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An Effective, Reliable, and Robust Framework for Human Activity Recognition Using Wearable Sensors

arXiv:2609.36848v1 Announce Type: new Abstract: Human Activity Recognition (HAR) through wearable sensors greatly improves the quality of human life through its multiple applications. For HAR, multi-s

researcharxiv-cs-lg

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Research

An Efficient Machine Learning Approach for Degradation Forecasting in AEM Water Electrolysis

DGX agent

arXiv:2609.37941v1 Announce Type: new Abstract: This study provides a data-driven analysis of a novel dataset of single-cell Anion Exchange Membrane water electrolyzers (AEMWE), operated under constan

researcharxiv-cs-lg

30 Sept 2026

An Empirical Study and Assessment of EU AI Act Compliance Checkers

arXiv:2609.36228v1 Announce Type: new Abstract: The EU AI Act introduces extensive compliance requirements for organizations that develop, deploy, or integrate AI systems. Many of these requirements a

An Exact Generate - Transform Decomposition of Small-LLM Team Scaling Across Orchestration Architectures

arXiv:2609.36104v1 Announce Type: new Abstract: Replacing one LLM agent with a collaborating team can raise accuracy, but whether scaling the team helps, and which architecture to scale, is unclear. S

Anatomy-Aware Prediction of Bronchoscopic Accessibility from 3D CT

model-releasesarxiv-cs-cv

arXiv:2609.37386v1 Announce Type: new Abstract: Pre-operative planning for bronchoscopy is critical for the diagnosis of lung lesions. Current accessibility assessment relies on subjective manual insp

Tutorials

Anisotropic Representations Improve Planning in JEPA World Models

arXiv:2609.37441v1 Announce Type: new Abstract: Latent world models learn action-conditioned dynamics in representation space and often score candidate actions by Euclidean distance to a goal represen

tutorialsarxiv-cs-ro

AnthroDial: Benchmarking LLM Anthropomorphism in Autonomous Social Interaction

arXiv:2609.37853v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed as social agents, yet credible human-like interaction requires more than fluent responses or pers

agentsarxiv-cs-cl

AnyAct: Universal Action for Self-Evolving Agents

arXiv:2609.37025v1 Announce Type: new Abstract: As large language models (LLMs) advance, AI agents are increasingly deployed in open-world environments to tackle complex sequential tasks (e.g., docume

Aperture: Merge-Consistent Rotary States for Compressed Tokens

arXiv:2609.36781v1 Announce Type: new Abstract: Token compression combines content from several positions, yet rotary position embeddings usually assign the merged token one coordinate. We ask what po

Applications

APM-Bench: Benchmarking Cross-session Persistent Memory for Egocentric Streaming Video Assistants

arXiv:2609.37559v1 Announce Type: new Abstract: To serve as real-world personal assistants, streaming video models need persistent memory that retains past experiences for later use. Yet existing stre

applicationsarxiv-cs-cv

Applying Language Models in Clinical Medicine: Recent Trends and Perspectives

arXiv:2609.34780v2 Announce Type: replace Abstract: The use and applicability of artificial intelligence (AI) in medical research and clinical practice has received increasing attention in the literat

ARC-KV: Amortizing Anchor Search for Reconstruction-Based KV Cache Compaction

arXiv:2609.36835v1 Announce Type: new Abstract: Long-context large language model inference is bottlenecked by KV caches that grow linearly with sequence length. This burden is especially severe for l

ARCagent: An Adaptive Retrieval Calibration Agent for Clinical Question Answering

arXiv:2609.36392v1 Announce Type: new Abstract: In diseases where clinical guidelines are incomplete, contested, or mutually contradictory, knowledge completeness and dynamic conflict-aware synthesis

Architecture Alignment With Sparse Priors in Tabular Foundation Models

model-releasesarxiv-cs-lg

arXiv:2609.36883v1 Announce Type: new Abstract: Tabular foundation models (TFMs) are increasingly popular because they deliver strong predictions on new datasets through in-context learning, without t

Are In-Context Images Worth 10 Dimensions?

arXiv:2609.37659v1 Announce Type: new Abstract: There has been significant work on understanding the In-Context Learning capabilities of Large Language Models, especially on the induction circuit. For

researcharxiv-cs-cv

ARGOS: Reinforcement Learning-Driven Multidimensional Elasticity for Service Orchestration in the Computing Continuum

arXiv:2609.37085v1 Announce Type: cross Abstract: Data-intensive services in the Computing Continuum must balance analytics quality, resource usage, and cost across heterogeneous nodes with limited an

ARK: A Dual-Axis Multimodal Retrieval Benchmark along Reasoning and Knowledge

model-releasesarxiv-cs-cv

arXiv:2602.09839v2 Announce Type: replace Abstract: Existing multimodal retrieval benchmarks largely emphasize semantic matching on daily-life images and offer limited diagnostics of professional know

AS^2D: Accelerating On-Demand Audio Understanding on Mobile Devices

arXiv:2609.37617v1 Announce Type: cross Abstract: Speculative decoding accelerates autoregressive generation by using a smaller drafter to propose tokens for batched verification by a larger target. H

ASCEND: Personal AI Agents for Autonomous Scientific Computing Across HPC Clusters and GPU Workstations

arXiv:2609.32868v2 Announce Type: replace-cross Abstract: Traditional scientific computing requires researchers to translate computational intent into environment configuration, resource requests, and

Asking for What Was Never Requested: Horizontal and Vertical Proactivity in Agents

arXiv:2609.37236v1 Announce Type: new Abstract: An agent that uses tools typically responds to what the user explicitly asks, yet completing the task may require information the user never requested.

AssayRouter: Historical Utility Priors for Frozen Molecular Predictor Routing

arXiv:2609.37285v1 Announce Type: new Abstract: Laboratories often face a new molecular assay with 16-64 labels and a bank of predictors whose training data and parameters are unavailable. The practic

local-aiarxiv-cs-ai

Asymmetric Scout-Worker Reconnaissance for Route Validation in Unknown Environments

arXiv:2609.36537v1 Announce Type: new Abstract: This paper studies asymmetric scout-worker reconnaissance in unknown environments, where a small, agile autonomous scout explores routes for a larger wo

agentsarxiv-cs-ro

Asymptotic Universal Alignment: A New Alignment Framework via Test-Time Scaling

arXiv:2601.08777v2 Announce Type: replace-cross Abstract: Aligning large language models (LLMs) to serve users with heterogeneous and potentially conflicting preferences is a central challenge for per

ATLAS: Aligned Transport of Latent Structure for Reliable World Model Planning

arXiv:2609.36333v1 Announce Type: cross Abstract: Latent world models rely on representation geometry for planning, yet regularizing the latent marginal alone does not determine the state-to-state rel

Attention-Scoped Guidance: Training-Free Spatial Control for Image Editing

arXiv:2609.37492v1 Announce Type: new Abstract: Instruction-guided image editing should change what the instruction names and leave the rest of the image untouched. In dual classifier-free guidance (C

researcharxiv-cs-cv

ATTUNER: Recomputation-Free KV Cache Reuse via Query-Side Adaptation

arXiv:2609.36722v1 Announce Type: new Abstract: Large language model (LLM) agents repeatedly load reusable content, such as skills, documents, and memory entries, into the current context. Re-encoding

local-aiarxiv-cs-cl

au-Multilingual: Benchmarking Voice Agents Across Languages

arXiv:2609.35820v1 Announce Type: cross Abstract: English-only benchmarks expose only a narrow slice of voice-agent behavior. We introduce au-Multilingual, extending au-Voice to Spanish, Brazilian Por

agentsarxiv-cs-ai

Audience-Bound Persistent Memory: Authorization Across the Memory Lifecycle

arXiv:2609.36373v1 Announce Type: cross Abstract: A personal language agent that acts for its owner across private and shared conversations can learn a fact from one audience and later place it in the

Auditable Long-Term Memory: A Deterministic Retrieval Chain Measured at 479/475 of 500 on LongMemEval-S

arXiv:2609.38021v1 Announce Type: cross Abstract: We evaluate an auditable long-term memory system on LongMemEval-S. Its retrieval chain uses hybrid candidate retrieval, cross-encoder reranking, cover

Authority Before Utility: Non-Compensatory Control for Persistent LLM Memory

arXiv:2609.37474v1 Announce Type: new Abstract: Persistent memory creates a control problem that retrieval relevance alone does not solve: a memory can remain highly useful after an update, deletion,

Authority Bias in Language Models: Source Deference and User Agreement Are Not Interchangeable

arXiv:2609.37616v1 Announce Type: cross Abstract: Language models tend to agree with whatever a user asserts, and post-training increasingly targets this sycophancy so that models evaluate claims on t

safetyarxiv-cs-cl

AutoLoCo: Communication Efficient Distributed LLM Training via Adaptive Synchronization

arXiv:2609.36662v1 Announce Type: cross Abstract: The pre-training of Large Language Models (LLMs) is increasingly conducted across multiple data centers. As training scales to a larger number of acce

local-aiarxiv-cs-ai

AutoMark: Enabling Autoresearch to Discover Better LLM Watermarks

model-releasesarxiv-cs-lg

arXiv:2609.37310v1 Announce Type: cross Abstract: With LLM watermarking being deployed commercially and now required by regulations, improving its reliability and effectiveness has become crucial. Yet

Automated Evaluation of Multi-Turn Dialogues in In-Car Conversational Assistants

arXiv:2609.35812v1 Announce Type: new Abstract: In-car conversational assistants (ICAs) are increasingly integrated into vehicles to support route planning, vehicle control, and information access. En

safetyarxiv-cs-cl

Automated Screw Planning for Reduced Pelvic Fractures Based on Statistical Shape Models and Deep Learning

arXiv:2609.36847v1 Announce Type: new Abstract: Percutaneous iliosacral screw fixation is an important minimally invasive treatment for unstable pelvic fractures. Because the sacroiliac region has com

AVIO: Learning to Add and Remove Sounding Objects in Audiovisual Scenes

arXiv:2609.36503v1 Announce Type: new Abstract: Adding or removing a sounding object requires coordinated changes to visual content and sound while preserving the surrounding scene. Yet paired supervi

local-aiarxiv-cs-ai

AX is the New AEO

arXiv:2609.34951v2 Announce Type: replace Abstract: In 2023, AI models answered from training data and hallucinated when it ran out, and businesses were told to seed that knowledge. Models' training k

agentsarxiv-cs-ai

Back2Struct: Making Structured Images Editable Again

arXiv:2609.37016v1 Announce Type: new Abstract: Structured images, such as diagrams, charts, and flowcharts, are inherently symbolic and can be compactly represented in an editable format, yet in prac

safetyarxiv-cs-cv

Backdoor in the Loop: Compromising Agentic Search via Malicious Retrievers

arXiv:2609.37468v1 Announce Type: cross Abstract: Agentic retrieval-augmented generation (RAG) interleaves reasoning with repeated retrieval, giving the retriever influence over both the evidence an a

agentsarxiv-cs-ai

Backdoor Mitigation in Decentralized LLM Fine-Tuning

arXiv:2609.37367v1 Announce Type: cross Abstract: Decentralized large language model (LLM) fine-tuning lets organizations collaboratively train a shared LLM on data they cannot pool, without a central

researcharxiv-cs-lg

Backpropagated Output Momentum: Relocating Optimizer History from Parameters to Task Space

model-releasesarxiv-cs-cl

arXiv:2609.36738v1 Announce Type: cross Abstract: Optimizer momentum is usually stored as a parameter-sized moving average of past gradients, which makes history costly and fixes each past signal in t

BadRAG: Identifying Vulnerabilities in Retrieval Augmented Generation of Large Language Models

arXiv:2406.00083v3 Announce Type: replace-cross Abstract: Retrieval-Augmented Generation (RAG) enhances Large Language Models (LLMs) by retrieving relevant information from external knowledge bases to

BaLEEN: Biasing with Latent Encoded Entities for Context-Aware ASR

arXiv:2609.36913v1 Announce Type: cross Abstract: Transcribing domain-specific entities and rare proper nouns remains a major challenge in automatic speech recognition (ASR). In this paper, we propose

BarcodeMAE+: Rethinking Masked Pretraining and Global Representations for DNA Barcode Foundation Models

arXiv:2609.35877v1 Announce Type: cross Abstract: Many DNA foundation models are pretrained by masking parts of a sequence and asking the model to reconstruct them. Standard masked pretraining exposes

researcharxiv-cs-lg

Hardware

BASE: Batch-Aware Selection of Experts Using Predicted Removal Error for Efficient MoE Decoding

arXiv:2609.36222v1 Announce Type: new Abstract: Large language models are increasingly expensive to serve. In large-scale serving systems, autoregressive decoding is often bottlenecked by transferring

hardwarearxiv-cs-lg

Bathtubs, Boundaries, and Sandboxes: AI Regulatory Learning under Legal Uncertainty

arXiv:2601.04094v4 Announce Type: cross Abstract: Effective regulation of AI is a defining policy challenge, driven by their integration into all aspects of society. To remain responsive to their rapi

Battery-Aware Reinforcement Learning for Aggressive Quadrotor Flight

arXiv:2609.37316v1 Announce Type: new Abstract: Agile flight tasks such as drone racing and pursuit-evasion require strong acceleration and precise turns, but the available thrust changes as the batte

safetyarxiv-cs-ro

BCNav: Bearing-Conditioned Depth Policies for Sound Source Navigation

arXiv:2609.37084v1 Announce Type: new Abstract: The ability to navigate toward sound sources extends a robot's reach beyond its visual field, enabling response to auditory events in unknown environmen

safetyarxiv-cs-ro