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Dynamic Semantic Compression for Efficient Latent-Space Inference in Large Language Models

arXiv:2609.15338v1 Announce Type: cross Abstract: Large Language Models (LLMs) primarily perform inference at the token level, resulting in substantial memory overhead and compromised computational ef

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Dynamics-Informed Reinforcement Learning for Agile and Energy-Efficient Locomotion of a Monopedal Hopping Quadcopter

DGX agent

arXiv:2609.15399v1 Announce Type: new Abstract: Although aerial-legged robots offer combined agility and efficiency, controlling high-speed hopping under complex hybrid dynamics is challenging. Reinfo

safetyarxiv-cs-ro

15 Sept 2026

DynEoMT: Learning Object Dynamicity from Online Segmentation Queries

model-releasesarxiv-cs-cv

arXiv:2609.14466v1 Announce Type: new Abstract: Video segmentation models recognize and track objects over time, but they do not indicate whether each segmented region moves independently of the obser

Local Ai

DynSTEER: Dynamic Stage-wise Trajectory Evaluation and Execution-time Review for Agents

arXiv:2609.14637v1 Announce Type: new Abstract: Large language model agents are increasingly deployed for long-horizon task execution. However, current evaluation paradigms face three major limitation

local-aiarxiv-cs-ai

E2A-Bench: Benchmarking Evidence-to-Action Reliability in Financial Chart Reasoning

model-releasesarxiv-cs-cl

arXiv:2609.14302v1 Announce Type: new Abstract: Can financial vision-language models (VLMs) turn chart evidence into reliable action recommendations? Existing hallucination evaluations are mostly clai

Early Prediction of Satellite Collision Probability Using a Hybrid TCN-Transformer Model for a CDM-Based Conjunction Analysis Framework

arXiv:2609.13191v1 Announce Type: new Abstract: The rapid expansion of operational satellites and orbital debris has increased the frequency of close approach events in low Earth orbit (LEO), creating

Early-Stopping Thresholds for ES-HyperNEAT: A Data-Driven Approach from Fitness Dynamics

arXiv:2609.13533v1 Announce Type: cross Abstract: Most hyperparameter configurations for Evolvable-Substrate HyperNEAT (ES-HyperNEAT) produce networks that stagnate at random-guessing performance, was

EB-gMCR: Energy-Based Generative Modeling for Signal Unmixing and Multivariate Curve Resolution

arXiv:2507.23600v5 Announce Type: replace Abstract: A single measurement of a chemical mixture, a reaction mixture, a natural extract, or a tissue, records the sum of the profiles of the few component

ECAS: An Edge-Controlled Agentic System for Validation-Gated Scientific Application Execution

arXiv:2609.14211v1 Announce Type: cross Abstract: Scientific applications increasingly rely on high-performance computing (HPC), yet translating a scientist's high-level goal into a correct target-sca

safetyarxiv-cs-ai

Echo-CoPilot: A Multiple-Perspective Agentic Framework for Reliable Echocardiography Interpretation

arXiv:2512.09944v4 Announce Type: replace Abstract: Echocardiography interpretation requires integrating multi-view temporal evidence with quantitative measurements and guideline-grounded reasoning, y

Echo-E^3Net: Efficient Endocardial Spatio-Temporal Network for Ejection Fraction Estimation

arXiv:2503.17543v4 Announce Type: replace-cross Abstract: Left ventricular ejection fraction (LVEF) is a primary marker of cardiac function. However, routine estimation from endocardial measurements r

researcharxiv-cs-cv

EcoBoat: Design and Experimental Validation of an Autonomous Body-Board Boat For Cleaning Water Bodies

arXiv:2609.14450v1 Announce Type: new Abstract: Cleaning water bodies such as swimming pools and lakes typically demands significant manual effort or reliance on costly, sensor-intensive robotic syste

agentsarxiv-cs-ro

Edge-addition monotonicity of positive p-energy fails for every p >= 1

arXiv:2609.13476v1 Announce Type: cross Abstract: At a 2021 AIM workshop, Guo conjectured that the positive square energy s+ = E+_2 should inherit the familiar edge-addition monotonicity of the spectr

Applications

EdgeHAR: An Edge-Native Compact Sensor Foundation Model for Human Activity Recognition

arXiv:2609.14498v1 Announce Type: cross Abstract: Sensor-based human activity recognition (HAR) is fundamental to ubiquitous and wearable computing, yet existing foundation models are largely designed

applicationsarxiv-cs-ai

Editorial routing shapes how computational results are qualified in AI-assisted scientific writing

model-releasesarxiv-cs-cl

arXiv:2609.14288v1 Announce Type: new Abstract: Large language models increasingly analyze computational results and draft manuscripts, making reliable communication as important as correct analysis.

Local Ai

EECTracker: Swarm Motion Prior-Guided Feature Compensation for Airborne Optical UAV Swarm Tracking

arXiv:2609.15171v1 Announce Type: new Abstract: Airborne optical tracking of uncrewed aerial vehicle (UAV) swarms is challenging due to extremely small target scales, rapid viewpoint changes, and clut

local-aiarxiv-cs-cv

EEG-Xplain: Decoding Neural Black-Boxes of EEG Foundation Models

arXiv:2609.15687v1 Announce Type: new Abstract: EEG foundation models such as BIOT, LaBraM, and EEGMamba have achieved remarkable performance in neural signal decoding, but their black-box nature limi

Efficiency Hallucination: Formalizing and Measuring Behavioral Calibration in LLM-Based Code Optimization

arXiv:2609.14839v1 Announce Type: cross Abstract: The integration of Large Language Models (LLMs) into automated code optimization introduces a critical reliability risk we term the Efficiency Halluci

Efficient On-Device Agents via Adaptive Context Management

arXiv:2511.03728v2 Announce Type: replace Abstract: On-device AI agents offer the potential for personalized, low-latency assistance, but their deployment is fundamentally constrained by limited memor

Efficient Online Inverse Optimization with O(d) Regret

arXiv:2609.13440v1 Announce Type: new Abstract: We give a deterministic algorithm for online inverse linear optimization with regret O(d), uniform in the horizon and O(d^{2}) time per round. A bound o

EI-DDLGN: Efficient Encrypted Inference with Deep Differentiable Logic Gate Networks under TFHE

arXiv:2609.13636v1 Announce Type: cross Abstract: Privacy-preserving inference via Torus Fully Homomorphic Encryption (TFHE) provides strong protection for sensitive data in outsourced deep learning a

Eigenvalue-Decomposition Cost Denoising as an Alternative to Predict-then-Optimize for Shortest-Path Problems

model-releasesarxiv-cs-lg

arXiv:2609.15111v1 Announce Type: cross Abstract: Predict-then-optimize methods such as Smart 'Predict, then Optimize' (SPO+) of Elmachtoub and Grigas (2022) learn a mapping from contextual features t

El Agente Potente: High-Throughput Agentic Atomistic Simulations

arXiv:2609.14840v1 Announce Type: new Abstract: Foundational machine-learning interatomic potentials (MLIPs) are transforming atomistic simulations by achieving near-ab initio accuracy across large ch

Elon just gave a much more practical explanation of the current AI safety problem....and laid out a practical framework for making frontier …

Elon just gave a much more practical explanation of the current AI safety problem....and laid out a practical framework for making frontier AI safer OpenAI and Anthropic are the two leading AI compani

safetyelon-musk--x

Elon just gave one of the clearest explanations yet for why Terafab has to exist There are basically two problems: • Geopolitical risk — at …

Elon just gave one of the clearest explanations yet for why Terafab has to exist There are basically two problems: • Geopolitical risk — at some point, advanced chips from Taiwan may not be available

agentselon-musk--x

ELON MUSK: I saw some pretty funny jokes on 𝕏. One of them I saw was: 'Your girlfriend's a 10, but she's a benchmark maxxer.' 🤣

model-releaseselon-musk--x

ELON MUSK: I saw some pretty funny jokes on 𝕏. One of them I saw was: 'Your girlfriend's a 10, but she's a benchmark maxxer.' 🤣 Media All-In Summit: Elon Musk & Gwynne Shotwell -- AI Risks and Peer Re

Embracing Flow Unsteadiness: A High-Throughput Learning Platform Enables Vortex-Exploiting Bioinspired Propulsion

arXiv:2609.14254v1 Announce Type: cross Abstract: Biological swimmers and flyers exploit unsteady vortices for propulsion, whereas engineered vehicles usually suppress them as disturbances. Learning s

researcharxiv-cs-ro

EMCStereo: Attention-Enhanced Stereo Matching for Thin-Structure Depth Estimation with a Synthetic Tree-Branch Benchmark

model-releasesarxiv-cs-cv

arXiv:2609.13233v1 Announce Type: new Abstract: Thin structures such as tree branches are among the hardest cases for stereo matching: a branch is only a few pixels wide, the background is cluttered,

EMoG: Emotion-Modulated Gait Generation for Expressive Humanoid Locomotion

arXiv:2609.14432v1 Announce Type: new Abstract: Existing humanoid locomotion systems primarily focus on stability and task execution, while integrating expressiveness with explicit locomotion control

safetyarxiv-cs-ro

Empathy Is Steerable but Multi-Axial: Mechanism Geometry and Persona Effects in LLMs

arXiv:2609.15654v1 Announce Type: new Abstract: Activation steering has been used to control traits such as honesty, refusal, and sycophancy, yet supportive empathy is evaluated along multiple dimensi

researcharxiv-cs-cl

Empirical Evaluation of Open-Source Large Language Models for Retrieval-Augmented Generation in ESG Domain

arXiv:2609.15242v1 Announce Type: new Abstract: Environmental, Social, and Governance (ESG) reporting is critical for corporate accountability, with Large Language Models (LLMs) and Retrieval-Augmente

Empirical Evaluation of Task-Based Permission Scoping Architecture for AI Agents

arXiv:2609.15422v1 Announce Type: new Abstract: AI agents are provisioned the same as employee-owned hosts in many enterprise settings with a static credential set fixed at deployment which includes a

EMR: Self-Evolving Medical Multi-Agent System via Experience Mining and Reuse

arXiv:2609.15161v1 Announce Type: cross Abstract: Large language model (LLM) driven multi-agent systems have shown promise in complex clinical reasoning, yet existing approaches rely on static strateg

Enabling Creative Exploration for Vibe Design Agents

arXiv:2609.15078v1 Announce Type: new Abstract: Vibe design agents turn natural-language briefs into rendered interfaces and frontend code. Yet a useful design agent should do more than produce one va

Enabling Population-Based Architectures for Neural Combinatorial Optimization

arXiv:2601.08696v2 Announce Type: replace-cross Abstract: Neural Combinatorial Optimization (NCO) has mostly focused on learning policies, typically neural networks, that operate on a single candidate

Enabling Streaming User Transcription in Full-Duplex Speech-to-Speech Models

arXiv:2609.15759v1 Announce Type: new Abstract: Full-duplex speech-to-speech (S2S) models enable natural conversational AI by allowing simultaneous listening and speaking. However, these models typica

agentsarxiv-cs-cl

End-to-End Cell Detection via Instance-aware Graph Modeling

arXiv:2609.15354v1 Announce Type: cross Abstract: Accurate cell detection and classification are crucial for pathological analysis, directly affecting diagnostic accuracy and treatment planning. To ca

End-to-End Verifiable and Robust Federated Learning

arXiv:2609.15521v1 Announce Type: new Abstract: Federated learning enables multiple parties to train a shared model without centralizing raw data with the help of an aggregator, but introduces integri

Enemray: Toward Capable Language Models for Hassaniya

arXiv:2609.14829v1 Announce Type: cross Abstract: We introduce Enemray, a Hassaniya-centric language model that enables general-purpose interaction in Hassaniya. Enemray is trained around a stability-

Enhancing Event Candidate Acquisition for Event Linking

arXiv:2609.13670v1 Announce Type: new Abstract: Event linking associates event mentions in text with entries in a knowledge base (KB), or identifies them as out-of-KB events. Although existing methods

Enhancing Large Language Model-Based Systems for End-to-End Circuit Analysis Problem Solving

arXiv:2512.10159v3 Announce Type: replace-cross Abstract: LLMs have shown strong performance in data-rich domains such as programming, but their reliability in engineering tasks remains limited. Circu

Ensemble Complexity in Photovoltaic Forecasting

arXiv:2609.15049v1 Announce Type: cross Abstract: An ensemble can improve photovoltaic forecasts while adding components that contribute little or increase computation. We assess these effects through

Ensemble-Conditioned Molecular Design

arXiv:2609.15077v1 Announce Type: new Abstract: Molecular design is typically approached as a problem of finding molecules which can adopt a single bioactive conformation. In reality, molecules occupy

Entropy-Punctured Bloom Filters for Memory-Efficient Machine Learning

arXiv:2609.14187v1 Announce Type: cross Abstract: Memory-efficient feature representations are increasingly important in machine learning settings where storage, transmission cost, bandwidth, or priva

Equilibrium bias and convergence in augmented primal--dual dynamics with sampled constraints

arXiv:2609.13925v1 Announce Type: cross Abstract: This work studies the stability and convergence of augmented primal-dual dynamics when constraint values are estimated from samples. Unbiased constrai

safetyarxiv-cs-lg

ER-EDF: A Psychology-Grounded Emotion Regulation Framework for Speech Empathetic Dialogue Generation in Large Audio-Language Models

arXiv:2609.15089v1 Announce Type: new Abstract: Empathetic response generation in spoken dialogue systems requires both accurate emotion perception and appropriate emotion regulation. Grounded in psyc

tutorialsarxiv-cs-ai

Ergodic Control and Controlled Diffusion for Robot Learning: Review and Tutorial

arXiv:2609.13295v1 Announce Type: cross Abstract: Diffusion learning leverages the statistical mechanism of diffusion processes for learning, reasoning, and inferring complex distributions from data.

Applications

Ergodic Trajectory Planning with Dynamic Sensor Footprints

arXiv:2512.08661v2 Announce Type: replace Abstract: This paper addresses the problem of trajectory planning for information gathering with a dynamic and resolution-varying sensor footprint. Ergodic pl

applicationsarxiv-cs-ro