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EgoCPT: Learning Dexterous Manipulation from a Single Ego-Centric Video with Contact-Aware Optimization

arXiv:2610.17572v1 Announce Type: new Abstract: While expert demonstrations on real robots are difficult to collect, human ego-centric videos are easy to collect and abundant on the internet. However,

researcharxiv-cs-ro

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Human DGX agent

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Research

EgoExplorer: A Vision-Motion-Touch Observatory for Human Loco-Manipulation In Situ

DGX agent

arXiv:2610.18872v1 Announce Type: cross Abstract: Learning humanoid loco-manipulation from human demonstrations rests on observing how locomotion, posture, and object interaction evolve together as ta

researcharxiv-cs-cv

14 Oct 2026

EgoMatrix: Physically Faithful Dexterous Robot Demonstrations from Egocentric Human Videos

arXiv:2610.18822v1 Announce Type: new Abstract: Egocentric human videos offer a scalable alternative to robot teleoperation for collecting dexterous manipulation data. However, two challenges limit th

EgoOmniWorld: Unifying Egocentric Understanding via Ego-Action-World Interactions

arXiv:2610.18499v1 Announce Type: new Abstract: Egocentric video understanding spans diverse capabilities, modalities, and evaluation formats, yet these are often studied in isolation despite their ti

EgoProbe: Benchmarking Long-Range and Exact Memory in Streaming Egocentric Videos

arXiv:2610.17128v1 Announce Type: new Abstract: Egocentric video provides a continuous first-person record of everyday activities, making it a natural foundation for wearable AI assistants. Unlike off

EgoWholeView: Camera-Only Head-Mounted Capture of Body and Bimanual Hand Motion for Embodied Demonstrations

arXiv:2610.16256v1 Announce Type: new Abstract: Head-mounted body and bimanual motion capture supports self-avatars, teleoperation, and embodied demonstrations. However, a single egocentric camera is

ELECT: Settling Identity Before Rendering for Scalable Story Visualization

arXiv:2610.15555v1 Announce Type: new Abstract: Training-free story visualization without reference images must preserve recurring entities across frames while scaling to long narratives. Existing met

Elephant in the Fridge: Constant-Memory Frame Packing for Long Video Understanding

arXiv:2610.16118v1 Announce Type: new Abstract: Hour-long videos, streaming feeds, and movie-length content are pushing vision-language models (VLMs) past their breaking point -- the standard recipe o

Ellipsoids from Tangents

arXiv:2610.15580v1 Announce Type: new Abstract: This paper presents an algorithm for detecting and fitting multiple ellipsoids in 2D, 3D and higher-dimensional data. The representation is based on tan

ELVIS: Enhance Low-Light for Video Instance Segmentation in the Dark

arXiv:2512.01495v3 Announce Type: replace Abstract: Video instance segmentation (VIS) for low-light content remains highly challenging for both humans and machines alike, due to noise, blur and other

researcharxiv-cs-cv

Applications

Embedding Graph Kernel Entropy (EGKE): Fine-grained Hallucination Detection for LLMs from Embeddings

arXiv:2610.14214v1 Announce Type: new Abstract: Hallucination detection is critical for ensuring the reliability of Large Language Models (LLMs) in real-world deployments. While recent works, such as

applicationsarxiv-cs-lg

Embodied Skill Bench: Benchmarking How Well Agents with Embodied Skills Perform on Physical Tasks

model-releasesarxiv-cs-ro

arXiv:2610.16238v1 Announce Type: new Abstract: LLM agents increasingly control robots using VLA policies, perception models, and procedural knowledge. These modules are difficult to reuse because the

Local Ai

Embodied Zero-Shot Task Planning via Hardware-Aware LLM-VLM Integration for Grounded Robotic Manipulation

arXiv:2610.14106v1 Announce Type: new Abstract: Large language models can translate natural-language instructions into plausible manipulation plans, but robotic execution requires physically grounded

local-aiarxiv-cs-ro

EmbodiedEvo: Self-improving Coding Agents for Physical Intelligence

arXiv:2610.18867v1 Announce Type: new Abstract: Bringing general-purpose agents into the physical world calls for an executable representation of physical intelligence. Compared with vision-language-a

Embodiment-Aware Inference-Time Search for Human Reaction Selection in Humanoid Retargeting

model-releasesarxiv-cs-ro

arXiv:2610.15274v1 Announce Type: new Abstract: Training humanoid robots to learn human behaviors requires expensive data collection, and human-robot interaction data can be even more difficult and co

EmbodiSteer: Steering Embodiment-Agnostic Visuomotor Policies with Joint-Space Guidance for Zero-Shot Cross-Embodiment Deployment

arXiv:2606.12965v2 Announce Type: replace Abstract: Scalable robot imitation learning relies on large-scale heterogeneous data from diverse robots or body-free data, making Cartesian end-effector acti

Emergent Loop Geometry in Gauge-Equivariant Graph Neural Networks

arXiv:2610.18742v1 Announce Type: cross Abstract: Gauge-equivariant graph neural networks generate ordered products of gauge links through local message passing, but the geometry of these internal str

EmoGenie: Benchmarking and Evaluating Expressed and Evoked Emotion in T2I Generation with MLLMs

arXiv:2610.18455v1 Announce Type: new Abstract: Rapid advances in artificial intelligence-generated content (AIGC) have significantly promoted using text-to-image (T2I) models to generate images with

EmoTrace-Bench: Diagnosing Emotional Expression in Text-to-Video Generation through Controlled Cues and Intensity

arXiv:2610.15452v1 Announce Type: new Abstract: Text-to-video (T2V) models are increasingly used to generate videos with targeted emotional expressions, yet existing evaluation methods mainly rely on

Enabling Token-wise Importance Sampling in Off-Policy RLVR with Proximal KL Regularization

arXiv:2610.18738v1 Announce Type: new Abstract: Off-policy data in reinforcement learning with verifiable rewards (RLVR) can arise from asynchronous generation, rollout-training mismatch, and response

EnactOpt: Diagnosis-Guided Harness Evolution for Embodied Agents

arXiv:2610.14977v1 Announce Type: new Abstract: Embodied agents built on foundation models rely on an execution harness to organize observations, guide actions, and incorporate execution feedback into

agentsarxiv-cs-ro

Encoding Context into LLM Weights: What Makes It Context?

arXiv:2610.17686v1 Announce Type: cross Abstract: Longer contexts allow large language models (LLMs) to condition their predictions on more information, but inference costs grow prohibitively with con

End-to-End Spoken Grammatical Error Correction

arXiv:2506.18532v2 Announce Type: replace-cross Abstract: Grammatical Error Correction (GEC) and feedback play a vital role in supporting second language (L2) learners, educators, and examiners. While

Hardware

Energy-Efficient Deep Learning Without Backpropagation: A Rigorous Hardware-Validated Benchmarking Study of Forward-Only Algorithms

arXiv:2511.01061v2 Announce Type: replace Abstract: Backpropagation (BP) powers modern deep learning, but it must hold every activation in memory until a global backward sweep consumes it, and that sw

hardwarearxiv-cs-lg

Tutorials

Energy-Guided Learning for Heat Equation with Noisy Source: Optimal Estimation and Generalization Bounds

arXiv:2610.15111v1 Announce Type: cross Abstract: Data and the governing partial differential equations (PDEs) of continuous-time dynamical systems provide rich structure for statistical learning. A c

tutorialsarxiv-cs-lg

Engram Neuron Inspired Adaptive Memorization for Lifelong Learning

arXiv:2610.14940v1 Announce Type: new Abstract: Lifelong learning enables artificial systems to adapt to changing environments. To achieve this, an effective artificial learner should dynamically reor

Enhanced Trading Systems with Intelligent Market Analysis

arXiv:2610.13998v1 Announce Type: new Abstract: This paper proposes a hybrid reinforcement learning trading framework integrating intraday market data with transformer-based financial sentiment signal

agentsarxiv-cs-lg

Applications

Enhancing Zero-Shot Domain Transfer in Low-Resource Sentiment Analysis: A Case Study in Marathi

arXiv:2610.15757v1 Announce Type: cross Abstract: Sentiment analysis is a key task in Natural Language Processing that determines the polarity of opinions in text. For low-resource languages like Mara

applicationsarxiv-cs-lg

Ensemble-MIX: Enhancing Sample-Efficiency in Multi-Agent RL via Selective Ensemble-Based Exploration

arXiv:2506.02841v5 Announce Type: replace-cross Abstract: Multi-agent reinforcement learning (MARL) methods have achieved state-of-the-art results on a range of multi-agent tasks. Yet, MARL algorithms

Entropy-Regularized Mean-Field Games with Average-Reward Criterion: Span-Seminorm Contractions and Model-Free Learning

arXiv:2610.15871v1 Announce Type: cross Abstract: We study stationary discrete-time mean-field games with finite state and action spaces under the average-reward criterion, with an entropy-regularized

EqC: Equilibrium Energy Control for Introspective Lifelong Robot Learning

arXiv:2610.18790v1 Announce Type: new Abstract: Long-term robot autonomy depends on more than effective action generation: a policy must recognize when its behavior is no longer sufficiently supported

Equilibrium contrastive learning for imbalanced image classification

arXiv:2602.09506v4 Announce Type: replace Abstract: Contrastive learning (CL) is a predominant technique in image classification, but they showed limited performance with an imbalanced dataset. Recent

safetyarxiv-cs-cv

Equilibrium Learning in Unbounded Stochastic Games with Gaussian Transitions

arXiv:2610.16149v1 Announce Type: cross Abstract: Learning equilibria from data is difficult when several decision makers interact indefinitely and the system state has no prescribed bounds. We examin

Local Ai

Error-Based Bidirectional Predictive Coding Enables Deep, 4-Bit Predictive Coding Networks

arXiv:2610.15933v1 Announce Type: new Abstract: Predictive coding networks (PCNs) promise properties not offered by backpropagation-trained networks: learning from purely local information, a single n

local-aiarxiv-cs-lg

Error Correction in Trained TTT Layers

model-releasesarxiv-cs-lg

arXiv:2610.16268v1 Announce Type: new Abstract: Test-time-training (TTT) layers update fast-weight memory while processing an input sequence. A gradient-based update, however, does not by itself estab

Esports World Model Dataset

arXiv:2610.16166v1 Announce Type: new Abstract: Interactive world models must capture how multiple participants jointly change a shared environment while observing different parts of it. Competitive g

safetyarxiv-cs-cv

Estimating the Causal Impact of Social Navigation Signals in Corridor Scenarios

arXiv:2610.16411v1 Announce Type: new Abstract: Deploying robots in human-shared environments requires deciding not only how to navigate, but also when dedicated social signals are worth emitting. Cla

Euclidean Distance-Based Flow Matching

arXiv:2610.18534v1 Announce Type: new Abstract: Flow Matching has recently become popular as a technique for generative modeling with applications in many domains. In the standard Flow Matching formul

Local Ai

EV-JEPA: Elastic V-JEPA for Any Device and Cross-Device Inference

arXiv:2610.14324v1 Announce Type: new Abstract: Foundation models like V-JEPA are increasingly deployed across a heterogeneous edge-cloud continuum spanning smart glasses, phones, robots, and servers.

local-aiarxiv-cs-cv

Evaluating Long-Horizon Robot Planning under Uncertainty

model-releasesarxiv-cs-ro

arXiv:2610.17326v1 Announce Type: new Abstract: Household robots must successfully navigate im-perfect circumstances, both in their internal models and the external world. We introduce a benchmark of

Evaluating the Causal Faithfulness of SHAP as a Candidate Attribution Method for SAE Features

arXiv:2610.17898v1 Announce Type: new Abstract: Sparse autoencoders decompose language model representations into interpretable features, but feature interpretation in this literature remains predomin

Event-Based Visual Teach-and-Repeat via Fast Fourier-Domain Cross-Correlation

arXiv:2509.17287v3 Announce Type: replace-cross Abstract: Visual teach-and-repeat (VT&R) navigation enables robots to autonomously traverse previously demonstrated paths using visual feedback. We pres

agentsarxiv-cs-cv

EventLens: Event-Structure Reinforcement Learning for Video Understanding

arXiv:2610.16172v1 Announce Type: new Abstract: Recent multimodal large language models (MLLMs) achieve strong results on video question answering, yet often fail to recover the temporal structure tha

safetyarxiv-cs-cv

Evidence-First Agentic Verification

model-releasesarxiv-cs-lg

arXiv:2610.17724v1 Announce Type: cross Abstract: Long-horizon, semi-verifiable agentic tasks often rely on rubric-based evaluation, but the evidence needed to assess these tasks can be spread across

EviScene: Beyond 'Is It AI?' for Agentic Image Factuality Assessment

arXiv:2610.14609v1 Announce Type: new Abstract: Determining whether an image is AI-generated does not establish whether the situation it depicts is factually supported. We formulate Image Factuality A

EviStress: Evidence Stress Learning for Generalizable Face Forgery Detection with Textual Explanations

arXiv:2610.16879v1 Announce Type: new Abstract: The rapid spread of face forgeries on the Web challenges the credibility of visual content. In practical Web environments, manipulated media originate f

EvolvAttack: Backdooring self Evolving VLM Agents

arXiv:2610.15244v1 Announce Type: new Abstract: Self-evolving mechanisms let vision-language model (VLM) agents continually adapt through evolving memory, but they also allow malicious behavior to eme

agentsarxiv-cs-lg

EvoSpatial: Experience-Driven Skill and Tool Evolution for Spatial Reasoning Agents

arXiv:2610.16679v1 Announce Type: new Abstract: Tool-augmented vision-language agents compose perception and measurement to reason about spatial relationships, but effective execution also requires tr