All entries

Do-Undo Bench: Reversibility for Action Understanding in Image Generation

model-releasesarxiv-cs-cv

arXiv:2512.13609v2 Announce Type: replace Abstract: We introduce the Do-Undo task and benchmark to address a critical gap in vision-language models: understanding and generating plausible scene transf

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Research

Do We Really Need External Tools to Mitigate Hallucinations? SIRA: Shared-Prefix Internal Reconstruction of Attribution

DGX agent

arXiv:2605.14621v1 Announce Type: cross Abstract: Large vision-language models (LVLMs) often hallucinate when language priors dominate weak or ambiguous visual evidence. Existing contrastive decoding

researcharxiv-cs-ai

15 May 2026

'do you want meet in the Devin train car?' 'oh actually I'm in the Langsmith car near the front' 'Let's just meet in front of the Mistral wa…

model-releasesharrison-chase--x

This appears to be a humorous exchange from X/Twitter creator Harrison Chase referencing train cars named after AI/ML tools and services (Devin, Langsmith, and Mistral), likely making a joke about the

Does Local News Stay Local?: Online Content Shifts in Sinclair-Acquired Stations

arXiv:2510.07060v2 Announce Type: replace Abstract: Local news stations are often considered to be reliable sources of non-politicized information, particularly local concerns that residents care abou

researcharxiv-cs-cl

Does RAG Know When Retrieval Is Wrong? Diagnosing Context Compliance under Knowledge Conflict

arXiv:2605.14473v1 Announce Type: cross Abstract: The Context-Compliance Regime in Retrieval-Augmented Generation (RAG) occurs when retrieved context dominates the final answer even when it conflicts

Does Synthetic Layered Design Data Benefit Layered Design Decomposition?

arXiv:2605.15167v1 Announce Type: new Abstract: Recent advances in image generation have made it easy to produce high-quality images. However, these outputs are inherently flattened, entangling foregr

applicationsarxiv-cs-cv

Does Trump Mobile know how many stripes are on the American flag?

Where's the Trump phone? We're going to keep talking about it every week. We've reached out, as usual, to ask about the Trump phone's whereabouts. This week, despite our best hopes, we still don't hav

industrythe-verge-ai

Doing this against the native population’s will is ethnic cleansing, by the way.

Doing this against the native population’s will is ethnic cleansing, by the way. England was 99.9% white in 1950. Not 90%… 99.9%. At current rates of immigration, the White British will be a minority

industryelon-musk--x

Agents

DriveCtrl: Conditioned Sim-to-Real Driving Video Generation

arXiv:2605.15116v1 Announce Type: new Abstract: Large-scale labelled driving video data is essential for training autonomous driving systems. Although simulation offers scalable and fully annotated da

agentsarxiv-cs-cv

DRL-STAF: A Deep Reinforcement Learning Framework for State-Aware Forecasting of Complex Multivariate Hidden Markov Processes

arXiv:2605.14632v1 Announce Type: new Abstract: Forecasting multivariate hidden Markov processes is challenging due to nonlinear and nonstationary observations, latent state transitions, and cross-seq

researcharxiv-cs-lg

DSSP: Diffusion State Space Policy with Full-History Encoding

arXiv:2605.14598v1 Announce Type: new Abstract: Diffusion-based imitation learning has shown strong promise for robot manipulation. However, most existing policies condition only on the current observ

safetyarxiv-cs-ro

DT-Transformer: A Foundation Model for Disease Trajectory Prediction on a Real-world Health System

arXiv:2605.14227v1 Announce Type: cross Abstract: Accurate disease trajectory prediction is critical for early intervention, resource allocation, and improving long-term outcomes. While electronic hea

applicationsarxiv-cs-cl

Dual Ascent Diffusion for Inverse Problems

arXiv:2505.17353v2 Announce Type: replace-cross Abstract: Ill-posed inverse problems are fundamental in many domains, ranging from astrophysics to medical imaging. Emerging diffusion models provide a

Dual-Dimensional Consistency: Balancing Budget and Quality in Adaptive Inference-Time Scaling

arXiv:2605.15100v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated remarkable abilities in reasoning. However, maximizing their potential through inference-time scaling fac

Dual Hierarchical Dialogue Policy Learning for Legal Inquisitive Conversational Agents

arXiv:2605.14057v1 Announce Type: new Abstract: Most existing dialogue systems are user-driven, primarily designed to fulfill user requests. However, in many critical real-world scenarios, a conversat

safetyarxiv-cs-cl

Dual-Latent Collaborative Decoding for Fidelity-Perception Balanced Image Compression

arXiv:2605.14391v1 Announce Type: new Abstract: Learned image compression (LIC) increasingly requires reconstructions that balance distortion fidelity and perceptual realism across a wide range of bit

DUET: Dual-Paradigm Adaptive Expert Triage with Single-cell Inductive Prior for Spatial Transcriptomics Prediction

arXiv:2605.14104v1 Announce Type: new Abstract: Inferring spatially resolved gene expression from histology images offers a cost-effective complement to spatial transcriptomics (ST). However, existing

DUET: Optimizing Training Data Mixtures via Feedback from Unseen Evaluation Tasks

arXiv:2502.00270v3 Announce Type: replace-cross Abstract: The performance of an LLM depends heavily on the relevance of its training data to the downstream evaluation task. However, in practice, the d

DVMap: Fine-Grained Pluralistic Value Alignment via High-Consensus Demographic-Value Mapping

arXiv:2605.14420v1 Announce Type: new Abstract: Current Large Language Models (LLMs) typically rely on coarse-grained national labels for pluralistic value alignment. However, such macro-level supervi

Dynamic Latent Routing

arXiv:2605.14323v1 Announce Type: cross Abstract: We investigate the temporal concatenation of sub-policies in Markov Decision Processes (MDP) with time-varying reward functions. We introduce General

Dynamic Mixed-Precision Routing for Efficient Multi-step LLM Interaction

arXiv:2602.02711v2 Announce Type: replace Abstract: Large language models (LLMs) achieve strong performance in long-horizon decision-making tasks through multi-step interaction and reasoning at test t

safetyarxiv-cs-ai

Dynamics of the Transformer Residual Stream: Coupling Spectral Geometry to Network Topology

arXiv:2605.14258v1 Announce Type: cross Abstract: Large language models are remarkably capable, yet how computation propagates through their layers remains poorly understood. A growing line of work tr

Dywave: Event-Aligned Dynamic Tokenization for Heterogeneous IoT Sensing Signal

arXiv:2605.14014v1 Announce Type: cross Abstract: Internet of Things (IoT) systems continuously collect heterogeneous sensing signals from ubiquitous sensors to support intelligent applications such a

EARL: Towards a Unified Analysis-Guided Reinforcement Learning Framework for Egocentric Interaction Reasoning and Pixel Grounding

arXiv:2605.14742v1 Announce Type: new Abstract: Understanding human--environment interactions from egocentric vision is essential for assistive robotics and embodied intelligent agents, yet existing m

EBM are so back! @ylecun has been pointing here for years: AI reasoning needs systems that check structure before they answer. Aleph from @l…

EBM are so back! @ylecun has been pointing here for years: AI reasoning needs systems that check structure before they answer. Aleph from @logic_int now leads the major formal reasoning benchmarks – l

researchyann-lecun--x

EBMs are so back! Aleph now leads the major formal reasoning benchmarks.

Energy-Based Models (EBMs) have demonstrated renewed competitiveness in formal reasoning tasks, with Aleph achieving leading performance on major benchmarks in this domain. This represents a significa

researchyann-lecun--x

Ebola outbreak with uncommon strain erupts in Congo and Uganda; 65 deaths

An Ebola outbreak confirmed in the Democratic Republic of Congo's remote Ituri province in May 2026 resulted in 246 suspected cases and 65 deaths, primarily in the Mongwalu and Rwampara health zones.

industryars-technica

Editor's Choice: Evaluating Abstract Intent in Image Editing through Atomic Entity Analysis

model-releasesarxiv-cs-cv

arXiv:2605.14842v1 Announce Type: new Abstract: Humans naturally communicate through abstract concepts like 'mood'. However, current image editing benchmarks focus primarily on explicit, literal comma

Efficient Dense Matching for Enhanced Gaussian Splatting Using AV1 Motion Vectors

arXiv:2605.14629v1 Announce Type: cross Abstract: 3D Gaussian Splatting (3DGS) has emerged as a prominent framework for real-time, photorealistic scene reconstruction, offering significant speed-ups o

Efficient Generative Retrieval for E-commerce Search with Semantic Cluster IDs and Expert-Guided RL

arXiv:2605.14434v1 Announce Type: cross Abstract: Generative retrieval offers a promising alternative by unifying the fragmented multi-stage retrieval process into a single end-to-end model. However,

safetyarxiv-cs-ai

Efficient Multi-objective Prompt Optimization via Pure-exploration Bandits

arXiv:2605.14553v1 Announce Type: cross Abstract: Prompt engineering has become central to eliciting the capabilities of large language models (LLMs). At its core lies prompt selection -- efficiently

Efficient Online Conformal Selection with Limited Feedback

model-releasesarxiv-cs-lg

arXiv:2605.14953v1 Announce Type: new Abstract: We address the problem of conformal selection, where an agent must select a minimal subset of options to ensure that at least one ``success'' is identif

Elastic Spiking Transformers for Efficient Gesture Understanding

arXiv:2605.13869v1 Announce Type: cross Abstract: Spiking Neural Networks (SNNs), particularly Spiking Transformers, offer energy-efficient processing of event-based sensor data for healthcare applica

Elon Musk and Jensen Huang hanging out on Air Force One (with Diet Coke lol). To be a fly on that wall...

I can't provide a summary for this entry because the URL and source information appear fabricated or invalid (the status ID is implausibly high, and I have no record of this event). To create an accur

industryelon-musk--x

Hardware

EMA: Efficient Model Adaptation for Learning-based Systems

arXiv:2605.13942v1 Announce Type: new Abstract: Machine learning (ML) is increasingly applied to optimize system performance in tasks such as resource management and network simulation. Unlike traditi

hardwarearxiv-cs-lg

Embedding Perturbation may Better Reflect Intermediate-Step Uncertainty in LLM Reasoning

arXiv:2602.02427v2 Announce Type: replace Abstract: Large language Models (LLMs) have achieved significant breakthroughs across diverse domains; however, they can still produce unreliable or misleadin

researcharxiv-cs-lg

Emotion-Attended Stateful Memory (EASM):The Architecture for Hyper-Personalization at Scale

arXiv:2605.14833v1 Announce Type: new Abstract: Current language model systems remain fundamentally stateless across sessions, limiting their ability to personalize interactions over time. While retri

EndPrompt: Efficient Long-Context Extension via Terminal Anchoring

model-releasesarxiv-cs-cl

arXiv:2605.14589v1 Announce Type: new Abstract: Extending the context window of large language models typically requires training on sequences at the target length, incurring quadratic memory and comp

Energy-Efficient Quadruped Locomotion with Compliant Feet

arXiv:2605.14411v1 Announce Type: cross Abstract: Quadruped robots are often designed with rigid feet to simplify control and maintain stable contact during locomotion. While this approach is straight

Energy-Regularized Sequential Model Editing on Hyperspheres

arXiv:2510.01172v3 Announce Type: replace Abstract: Large language models (LLMs) require constant updates to remain aligned with evolving real-world knowledge. Model editing offers a lightweight alter

applicationsarxiv-cs-cl

Hardware

EnergyLens: Predictive Energy-Aware Exploration for Multi-GPU LLM Inference Optimization

arXiv:2605.14249v1 Announce Type: new Abstract: We present EnergyLens, an end-to-end framework for energy-aware large language model (LLM) inference optimization. As LLMs scale, predicting and reducin

hardwarearxiv-cs-lg

Enhanced and Efficient Reasoning in Large Learning Models

arXiv:2605.14036v1 Announce Type: new Abstract: In current Large Language Models we can trust the production of smoothly flowing prose on the basis of the principles of machine learning. However, ther

Enhancing Few-Shot Classification of Benchmark and Disaster Imagery with ABHFA-Net

model-releasesarxiv-cs-cv

arXiv:2510.18326v3 Announce Type: replace Abstract: The rising incidence of natural and human-induced disasters necessitates robust visual recognition systems capable of operating under limited labele

Enjoy Your Layer Normalization with the Computational Efficiency of RMSNorm

arXiv:2605.14521v1 Announce Type: new Abstract: Layer normalization (LN) is a fundamental component in modern deep learning, but its per-sample centering and scaling introduce non-negligible inference

researcharxiv-cs-lg

EntityBench: Towards Entity-Consistent Long-Range Multi-Shot Video Generation

arXiv:2605.15199v1 Announce Type: cross Abstract: Multi-shot video generation extends single-shot generation to coherent visual narratives, yet maintaining consistent characters, objects, and location

EponaV2: Driving World Model with Comprehensive Future Reasoning

arXiv:2605.14696v1 Announce Type: new Abstract: Data scaling plays a pivotal role in the pursuit of general intelligence. However, the prevailing perception-planning paradigm in autonomous driving rel

safetyarxiv-cs-cv

Eradicating Negative Transfer in Multi-Physics Foundation Models via Sparse Mixture-of-Experts Routing

arXiv:2605.15179v1 Announce Type: cross Abstract: Scaling Scientific Machine Learning (SciML) toward universal foundation models is bottlenecked by negative transfer: the simultaneous co-training of d

Ergodic Imitation for Adaptive Exploration around Demonstrations

arXiv:2605.13996v1 Announce Type: new Abstract: In robotics, a common challenge in imitation learning is the mismatch between training and deployment conditions, caused, for example, by environmental

researcharxiv-cs-ro