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Dual-Anchor Acceleration Is Near-Optimal for Stochastic Monotone Root-Finding

arXiv:2609.36033v1 Announce Type: cross Abstract: Among distinct optimal acceleration mechanisms for deterministic monotone root-finding problems and fixed-point problems, dual-anchoring has recently

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Dual-Channel Robust Group-Relative Policy Optimization via Advantage and Sequence-Weight Estimation

DGX agent

arXiv:2609.36944v1 Announce Type: new Abstract: Group-relative policy optimization relies on reward-derived advantages and sequence-level likelihood weights, both of which can be sensitive to localize

safetyarxiv-cs-ai

30 Sept 2026

Dual-Mode Low-Rank Learner with Bridge-Prototype Ensemble for Vision-Language Class-Incremental Learning

arXiv:2609.36759v1 Announce Type: cross Abstract: Benefiting from transferable visual-textual alignment, CLIP has been widely adopted for class-incremental learning (CIL). However, existing learners e

DualTrack: Synchronized speech-gesture generation via symmetric coupling of pretrained priors

arXiv:2609.36624v1 Announce Type: new Abstract: Joint speech-gesture synthesis must coordinate two modalities despite limited paired data. Existing approaches often lack bidirectional interaction, hav

researcharxiv-cs-ai

Dyad: Extending Large Language Models with Native Typed Decision-Making

arXiv:2609.36116v1 Announce Type: new Abstract: We study how to build more capable general-purpose agents by extending large language models (LLMs) with native typed decision-making. We introduce Dyad

safetyarxiv-cs-lg

Dynamic Optimizations of LLM Ensembles with Two-Stage Reinforcement Learning Agents

arXiv:2502.04492v3 Announce Type: replace Abstract: The advancement of LLMs and their accessibility have triggered renewed interest in multi-agent reinforcement learning as robust and adaptive framewo

safetyarxiv-cs-cl

Dynamic Regret via Discounted-to-Dynamic Reduction with Applications to Curved Losses and Adam Optimizer

arXiv:2602.08372v2 Announce Type: replace Abstract: We study dynamic regret minimization in non-stationary online learning, with a primary focus on follow-the-regularized-leader (FTRL) methods. FTRL i

DynamicHOI: Coupled Dynamics for Physics-aware HOI Reconstruction

arXiv:2609.36454v1 Announce Type: new Abstract: We study hand-object interaction (HOI) reconstruction from monocular RGB videos, where partial observations can produce visually plausible yet mechanica

researcharxiv-cs-cv

E-MoE: Enhanced Mixture-of-Experts for Non-Factorized Diffusion Language Models

arXiv:2609.37533v1 Announce Type: new Abstract: Masked diffusion models (MDMs) generate sequences by progressively unmasking several tokens per denoising step, but their reverse process is typically f

researcharxiv-cs-cl

Early Learning Shapes Later Directions Of Representation Change In Continual Learning

arXiv:2609.36081v1 Announce Type: new Abstract: Representations continually change as a network learns new tasks. We ask whether early representational changes naturally form a geometric structure tha

EASE: Behavior-Adaptive Skill Curation for Self-Evolving Agents

arXiv:2609.36746v1 Announce Type: new Abstract: Agent skills provide a lightweight mechanism for self-evolving agents to accumulate reusable procedural knowledge without updating model parameters. How

EasyPPO: Stabilizing the Critic Is Key

arXiv:2609.36802v1 Announce Type: new Abstract: A key strength of Proximal Policy Optimization (PPO) is its learned critic, which uses historical trajectories collected during reinforcement learning t

safetyarxiv-cs-lg

Effective Dense Retrieval using Only In-Context Examples

arXiv:2609.38099v1 Announce Type: cross Abstract: Turning decoder-only large language models (LLMs) into strong dense retrievers typically requires some form of retriever training. In this paper, we a

researcharxiv-cs-cl

Local Ai

Efficient and Scalable Physics-Guided Fully Convolutional Spatiotemporal Learning for 3D Microstructure Evolution Prediction

arXiv:2609.36504v1 Announce Type: new Abstract: Accurate prediction of three-dimensional (3D) microstructure evolution remains computationally demanding because high-fidelity phase-field simulations r

local-aiarxiv-cs-lg

Applications

Efficient Audiovisual Speech Processing via MUTUD: Multimodal Training and Unimodal Deployment

arXiv:2501.18157v2 Announce Type: replace-cross Abstract: Building reliable speech systems often requires combining multiple modalities, like audio and visual cues. While such multimodal solutions fre

applicationsarxiv-cs-cv

Efficient Offline Learning of Ranking Policies via Top-k Policy Decomposition

arXiv:2609.36740v1 Announce Type: new Abstract: Many recommender systems such as for e-commerce and news platforms aim to provide users with rankings they are likely to interact with. Off-Policy Learn

safetyarxiv-cs-lg

Efficiently Approximating Attention Is Hard

model-releasesarxiv-cs-lg

arXiv:2609.37261v1 Announce Type: new Abstract: Softmax attention is ubiquitous in modern machine learning, but its quadratic scaling with sequence length makes it costly. To reduce this cost, attenti

EgoAlign: Bridging the Human-Humanoid Gap for Long-Range Loco-Manipulation

arXiv:2609.38046v1 Announce Type: new Abstract: Egocentric human demonstrations offer an accessible source of task experience, but differences in body scale and controller response, together with miss

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EgoHumanoid-V2: Human-to-Humanoid Transfer of Coordinated Whole-Body Skills for Loco-Manipulation

arXiv:2609.37181v1 Announce Type: cross Abstract: Human demonstrations capture diverse scenes and rich whole-body skills without requiring robot teleoperation. Prior work on egocentric transfer has em

EGSD: Event-Grounded Self-Distillation for Streaming Video Understanding

arXiv:2609.36803v1 Announce Type: new Abstract: Real-time video understanding requires incrementally maintaining a memory of streaming content, and optimizing this requires dense process signals. On-P

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Elastic ODYN: Differentiable Optimization for Infeasible Control and Learning in Robotics

model-releasesarxiv-cs-ro

arXiv:2606.16564v2 Announce Type: replace Abstract: Robotic systems routinely encounter conflicting objectives, modeling errors, and degenerate contact conditions that render quadratic programs (QPs)

Hardware

Embedded Bi-Temporal Building Damage Assessment for On-Board Data Reduction

arXiv:2609.37013v1 Announce Type: cross Abstract: Rapid assessment of building damage after natural disasters is essential to support emergency response. Earth Observation satellites can acquire relev

hardwarearxiv-cs-ai

Agents

Embodied Semantic Communication for Collective Autonomous Agents: A Tutorial on Representation, Wireless Delivery, and Closed-Loop Coordination

arXiv:2609.35936v1 Announce Type: cross Abstract: As autonomous systems and embodied intelligence enter the dynamic physical world, multi-agent collaboration calls for a paradigm shift in communicatio

agentsarxiv-cs-ai

Emergent phases of superposition: from partial to full representation

arXiv:2609.36455v1 Announce Type: new Abstract: Large language models are thought to represent features by vectors in a hidden space of dimension given by the model's width. Superposition, in which mo

Local Ai

Emergent Specialization in Populations of Self-Supervised Collaborative Vision Experts Without a Shared Gate or Cross-Agent Gradients

arXiv:2609.36770v1 Announce Type: new Abstract: Can a population of neural networks develop a useful division of labor without a shared gate or gradients between agents? We study a setting where each

local-aiarxiv-cs-ai

Emergent Tonal Structure in Learned Chord Embeddings and Its Relation to Tonal Tension

arXiv:2609.36460v1 Announce Type: cross Abstract: Several tonal pitch spaces and computational models have been proposed to analyze tonal structure in Western tonal music, many of them grounded in pri

EmoRES-TTS: Residual-Enhanced Vector Steering for Emotional Speech Generation

arXiv:2609.38157v1 Announce Type: cross Abstract: Emotion-conditioned text-to-speech (TTS) models may fail to express the requested emotion reliably, and improving controllability by additional traini

researcharxiv-cs-cl

Empower your agents with the Google Cloud CLI remote MCP server

model-releasesgoogle-cloud-ai

Today, we’re expanding our ecosystem of managed remote MCP servers by introducing the Google Cloud CLI remote MCP server in preview. Powered by the popular gcloud and bq (BigQuery) command-line tools,

Encoder-Sharing Hierarchical Federated Multi-Task Learning for VANETs

arXiv:2609.36157v1 Announce Type: cross Abstract: Most federated learning frameworks for vehicular ad hoc networks assume that all vehicles collaboratively train a single model for a common task. This

Encore: Few-Shot Agentic Discovery of Manipulation Strategies

arXiv:2609.37359v1 Announce Type: cross Abstract: Coding agents can now write, run, and debug programs with little human help. Robot tasks, however, are usually specified by a sentence that leaves out

End-to-End Optical Semantic Communication over a Nonlinear WDM Fiber Link

arXiv:2609.37551v1 Announce Type: cross Abstract: Emerging optical-network applications increasingly use received data for inference and control rather than exact source reproduction, creating an oppo

End-to-End Self-Supervised RGB-T Tracking without Modality Misleading

arXiv:2609.37162v1 Announce Type: new Abstract: RGB-T object tracking leverages the complementary characteristics of visible and thermal infrared modalities to improve robustness under adverse conditi

safetyarxiv-cs-cv

EndoPrior-GS: Dynamic Endoscopic Reconstruction with a Joint Texture Prior

model-releasesarxiv-cs-cv

arXiv:2609.37874v1 Announce Type: new Abstract: Dynamic endoscopic reconstruction is fundamental to robotic surgery and computer-assisted interventions. While 3D Gaussian Splatting (3DGS) realises rea

EnergyEminence: Source-Aware Environmental Calibration and Evaluation in a Physics-Grounded Grid Digital Twin

arXiv:2609.36215v1 Announce Type: new Abstract: Power-grid digital twins must combine data-driven prediction with physically meaningful state evolution while preserving the provenance of environmental

Engineering Efficient Self-Play Chess: Search, Replay, and Throughput Under Limited Compute

arXiv:2609.37447v1 Announce Type: cross Abstract: How strong can an AlphaZero-style chess system become under limited training compute when its entire learning loop is engineered for efficiency? We tr

Engineering Simplicity: Simple Mechanism Interfaces Steer LLM Agents

arXiv:2609.36365v1 Announce Type: new Abstract: Can interaction formats and textual scaffolds help large language model (LLM) agents make better decisions, and do better decisions come with better exp

EngiWorld: What Can Frontier Agents Deliver in Professional Engineering Environments?

arXiv:2609.37686v1 Announce Type: new Abstract: Autonomous agents have made rapid progress in general-purpose computer use, but reliable automation of professional industrial engineering remains out o

Tutorials

EnJoi: Ensemble Joint Score Filter for Generative Data Assimilation

arXiv:2609.35944v1 Announce Type: new Abstract: Data Assimilation (DA) aims to recover the full state of a dynamical system that is only partially observed. A solution is to use Score-based models to

tutorialsarxiv-cs-lg

EnterpriseBench: Benchmarking LLM Agents on Enterprise-Level Strategic Reasoning and Decision-Making

arXiv:2609.37658v1 Announce Type: new Abstract: LLM agents are increasingly expected to support enterprise workflows, where tasks often involve missing information, uncertainty, feedback, and long-ter

Environment Steering: Using Data Flow Control to Improve Agent Utility and Safety

arXiv:2609.35807v1 Announce Type: cross Abstract: LLM agents can make unsafe tool calls even when instructed to behave safely. Existing defenses constrain agents before execution, modify tool inputs/o

Agents

EpiCon: Collective Agent Learning through Co-Evolving Multimodal Memory

arXiv:2609.37923v1 Announce Type: new Abstract: Agents can learn from past executions, but enabling different agents to reuse and build on one another's experience remains challenging. We introduce Ep

agentsarxiv-cs-cv

Equally Good, Yet Different: Benchmarking Rashomon sets in AutoML packages

model-releasesarxiv-cs-lg

arXiv:2609.36970v1 Announce Type: new Abstract: The Rashomon effect describes the existence of multiple near-optimal models that achieve comparable performance while offering fundamentally different e

EquivDP3: A SIM(3)-Invariant Point-Cloud Encoder for Data-Efficient Humanoid Loco-Manipulation

model-releasesarxiv-cs-ro

arXiv:2609.36575v1 Announce Type: new Abstract: Visuomotor policies for humanoid loco-manipulation must generalize across object poses and lighting from only a handful of demonstrations. 3D Diffusion

ER-JEPA: Experience Replay Improves Joint-Embedding Predictive Learning in Language Models

arXiv:2609.36952v1 Announce Type: cross Abstract: Large language models (LLMs) excel at token-level generation but may learn undesirable abstract semantics and lack comprehensive perception. LLM-JEPA

Estimating the Causal Effects of T Cell Receptors

arXiv:2410.14127v2 Announce Type: replace-cross Abstract: A central question in human immunology is how a patient's T cell receptors impacts disease. Here, we introduce a method to infer the causal ef

Estimation of Room Impulse Responses from Handclaps

arXiv:2609.35839v1 Announce Type: cross Abstract: Handclaps provide an equipment-free excitation for room acoustics, but their unknown and variable source waveform makes room impulse response (RIR) es

Eternal Sunshine of the Spotless Mind: Systematically Erasing LLM's Memories

model-releasesarxiv-cs-cl

arXiv:2609.36414v1 Announce Type: new Abstract: We consider persistent LLMs that accumulate memories of their interactions with a user over time. Such LLMs maintain memories using external storage, wh

Evaluating Alignment of Behavioral Dispositions in LLMs

arXiv:2602.11328v2 Announce Type: replace Abstract: As people turn to LLMs for social advice, understanding their behavior in such contexts becomes essential. In this work, we focus on behavioral disp

safetyarxiv-cs-cl