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Efficient-VLN: A Simple yet Strong Baseline for Efficient Vision-Language Navigation

arXiv:2512.10310v2 Announce Type: replace Abstract: While Multimodal Large Language Models (MLLMs) have demonstrated significant promise in Vision-Language Navigation (VLN), existing agents remain hea

agentsarxiv-cs-cv

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EfficientUICoder: A Bidirectional Token Compression Framework for Efficient MLLM-Based UI Code Generation

DGX agent

arXiv:2509.12159v2 Announce Type: replace-cross Abstract: Multimodal Large Language Models have demonstrated exceptional performance in UI2Code tasks, significantly enhancing website development effic

researcharxiv-cs-ai

30 Jun 2026

Em-ergence of the em-dash: a population-level rise in em-dash frequency in medRxiv preprints at the dawn of the large-language-model era

arXiv:2606.29540v1 Announce Type: cross Abstract: Large language models (LLMs) can leave subtle stylistic traces in assisted text; one of the most cited is the em-dash (Unicode U+2014). Yet no one has

Em-Garde: A Propose-Match Framework for Proactive Streaming Video Understanding

arXiv:2603.19054v2 Announce Type: replace-cross Abstract: Recent advances in Streaming Video Understanding has enabled a new interaction paradigm where models respond proactively to user queries. Curr

Embodiment Meets Environment: Toward Context-Aware, Safe Physical Caregiving Robots

arXiv:2606.28592v1 Announce Type: new Abstract: Physical caregiving robots need to assist different users with different tasks in diverse environments, and they come in many embodiments. While substan

applicationsarxiv-cs-ro

Emergence of a Shared Canonical Object Frame from In-the-Wild Videos

arXiv:2606.30058v1 Announce Type: new Abstract: Comparing object orientations and positions across different instances requires their poses to be expressed in a shared canonical frame. Establishing su

Emergence of Minimal Circuits for Indirect Object Identification in Attention-Only Transformers

arXiv:2510.25013v2 Announce Type: replace-cross Abstract: Mechanistic interpretability aims to reverse-engineer large language models (LLMs) into human-understandable computational circuits. However,

EMPATH: A Multilingual Auditor-Judge Benchmark for Safety Evaluation of Emotional-Support Chatbots

arXiv:2606.30256v1 Announce Type: new Abstract: Safety benchmarks often buy scalability by fixing the prompt, the language, and the turn structure. For emotional-support chatbots, that bargain hides p

Empirical Evaluation of Multi-Modal Touch Detection in Over-the-Shoulder Video Surveillance

arXiv:2606.29504v1 Announce Type: new Abstract: Video Intelligence Surveillance (VIDINT) on over-the-shoulder footage is a proposed vector for monitoring human-computer interaction patterns without di

Empowering a Single-Frequency GNSS Receiver to Achieve High-Precision Positioning with Relative Observations

arXiv:2606.29192v1 Announce Type: new Abstract: Global Navigation Satellite System (GNSS) navigation is widely used to provide absolute, outdoor positioning in field robotics. Advances in Real-Time Ki

agentsarxiv-cs-ro

ENC-ODE: Event-level Neurodegenerative Modeling in Continuous Time with Neural ODEs

arXiv:2606.30398v1 Announce Type: new Abstract: Accurately predicting the temporal evolution of clinical biomarkers is crucial for the early diagnosis and management of neurodegenerative diseases such

End-to-End Facial Expression Detection in Long Videos

arXiv:2504.07660v2 Announce Type: replace Abstract: Facial expression detection requires spotting when expressions occur and recognizing which emotional category they belong to. Despite their close re

applicationsarxiv-cs-cv

Hardware

Enhanced Diffusion Sampling: Efficient Rare Event Sampling and Free Energy Calculation with Diffusion Models

arXiv:2602.16634v2 Announce Type: replace-cross Abstract: The rare-event sampling problem has long been the central limiting factor in molecular dynamics (MD), especially in biomolecular simulation. R

hardwarearxiv-cs-ai

Enhancing Automatic Chord Recognition via Pseudo-Labeling and Knowledge Distillation

arXiv:2602.19778v4 Announce Type: replace-cross Abstract: Automatic Chord Recognition (ACR) is constrained by the scarcity of aligned chord labels, as well-aligned annotations are costly to acquire. A

researcharxiv-cs-lg

Enhancing Layer Interaction Using Key-Correlated Layer Attention

arXiv:2606.28405v1 Announce Type: new Abstract: Recent advances in network architecture design have introduced layer attention to enhance inter-layer interactions. In such frameworks, each layer queri

Enhancing Part-Level Point Grounding for Any Open-Source MLLMs

arXiv:2606.29267v1 Announce Type: new Abstract: Visual grounding aims to associate free-form textual queries with specific regions in an image. While recent Multimodal Large Language Models (MLLMs) ha

Ensemble Learning Based Classification Algorithm Recommendation

arXiv:2101.05993v2 Announce Type: replace-cross Abstract: Selecting an appropriate classification algorithm for a given data set remains a challenging problem in data mining and machine learning. Exis

Entity Binding Failures in Tool-Augmented Agents

arXiv:2606.30531v1 Announce Type: new Abstract: Tool-augmented language-model agents are often evaluated by whether they select the correct tool, produce valid API arguments, and complete the requeste

safetyarxiv-cs-ai

Entropy-Gated Latent Recursion

arXiv:2606.16620v2 Announce Type: replace-cross Abstract: Inference-time scaling has become the dominant lever for improving language-model reasoning, but existing methods derive rollout diversity fro

Entropy-Regularized Reinforcement Learning for Linear-Quadratic Stackelberg Differential Games in Regime-Switching Diffusion Models

arXiv:2606.28671v1 Announce Type: new Abstract: Stackelberg differential games (SDGs) provide a powerful framework for hierarchical decision-making in stochastic and continuous-time environments, yet

researcharxiv-cs-lg

Entropy Regularized Reinforcement Learning for Zero-Sum Stochastic Differential Games in a Regime-Switching Jump-Diffusion Process

model-releasesarxiv-cs-lg

arXiv:2606.28669v1 Announce Type: new Abstract: To address parameter misspecification and sudden structural environmental changes in conventional stochastic differential game (SDG) frameworks, this pa

EntroRouter: Learning Efficient Model Routing via Entropy Regulation

arXiv:2606.29424v1 Announce Type: new Abstract: Model routing balances solution accuracy and computational cost by selecting among models of varying capabilities. While recent multi-round frameworks i

safetyarxiv-cs-cl

Envisage: Diffusion-Based Rhinoplasty Goal Visualization with Mask-Decomposed Evaluation

model-releasesarxiv-cs-cv

arXiv:2606.28628v1 Announce Type: cross Abstract: Localized generative editing needs localized evaluation: full-image identity metrics are structurally confounded under hard-composited edits. We prese

EPIC-EuroParl-UdS: Information-Theoretic Perspectives on Translation and Interpreting

arXiv:2603.09785v3 Announce Type: replace Abstract: This paper introduces an updated and combined version of the bidirectional English-German EPIC-UdS (spoken) and EuroParl-UdS (written) corpora conta

safetyarxiv-cs-cl

EpiSAM: Character Segmentation in Challenging Stone Inscriptions

arXiv:2606.28859v1 Announce Type: new Abstract: Stone inscriptions are invaluable sources of historical and linguistic knowledge, yet their automated analysis remains a major challenge due to surface

EraseLoRA: MLLM-Driven Foreground Exclusion and Background Subtype Aggregation for Dataset-Free Object Removal

arXiv:2512.21545v2 Announce Type: replace Abstract: Object removal must prevent the masked target from reappearing and reconstruct the occluded background with structural and contextual fidelity, rath

safetyarxiv-cs-cv

Establishing the Minimal Clinically Important Difference (MCID) for Smartphone-Derived Gait Measures in Multiple Sclerosis

arXiv:2606.28449v1 Announce Type: cross Abstract: Background: Digital health technologies allow for frequent, remote gait monitoring in people with multiple sclerosis (MS). However, to differentiate d

applicationsarxiv-cs-cv

Estimating Grammatical Gender Directions in Contextual Embeddings under Controlled and Natural Contexts

arXiv:2606.30152v1 Announce Type: cross Abstract: Contextual language models conflate grammatical gender and social semantic bias in gendered languages such as Spanish. Existing gender debiasing appro

safetyarxiv-cs-ai

EVAF: A Test-Retest Protocol for Selective Parametric Consolidation

arXiv:2606.29916v1 Announce Type: cross Abstract: Long-running language agents need mechanisms for deciding which experiences should persist after the working context is gone. Retrieval systems can re

Eval-Actions: Fine-Grained Execution Quality Evaluation for Robotic Manipulation

model-releasesarxiv-cs-ro

arXiv:2601.18723v2 Announce Type: replace Abstract: Although Vision--Action (VA) and Vision--Language--Action (VLA) policies have advanced robotic manipulation, their evaluation remains dominated by b

EvalSafetyGap: A Hybrid Survey and Conceptual Framework for LLM Evaluation-Safety Failures

arXiv:2606.30219v1 Announce Type: new Abstract: LLM evaluation and AI safety face a shared measurement problem: benchmark scores, reward-model signals, and reported safety metrics can improve while th

Evaluating LLMs on Chinese Topic Constructions: A Research Proposal Inspired by Tian et al. (2024)

arXiv:2504.14969v2 Announce Type: replace Abstract: This paper proposes a framework for evaluating large language models (LLMs) on Chinese topic constructions, focusing on their sensitivity to island

researcharxiv-cs-cl

Evaluating Memory in LLM Agents via Incremental Multi-Turn Interactions

arXiv:2507.05257v4 Announce Type: replace-cross Abstract: Recent benchmarks for Large Language Model (LLM) agents primarily focus on evaluating reasoning, planning, and execution capabilities, while a

Evaluating Newtonian Mechanics in Video Generative Models with Real Physical Systems

arXiv:2504.02918v3 Announce Type: replace Abstract: Recent advances in image and video generation raise hopes that these models possess world modeling capabilities-the ability to generate realistic, p

agentsarxiv-cs-cv

Tutorials

Event-Conditioned Diagnostics of Kinematic, Contact, and Object-Permanence Fields in Passive Object-State World Models

arXiv:2606.28455v1 Announce Type: cross Abstract: World models can predict future physical states, but prediction accuracy alone does not explain how physical information is organized and used inside

tutorialsarxiv-cs-ai

Event-VLA: Action-Conditioned Event Fusion for Robust Vision-Language-Action Model

arXiv:2606.29384v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have become an important paradigm of embodied AI. However, existing VLA models typically assume well-lit and stable

applicationsarxiv-cs-cv

EventVLA: Event-Driven Visual Evidence Memory for Long-Horizon Vision-Language-Action Policies

model-releasesarxiv-cs-cv

arXiv:2606.20092v2 Announce Type: replace Abstract: Memory remains a critical bottleneck for long-horizon robotic manipulation, as standard Vision-Language-Action (VLA) policies often fail when task-r

Evidence-Based Text-Conditioned 3D CT Synthesis for Ovarian Cancer

arXiv:2606.28980v1 Announce Type: cross Abstract: Ovarian cancer is frequently diagnosed at an advanced stage, making preoperative contrast-enhanced computed tomography (CT) central to staging and sur

safetyarxiv-cs-ai

Evidence-Driven LLM Agent for C-to-Synthesizable-C Conversion and Verification

arXiv:2606.28409v1 Announce Type: cross Abstract: Software-compilable C programs routinely fail to complete the four-stage pipeline of a high-level synthesis (HLS) toolchain -- compilation, C simulati

agentsarxiv-cs-ai

Evidence-Informed LLM Beliefs for Continual Scientific Discovery

arXiv:2606.29182v1 Announce Type: new Abstract: Open-ended scientific discovery with large language models (LLMs) increasingly operates as a long-horizon loop of hypothesis search and verification, wh

EVLA: An Electro-Aware Multimodal Assistant for Physically-Grounded Driving Reasoning and Control

model-releasesarxiv-cs-cl

arXiv:2606.28938v1 Announce Type: new Abstract: Modern vision-language models (VLMs) for driving assistants typically treat vehicle dynamics as a black box, resulting in decisions that lack awareness

EvLIR: Learning Illumination Residuals from Ordered Events for Low-Light Image Enhancement

arXiv:2606.29430v1 Announce Type: new Abstract: Low-light image enhancement is severely ill-posed when the input frame contains missing structure, saturated noise, and weak local contrast. Event camer

Hardware

Evolution Fine-Tuning: Learning to Discover Across 371 Optimization Tasks

arXiv:2606.29082v1 Announce Type: new Abstract: Would experience designing faster GPU kernels also help close in on a long-standing open mathematical conjecture? Large Language Models (LLMs) integrate

hardwarearxiv-cs-cl

Evolutional Math: Cross-Validated Island-Model Genetic Programming for Interpretable Symbolic Regression on Small, Wide Datasets

arXiv:2606.28381v1 Announce Type: cross Abstract: Symbolic regression via genetic programming routinely fails on small, wide datasets - a regime common in clinical-trial monitoring, biostatistics, and

Evolutionary Hyperparameter Optimization to Find Lightweight CNN Models for Autonomous Steering

arXiv:2606.29684v1 Announce Type: cross Abstract: This research investigates the optimization of Convolutional and Dense Neural Networks (CNNs and DNNs) for autonomous steering using the (N+M) Evoluti

agentsarxiv-cs-cv

Local Ai

ExACT: Exemplar-Driven Calibrated Refinement for Training-Free Visual Grounding in Remote Sensing Images

arXiv:2606.28920v1 Announce Type: new Abstract: Remote sensing visual grounding (RSVG) aims to locate specific objects in high-resolution RS imagery using free-form natural language descriptions. Whil

local-aiarxiv-cs-cv

Exit-and-Join Dynamics and Equilibrium in Continuum Cooperative Games

arXiv:2606.28824v1 Announce Type: cross Abstract: This paper develops a continuum theory of exit-and-join coalition dynamics in nonatomic cooperative games. We extend the Aumann-Shapley value and the

agentsarxiv-cs-ai

Experience Augmented Policy Optimization for LLM Reasoning

model-releasesarxiv-cs-lg

arXiv:2606.30420v1 Announce Type: new Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) is a powerful paradigm for improving the reasoning capabilities of large language models (LLMs). H