

safetyarxiv-cs-ai

14 May 2026

Differentiable Learning of Lifted Action Schemas for Classical Planning

arXiv:2605.13282v1 Announce Type: new Abstract: Classical planners can effectively solve very large deterministic MDPs represented in STRIPS or PDDL where states are sets of atoms over objects and rel

tutorialsarxiv-cs-ai

Differentially Private Nonparametric Confidence Intervals Under Minimal Distributional Assumptions

arXiv:2511.01303v2 Announce Type: replace-cross Abstract: We consider the problem of constructing differentially private nonparametric confidence intervals (CIs) for an arbitrary quantity using resamp

DiffST: Spatiotemporal-Aware Diffusion for Real-World Space-Time Video Super-Resolution

arXiv:2605.13182v1 Announce Type: new Abstract: Diffusion-based models have shown strong performance in video super-resolution (VSR) and video frame interpolation (VFI). However, their role in the cou

tutorialsarxiv-cs-cv

Diffusion-Inspired Reconfiguration of Transformers for Uncertainty Calibration

arXiv:2602.08920v2 Announce Type: replace Abstract: Uncertainty calibration in pre-trained transformers is critical for their reliable deployment in risk-sensitive applications. Yet, most existing pre

Diffusion Model's Generalization Can Be Characterized by Inductive Biases toward a Data-Dependent Ridge Manifold

arXiv:2602.06021v2 Announce Type: replace-cross Abstract: We study a data-dependent notion of diffusion-model generalization: when a model does not memorize the training set, where do its generated sa

DiffusionHijack: Supply-Chain PRNG Backdoor Attack on Diffusion Models and Quantum Random Number Defense

arXiv:2605.13115v1 Announce Type: cross Abstract: Diffusion models depend on pseudo-random number generators (PRNGs) for latent noise sampling. We present DiffusionHijack, a supply-chain backdoor atta

Digital Twins as Synthetic Controls in Single-Arm Trials

arXiv:2605.12832v1 Announce Type: cross Abstract: Single-arm trials are an important study design for evaluating drug efficacy and safety without enrolling patients into a control arm. Although they d

DirectTryOn: One-Step Virtual Try-On via Straightened Conditional Transport

arXiv:2605.12939v1 Announce Type: new Abstract: Recent diffusion- and flow-based VTON methods achieve strong results with pretrained generative models, but their reliance on multi-step sampling incurs

researcharxiv-cs-cv

DisaBench: A Participatory Evaluation Framework for Disability Harms in Language Models

arXiv:2605.12702v1 Announce Type: new Abstract: General-purpose safety benchmarks for large language models do not adequately evaluate disability-related harms. We introduce DisaBench: a taxonomy of t

safetyarxiv-cs-ai

DisAgg: Distributed Aggregators for Efficient Secure Aggregation in Federated Learning

arXiv:2605.13708v1 Announce Type: cross Abstract: Federated learning enables collaborative model training across distributed clients, yet vanilla FL exposes client updates to the central server. Secur

.@Discoplomacy This kill-switch provision helps govt intervene in cases where UK datacenters are being maliciously used by a threat actor to…

.@Discoplomacy This kill-switch provision helps govt intervene in cases where UK datacenters are being maliciously used by a threat actor to conduct cyberattacks. It also helps in cases where the gove

tutorialsconnor-leahy--x

DiscoverLLM: From Executing Intents to Discovering Them

arXiv:2602.03429v2 Announce Type: replace Abstract: To handle ambiguous and open-ended requests, Large Language Models (LLMs) are increasingly trained to interact with users to surface intents they ha

tutorialsarxiv-cs-ai

Local Ai

Discovery of Hidden Miscalibration Regimes

arXiv:2605.13484v1 Announce Type: cross Abstract: Calibration is commonly evaluated by comparing model confidence with its empirical correctness, implicitly treating reliability as a function of the c

local-aiarxiv-cs-ai

Discrete Diffusion for Complex and Congested Multi-Agent Path Finding with Sparse Social Attention

arXiv:2605.13296v1 Announce Type: new Abstract: Multi-Agent Path Finding (MAPF) is a coordination problem that requires computing globally consistent, collision-free trajectories from individual start

agentsarxiv-cs-ai

Discrete MeanFlow: One-Step Generation via Conditional Transition Kernels

arXiv:2605.12805v1 Announce Type: cross Abstract: MeanFlow enables one-step generation in continuous spaces by learning an average velocity over a time interval rather than the instantaneous velocity

researcharxiv-cs-ai

Discrete Stochastic Localization for Non-autoregressive Generation

arXiv:2605.12836v1 Announce Type: new Abstract: Continuous diffusion is a natural framework for non-autoregressive generation but has generally lagged behind masked discrete diffusion models (MDMs) on

Applications

Distinguishing performance gains from learning when using generative AI

arXiv:2605.13731v1 Announce Type: new Abstract: Generative artificial intelligence (AI) is increasingly being integrated into education, where it can boost learners' performance. However, these uses d

applicationsarxiv-cs-lg

DistractMIA: Black-Box Membership Inference on Vision-Language Models via Semantic Distraction

arXiv:2605.12574v1 Announce Type: cross Abstract: Vision-language models (VLMs) are trained on large-scale image-text corpora that may contain private, copyrighted, or otherwise sensitive data, motiva

Distribution Shift in Missing Data Imputation: A Risk-Based Perspective and Importance-Weighted Correction under MAR

arXiv:2602.06713v2 Announce Type: replace-cross Abstract: Missing data imputation, where a model is trained on observed data to estimate unobserved values, is a fundamental problem in machine learning

tutorialsarxiv-cs-lg

Distributionally Robust Safety Under Arbitrary Uncertainties: A Safety Filtering Approach

arXiv:2605.12974v1 Announce Type: new Abstract: In this work, we study how to ensure probabilistic safety for nonlinear systems under distributional ambiguity. Our approach builds on a backup-based sa

safetyarxiv-cs-ro

Hardware

DIVER:Diving Deeper into Distilled Data via Expressive Semantic Recovery

arXiv:2605.12649v1 Announce Type: new Abstract: Dataset distillation aims to synthesize a compact proxy dataset that is unreadable or non-raw from the original dataset for privacy protection and highl

hardwarearxiv-cs-cv

Diversity of Extensions in Abstract Argumentation

arXiv:2605.13332v1 Announce Type: new Abstract: Argumentation is an important topic of AI for modelling and reasoning about arguments. In abstract argumentation, we consider directed graphs, so-called

researcharxiv-cs-ai

Do Activation Verbalization Methods Convey Privileged Information?

arXiv:2509.13316v4 Announce Type: replace-cross Abstract: Recent interpretability methods have proposed to translate LLM internal representations into natural language descriptions using a second verb

Do Androids Dream of Breaking the Game? Systematically Auditing AI Agent Benchmarks with BenchJack

arXiv:2605.12673v1 Announce Type: new Abstract: Agent benchmarks have become the de facto measure of frontier AI competence, guiding model selection, investment, and deployment. However, reward hackin

Do Fair Models Reason Fairly? Counterfactual Explanation Consistency for Procedural Fairness in Credit Decisions

arXiv:2605.12701v1 Announce Type: cross Abstract: Machine learning algorithms in socially sensitive domains (e.g., credit decisions) often focus on equalizing predictive outcomes. However, satisfying

safetyarxiv-cs-ai

Applications

Do Heavy Tails Help Diffusion? On the Subtle Trade-off Between Initialization and Training

arXiv:2605.13175v1 Announce Type: new Abstract: Recent works have proposed incorporating heavy-tailed (HT) noise into diffusion- and flow-based generative models, with the goals of better recovering t

applicationsarxiv-cs-lg

DocAtlas: Multilingual Document Understanding Across 80+ Languages

model-releasesarxiv-cs-cv

arXiv:2605.12623v1 Announce Type: cross Abstract: Multilingual document understanding remains limited for low-resource languages due to scarce training data and model-based annotation pipelines that p

Local Ai

Does Engram Do Memory Retrieval in Autoregressive Image Generation?

arXiv:2605.13179v1 Announce Type: new Abstract: The Engram module -- a hash-keyed, O(1) associative memory injected into Transformer layers -- was recently shown to improve large language model pretra

local-aiarxiv-cs-cv

Does language matter for spoken word classification? A multilingual generative meta-learning approach

arXiv:2605.13084v1 Announce Type: cross Abstract: Meta-learning has been shown to have better performance than supervised learning for few-shot monolingual spoken word classification. However, the met

researcharxiv-cs-ai

Tools

Doing this is a great way to make a bonfire of your reputation

Doing this is a great way to make a bonfire of your reputation A person I know (and who is? was? a good professional al) left an AI-generated comment under my LinkedIn post. Full-on AI slop. I asked:

toolssimon-willison--x

Domain Adaptation of Large Language Models for Polymer-Composite Additive Manufacturing Using Retrieval-Augmented Generation and Fine-Tuning

arXiv:2605.12516v1 Announce Type: cross Abstract: General-purpose large language models (LLMs) often struggle to generate reliable responses in specialized engineering domains due to limited domain gr

DP-KFC: Data-Free Preconditioning for Privacy-Preserving Deep Learning

arXiv:2605.13418v1 Announce Type: new Abstract: Differentially private optimization suffers from a fundamental geometric mismatch: deep networks have highly anisotropic loss landscapes, yet DP-SGD inj

DP-Muon: Differentially Private Optimization via Matrix-Orthogonalized Momentum

arXiv:2605.12994v1 Announce Type: new Abstract: We study differentially private (DP) training with Muon, a matrix-valued optimizer that updates hidden-layer weights using momentum followed by Newton--

Local Ai

Drag within Prior Distribution: Text-Conditioned Point-Based Image Editing within Distribution Constraints

arXiv:2605.13349v1 Announce Type: new Abstract: Diffusion-based point editing methods have gained significant traction in image editing tasks due to their ability to manipulate image semantics and fin

local-aiarxiv-cs-cv

DRIFT: A Benchmark for Task-Free Continual Graph Learning with Continuous Distribution Shifts

model-releasesarxiv-cs-lg

arXiv:2605.12998v1 Announce Type: new Abstract: Continual graph learning (CGL) aims to learn from dynamically evolving graphs while mitigating catastrophic forgetting. Existing CGL approaches typicall

Driving Intents Amplify Planning-Oriented Reinforcement Learning

arXiv:2605.12625v1 Announce Type: cross Abstract: Continuous-action policies trained on a single demonstrated trajectory per scene suffer from mode collapse: samples cluster around the demonstrated ma

safetyarxiv-cs-cv

Dual-Pathway Circuits of Object Hallucination in Vision-Language Models

arXiv:2605.13156v1 Announce Type: new Abstract: Vision-language models (VLMs) have demonstrated remarkable capabilities in bridging visual perception and natural language understanding, enabling a wid

researcharxiv-cs-cv

Dynamical Predictive Modelling of Cardiovascular Disease Progression Post-Myocardial Infarction via ECG-Trained Artificial Intelligence Model

arXiv:2605.13568v1 Announce Type: cross Abstract: Myocardial infarction (MI) is a leading cause of death, and its adverse outcomes are urgent to predict. Yet ECG-based prognostic models underperform b

tutorialsarxiv-cs-ai

Dynamics Computation of Soft-Rigid Hybrid-Link System and Its Application to Motion Analysis of an Athlete Wearing Sport Prosthesis

arXiv:2605.13192v1 Announce Type: new Abstract: This paper presents a motion analysis framework for an athlete wearing sport-specific flexible prosthesis based on the soft-rigid hybrid-link system. Su

researcharxiv-cs-ro

DynoJEPP: Joint Estimation, Prediction and Planning in Dynamic Environments

arXiv:2605.12897v1 Announce Type: new Abstract: DynoJEPP is a factor-graph-based framework that jointly formulates and simultaneously optimizes estimation, prediction, and planning in dynamic environm

researcharxiv-cs-ro

Industry

Each round founders should take <runway> years worth of comp as secondary & pay themselves just enough for health insurance Far more tax eff…

Each round founders should take <runway> years worth of comp as secondary & pay themselves just enough for health insurance Far more tax efficient than primary => salary In case you were wondering whe

industryemad-mostaque--x

Early beta and we are looking forward to your feedback! We will keep improving until Grok Build is absolutely the best in the world

Early beta and we are looking forward to your feedback! We will keep improving until Grok Build is absolutely the best in the world An early beta of Grok Build, an agentic CLI for coding, building app

agentselon-musk--x

Early Data Exposure Improves Robustness to Subsequent Fine-Tuning

arXiv:2605.12705v1 Announce Type: new Abstract: How can we train models whose post-trained capabilities survive subsequent fine-tuning? Rather than focusing on downstream interventions to mitigate for

Early Semantic Grounding in Image Editing Models for Zero-Shot Referring Image Segmentation

arXiv:2605.13122v1 Announce Type: new Abstract: Instruction-based image editing (IIE) models have recently demonstrated strong capability in modifying specific image regions according to natural langu

researcharxiv-cs-cv

Earth Science Foundation Models: From Perception to Reasoning and Discovery

arXiv:2605.12542v1 Announce Type: cross Abstract: Large foundation models (FMs) are transforming Earth science by integrating heterogeneous multimodal data, such as multi-platform imagery, gridded rea

agentsarxiv-cs-lg

ECG-NAT: A Self-supervised Neighborhood Attention Transformer for Multi-lead Electrocardiogram Classification

arXiv:2605.13194v1 Announce Type: cross Abstract: Electrocardiogram (ECG) arrhythmia classification remains challenging due to signal variability, noise, limited labeled data, and the difficulty in ac