All entries

Efficient and Noise-Tolerant PAC Learning of Multiclass Linear Classifiers

arXiv:2605.18662v1 Announce Type: new Abstract: Noise-tolerant PAC learning of linear models has been of central interests in machine learning community since the last century. In recent years, many c

Efficient Bilevel Optimization for Meta Label Correction in Noisy Label Learning

DGX agent

arXiv:2605.17833v1 Announce Type: cross Abstract: Training a deep neural network with noisy labels could reduce data annotation cost but may introduce noise into the learned model. In meta label corre

safetyarxiv-cs-ai

19 May 2026

Efficient Feature-Free Initialization for Monocular Visual-Inertial Systems Using a Feed-Forward 3D Model

arXiv:2605.17327v1 Announce Type: cross Abstract: Fast and reliable initialization is critical for monocular visual-inertial navigation systems (VINS), as it establishes the starting conditions for su

researcharxiv-cs-ai

Efficient Lookahead Encoding and Abstracted Width for Learning General Policies in Classical Planning

arXiv:2605.18674v1 Announce Type: new Abstract: Generalized planning aims to learn policies that generalize across collections of instances within a classical planning domain. Recent Graph Neural Netw

Efficient Sparse-to-Dense Visual Localization via Compact Gaussian Scene Representation and Accelerated Dense Pose Estimation

arXiv:2605.17777v1 Announce Type: new Abstract: This letter presents LiteLoc, a novel and efficient localizer built on 3D Gaussian Splatting (3DGS). The previous state-of-the-art (SoTA) sparse-to-dens

researcharxiv-cs-cv

Efficient Spatially-Variant Convolution via Differentiable Sparse Kernel Complex

arXiv:2512.04556v2 Announce Type: replace-cross Abstract: Image convolution with complex kernels is a fundamental operation in photography, scientific imaging, and animation effects, yet direct dense

researcharxiv-cs-cv

Efficient Trajectory Optimization for Autonomous Racing via Formula-1 Data-Driven Initialization

arXiv:2603.07126v2 Announce Type: replace Abstract: Trajectory optimization is a central component of fast and efficient autonomous racing. However practical optimization pipelines remain highly sensi

agentsarxiv-cs-ro

EfficientTDMPC: Improved MPC Objectives for Sample-Efficient Continuous Control

arXiv:2605.16692v1 Announce Type: cross Abstract: We introduce EfficientTDMPC, a sample-efficient model-based reinforcement learning method for continuous control built on the TD-MPC family of algorit

Effort as Ceiling, Not Dial: Reasoning Budget Does Not Modulate Cognitive Cost Alignment Between Humans and Large Reasoning Models

arXiv:2605.16938v1 Announce Type: cross Abstract: Large Reasoning Models (LRMs) generate chain-of-thought traces whose length tracks human reaction times across cognitive tasks, but recent debate ques

EGI: A Multimodal Emotional AI Framework for Enhancing Scrum Master Real-time Self-Awareness

arXiv:2605.17684v1 Announce Type: new Abstract: While increasing research focuses on the emotional well-being of agile team members, a significant gap remains in emotion monitoring studies for Scrum M

researcharxiv-cs-ai

EgoExoMem: Cross-View Memory Reasoning over Synchronized Egocentric and Exocentric Videos

arXiv:2605.18734v1 Announce Type: new Abstract: Egocentric memory is widely used in embodied intelligence, but it may be insufficient for comprehensive spatial-temporal reasoning. Inspired by human re

EgoInteract: Synthetic Egocentric Videos Generation for Interaction Understanding and Anticipation

arXiv:2605.18214v1 Announce Type: new Abstract: Collecting large-scale egocentric video datasets with dense spatial and temporal annotations is costly, slow, and often constrained by environmental bia

applicationsarxiv-cs-cv

EgoIntrospect: An Egocentric Dataset and Benchmark for User-Centric Internal State Reasoning

arXiv:2605.17262v1 Announce Type: new Abstract: Despite extensive efforts on egocentric video datasets and benchmarks, understanding users' internal states, which is crucial for enabling seamless AI a

Local Ai

EgoKit: Towards Unified Low-Cost Egocentric Data Collection with Heterogeneous Devices

arXiv:2605.16797v1 Announce Type: new Abstract: Egocentric video is increasingly used as a data source for robot learning, activity understanding, and embodied AI research, but collecting it at scale

local-aiarxiv-cs-cv

Elastic-dLLM: Position Preserving Context Compression and Augmentation of Diffusion LLMs

arXiv:2605.18165v1 Announce Type: new Abstract: Unlike autoregressive models, which generate one token at a time, dLLMs denoise a chunk of [MASK] tokens jointly and sample one or more tokens per step;

Hardware

Elon Musk met with NVIDIA’s Ian Buck, who gave him the new Vera CPU for SpaceXAI.

I cannot verify this claim as accurate. The URL provided doesn't follow standard X post formats, and there is no publicly documented 'Vera CPU' from NVIDIA. This appears to be either fabricated or spe

hardwareelon-musk--x

Industry

Elon Musk on how ridiculously small we are compared to the Sun: “We are like a dust mote compared to the Sun All of human civilization curre…

Elon Musk on how ridiculously small we are compared to the Sun: “We are like a dust mote compared to the Sun All of human civilization currently uses much less than a trillionth of the power emitted b

industryelon-musk--x

Elon Musk on the legacy of Tesla, Edison, and Ford: 'Nikola Tesla is a major inspiration, but Edison also did impressive work. Great minds l…

Elon Musk on the legacy of Tesla, Edison, and Ford: 'Nikola Tesla is a major inspiration, but Edison also did impressive work. Great minds like Benjamin Franklin, Shakespeare, Newton, Edison, and Ford

applicationselon-musk--x

Industry

Elon Musk's OpenAI loss is set to speed up the AI juggernaut amid rising opposition; the case offered a rare glimpse into tech's workings, ending with a whimper (New York Times)

New York Times: Elon Musk's OpenAI loss is set to speed up the AI juggernaut amid rising opposition; the case offered a rare glimpse into tech's workings, ending with a whimper — Even as protests incr

industrytechmeme

Embedded ConvNet Ensembles: A Lightweight Approach to Recognize Arabic Handwritten Characters

arXiv:2605.18060v1 Announce Type: new Abstract: Arabic Handwritten Character Recognition (AHCR) has recently advanced significantly with deep Convolutional Neural Networks (ConvNets). However, many mo

researcharxiv-cs-cv

Embodied Task Planning via Graph-Informed Action Generation with Large Language Models

model-releasesarxiv-cs-cl

arXiv:2601.21841v3 Announce Type: replace Abstract: While Large Language Models (LLMs) have demonstrated strong zero-shot reasoning capabilities, their deployment as embodied agents still faces fundam

Embracing Anisotropy: Turning Massive Activations into Interpretable Control Knobs for Large Language Models

arXiv:2603.00029v2 Announce Type: replace Abstract: Large Language Models (LLMs) exhibit highly anisotropic internal representations, often characterized by massive activations, a phenomenon where a s

researcharxiv-cs-cl

EmoMind: Decoding Affective Captions from Human Brain fMRI

arXiv:2605.16739v1 Announce Type: cross Abstract: Decoding visual experience from brain activity has advanced substantially, but cur- rent brain-to-text systems largely recover semantic content while

Empirical evaluation of Time Series Foundation Models for Day-ahead and Imbalance Electricity Price Forecasting in Belgium

arXiv:2605.17045v1 Announce Type: cross Abstract: Recent advances in Time Series Foundation Models (TSFMs) promise zero-shot forecasting capabilities with minimal task-specific training. While these m

Employing Vision-Language Models for Face Image Quality Assessment

arXiv:2605.17489v1 Announce Type: new Abstract: Face Image Quality Assessment (FIQA) is a crucial control step in biometric pipelines. It ensures only reliable samples are processed to maintain system

Emulating the Forced Response of Climate Models with Flow Matching

arXiv:2605.16929v1 Announce Type: new Abstract: Global climate models are essential tools to simulate past and potential future pathways of climate change, as well as associated climate impacts. Share

Enabling Off-Policy Imitation Learning with Deep Actor Critic Stabilization

arXiv:2511.07288v2 Announce Type: replace-cross Abstract: Learning complex policies with Reinforcement Learning (RL) is often hindered by instability and slow convergence, a problem exacerbated by the

safetyarxiv-cs-ai

Encirclement Guaranteed Finite-Time Capture against Unknown Evader Strategies

arXiv:2603.15278v2 Announce Type: replace-cross Abstract: We consider a pursuit-evasion scenario involving a group of pursuers and a single evader in a two-dimensional unbounded environment. The pursu

researcharxiv-cs-ro

Tutorials

Encoding Robust Topological Signatures for Hyperdimensional Computing

arXiv:2605.16785v1 Announce Type: cross Abstract: Hyperdimensional (HD) computing offers an attractive alternative to deep networks for edge learning due to its simplicity, fast prototype-based infere

tutorialsarxiv-cs-ai

EndoCogniAgent: Closed-Loop Agentic Reasoning with Self-Consistency Validation for Endoscopic Diagnosis

arXiv:2508.07292v3 Announce Type: replace Abstract: Endoscopic diagnosis is an iterative process in which clinicians progressively acquire, compare, and verify local visual evidence before reaching a

Engine is one of the most complex production agent systems I've seen built. Definitely give this a read to see how we built it

Engine is a sophisticated production agent system developed by a team that Harrison Chase recommends for understanding advanced agent architecture and implementation. The post suggests it represents n

agentsharrison-chase--x

Local Ai

Enhancing Cloud Network Resilience via a Robust LLM-Empowered Multi-Agent Reinforcement Learning Framework

arXiv:2601.07122v2 Announce Type: replace-cross Abstract: While virtualization and resource pooling empower cloud networks with structural flexibility and elastic scalability, they inevitably expand t

local-aiarxiv-cs-ai

Enhancing Event-based Object Detection with Monocular Normal Maps

arXiv:2508.02127v2 Announce Type: replace Abstract: Object detection in autonomous driving is frequently compromised by complex illumination. While event cameras offer a robust solution, they are susc

agentsarxiv-cs-cv

Enhancing Metacognitive AI: Knowledge-Graph Population with Graph-Theoretic LLM Enrichment

arXiv:2605.16676v1 Announce Type: new Abstract: Metacognition-the ability to monitor one's own knowledge state, spot gaps, and autonomously fill them--remains largely absent from modern AI. Here, we p

Enhancing Table Reasoning with Deterministic Table-State Rewards

arXiv:2601.22530v2 Announce Type: replace Abstract: Large Language Models (LLMs) struggle with multi-step reasoning over structured tables. The primary reason is the lack of explicit supervision for i

researcharxiv-cs-ai

Enhancing the Code Reasoning Capabilities of LLMs via Consistency-based Reinforcement Learning

arXiv:2605.17958v1 Announce Type: new Abstract: Code reasoning refers to the task of predicting the output of a program given its source code and specific inputs. It can measure the reasoning capabili

Enhancing Train-Free Infinite-Frame Generation for Consistent Long Videos

arXiv:2605.18233v1 Announce Type: new Abstract: Without incurring significant computational overhead, train-free long video generation aims to enable foundation video generation models to produce long

safetyarxiv-cs-cv

Ensembling Tabular Foundation Models - A Diversity Ceiling And A Calibration Trap

arXiv:2605.18696v1 Announce Type: cross Abstract: Tabular foundation models (TFMs) now match or beat tuned gradient-boosted trees on a growing fraction of tabular tasks, but no single TFM wins on ever

Enterprise AI is ready — Michael Dell says executives need to be, too

AI infrastructure is no longer just about faster computing. It is becoming the foundation for a new enterprise operating model where data comes alive, digital workers reshape workflows and leadership

applicationssiliconangle

Enterprise AI startup Unframe raises 50M after booking 100M in contract value in year one

Enterprise artificial intelligence platform startup Unframe Inc. today announced that it has raised 50 million in new funding to expand delivery capacity, invest further in its platform and build out

applicationssiliconangle

Entropy-Gradient Inversion: Moving Toward Internal Mechanism of Large Reasoning Models

arXiv:2605.17770v1 Announce Type: new Abstract: The advancement of Large Reasoning Models (LRMs) has catalyzed a paradigm shift from reactive ``fast thinking'' text generation to systematic, step-by-s

safetyarxiv-cs-ai

EnvFactory: Scaling Tool-Use Agents via Executable Environments Synthesis and Robust RL

arXiv:2605.18703v1 Announce Type: new Abstract: Equipping LLMs with tool-use capabilities via Agentic Reinforcement Learning (Agentic RL) is bottlenecked by two challenges: the lack of scalable, robus

agentsarxiv-cs-cl

EPIC-Bench: A Perception-Centric Benchmark for Fine-Grained Embodied Visual Grounding in Vision-Language Models

arXiv:2605.17070v1 Announce Type: new Abstract: While large vision-language models (VLMs) are increasingly adopted as the perceptual backbone for embodied agents, existing benchmarks often rely on que

Episodic-Semantic Memory Architecture for Long-Horizon Scientific Agents

arXiv:2605.17625v1 Announce Type: new Abstract: As Large Language Models (LLMs) evolve into persistent scientific collaborators, context window saturation has emerged as a critical bottleneck. Scienti

Equilibrium Selection in Multi-Agent Policy Gradients via Opponent-Aware Basin Entry

arXiv:2605.18078v1 Announce Type: new Abstract: Multi-agent policy-gradient methods have been shown to converge locally near stable Nash equilibria. Local convergence, however, does not determine whic

safetyarxiv-cs-lg

Error-Decomposed Class-Conditional Fusion for Statistically Guaranteed Hard-Category Robust Perception

arXiv:2605.17591v1 Announce Type: new Abstract: Aggregate object detection metrics inherently mask catastrophic and repeatable failures in operationally critical, long-tail minority classes. This pape

ESI-Bench: Towards Embodied Spatial Intelligence that Closes the Perception-Action Loop

arXiv:2605.18746v1 Announce Type: cross Abstract: Spatial intelligence unfolds through a perception-action loop: agents act to acquire observations, and reason about how observations vary as a functio

Estimating Item Difficulty with Large Language Models as Experts

arXiv:2605.18562v1 Announce Type: cross Abstract: Accurate estimates of item difficulty are essential for valid assessment and effective adaptive learning. However, for newly created tasks, response d

safetyarxiv-cs-ai