Search: “deployment”

GaLe: memory-efficient Global Approximate and Local Exact features

arXiv:2609.02689v1 Announce Type: new Abstract: Embedded devices typically lack the resources of GPU-equipped machines, and existing inference methods suffer from either high computational overhead (p

local-aiarxiv-cs-cv

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General Demographic Pre-trained Models for Enhancing Predictive Performance Across Diseases and Population

DGX agent

arXiv:2509.07330v3 Announce Type: replace-cross Abstract: Foundation models for healthcare require balancing robust generalization across heterogeneous clinical populations and disease settings with t

applicationsarxiv-cs-ai

3 Sept 2026

Grounded, Compute-Efficient LLM Policy Agents for Energy-Poverty Equity in Physically-Constrained Peer-to-Peer Energy Markets

arXiv:2609.01918v1 Announce Type: new Abstract: Energy poverty is nearly absent from NLP-for-social-good, and the little existing work is either static retrieval/QA or relies on carbon-intensive cloud

local-aiarxiv-cs-cl

HeadWiseKV: Budgeted Per-Head Cache Residency for Hybrid Long-Context Language Models

arXiv:2609.02029v1 Announce Type: new Abstract: Long-context inference retains a growing key--value (KV) cache during decoding, which consumes substantial GPU memory and can reduce generation throughp

local-aiarxiv-cs-ai

Humanoid Safe Stop via Learned Stoppability Value

arXiv:2609.02358v1 Announce Type: cross Abstract: Humanoid robots responding to emergency stop commands typically execute a fixed maneuver, without reasoning about whether a safe stop is actually feas

safetyarxiv-cs-lg

Hybrid Retrieval-Augmented Generation with Knowledge Graph Expansion, RRF Fusion, and Per-Chunk Grounded Evaluation for Enterprise Document Search

arXiv:2609.01617v1 Announce Type: cross Abstract: Getting accurate, grounded answers out of large enterprise document repositories is a difficult problem. Dense vector retrieval alone frequently perfo

Applications

Marginal Expected Revenue for Jointly Ranking Auction and Fixed-Price Listings in E-Commerce Sponsored Search

arXiv:2609.01628v1 Announce Type: cross Abstract: E-commerce search ranking must balance multiple objectives--relevance, user engagement, and platform revenue--when allocating impression slots to comp

applicationsarxiv-cs-lg

Measurement-Driven Sub-Network Selection for On-Premise Retrieval-Augmented Factory Agents

arXiv:2609.02760v1 Announce Type: new Abstract: On-premise assistants can give factory workers conversational access to machine documentation, but models capable of the task rarely fit shop-floor hard

Modeling and Optimizing User Preferences in AI Copilots: A Comprehensive Survey and Taxonomy

arXiv:2505.21907v3 Announce Type: replace Abstract: AI copilots represent a new generation of AI-powered systems designed to assist users, particularly knowledge workers and developers, in complex, co

MuyBridge: Mobile Human Center-of-Mass Estimation from Monocular Video via Sparse Fusion

arXiv:2609.02854v1 Announce Type: new Abstract: The 3D center of mass (CoM) is a primary quantity in the biomechanical analysis of sport, rehabilitation, and clinical movement, yet existing 3D pose tr

local-aiarxiv-cs-cv

MV-dVRK: A Multi-Viewpoint Benchmark for Spatial Surgical Perception

model-releasesarxiv-cs-cv

arXiv:2609.02717v1 Announce Type: new Abstract: Large-scale training and refined optimization techniques have greatly improved sparse multi-view 3D reconstruction. Despite their relevance to surgery,

OmegaUse-SOP: SOP Engineering for Professional Computer Use from Human Demonstrations

arXiv:2609.02149v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly evolving from conversational assistants into agents capable of operating external digital environments.

Tutorials

Prompting the Unknown: Understanding Response Uncertainty in Large Language Models

arXiv:2407.14845v4 Announce Type: replace-cross Abstract: Large language models (LLMs) are widely used in decision-making across diverse domains. Ensuring the generation of safe and reliable responses

tutorialsarxiv-cs-cl

Ranked by the Matcher: A Reproducibility Audit of Knowledge Graph Extraction from Threat Reports

arXiv:2609.01671v1 Announce Type: cross Abstract: Security teams and researchers choose knowledge-graph extraction tooling for threat reports on the strength of published triple-F1 scores, yet those s

Rethinking the Teacher-Student Framework for Test-Time Adaptation

arXiv:2609.02507v1 Announce Type: new Abstract: Test-Time Adaptation (TTA) has recently emerged as a promising strategy that allows the adaptation of pre-trained models to changing data distributions

researcharxiv-cs-lg

SkillGLoW: Procedural-Family Skill Consolidation for Self-Improving Agents on Long-Horizon Task Streams

arXiv:2609.02217v1 Announce Type: new Abstract: LLM agents increasingly self-improve by writing and reusing textual skills, kept either as one global document or as a flat pool of per-task entries, th

Tutorials

SlowFast-SCI: Slow-Fast Deep Unfolding Learning for Spectral Compressive Imaging

arXiv:2509.16509v3 Announce Type: replace Abstract: Humans learn in two complementary ways: a slow, cumulative process that builds broad, general knowledge, and a fast, on-the-fly process that capture

tutorialsarxiv-cs-cv

SpeakPay: Domain-Adaptive LoRA Fine-Tuning of Whisper for Low-Resource Nepali Financial Speech Recognition

model-releasesarxiv-cs-cl

arXiv:2609.01737v1 Announce Type: new Abstract: Mobile payment applications in Nepal are graphically mediated and largely inaccessible to visually impaired users. This paper presents SpeakPay, a voice

Applications

Test-Time Logit Prompting for Source-Free Missing Modality Adaptation

arXiv:2609.02039v1 Announce Type: new Abstract: Vision-language models (VLMs) have achieved remarkable performance by leveraging complementary information from large-scale image-text pairs. However, m

applicationsarxiv-cs-cv

Towards Trustworthy Autonomous Robots: An Explainable AI-Based Decision Framework

arXiv:2609.02861v1 Announce Type: cross Abstract: Autonomous robots powered by deep learning face a fundamental auditability challenge: when incidents occur, investigators cannot reconstruct why the s

safetyarxiv-cs-ai

Tri-Band Channel Measurement-Enabled Multi-Layer Digital Twin for Terahertz Wireless Data Centers

arXiv:2609.01699v1 Announce Type: new Abstract: The rapid growth of AI computing has driven increasing demands for flexible and high-capacity data-center interconnections. Owing to its ultra-wide band

researcharxiv-cs-lg

Unfolding the Leech Lattice: Fused Multi-Shell Decoding and VRAM Layouts for 2-Bit LLM Weights

arXiv:2609.02652v1 Announce Type: new Abstract: Leech-lattice vector quantization holds the strongest reported 2-bit quality under its own evaluation protocol. Its kernel decodes one shell; we found n

local-aiarxiv-cs-lg

World-Model-Augmented Visual Locomotion for Humanoids on Foothold-Constrained Terrain

arXiv:2609.02542v1 Announce Type: new Abstract: Foothold-constrained terrain is characterized by sparse, discontinuous, or geometrically restricted feasible foot contacts, as encountered on stepping s

safetyarxiv-cs-ro

A Classifier That Teaches Itself: Self-Improving, Frozen-gate Training (SIFT) for Dynamic Document Classification

arXiv:2607.18358v2 Announce Type: replace Abstract: Document classification is a solved problem in the laboratory and an unsolved one in the enterprise. The blocker is rarely model architecture; it is

safetyarxiv-cs-cl

AgentFactory: Towards Automated Agentic System Design and Optimization

arXiv:2609.01045v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated remarkable capabilities as powerful components in agentic systems, enabling sophisticated reasoning and c

An Intelligent Decision Support System for Emotion Monitoring using Microscopic Fixational Dynamics

arXiv:2609.00846v1 Announce Type: new Abstract: The rising prevalence of psychological disorders necessitates effective emotion monitoring, yet current methods relying on facial or physiological signa

local-aiarxiv-cs-cv

APEX-EM: Non-Parametric Online Learning for Autonomous Agents via Structured Procedural-Episodic Experience Replay

arXiv:2603.29093v3 Announce Type: replace-cross Abstract: LLM agents rerun full reasoning for every task, even one they solved moments earlier. We introduce extbf{APEX-EM}, a non-parametric experience

Are We There Yet? Assessing Computer-Use Agents for Blind Users' Accessible Interaction with Desktop Applications

arXiv:2609.00524v1 Announce Type: cross Abstract: Computer-use agents are emerging as a paradigm for agentic human-AI interaction, combining language reasoning with multi-modal interface grounding to

Applications

Autoresearch for Marketplace Catalogs: From Legacy Forms to AI-Native Matching

arXiv:2609.00274v1 Announce Type: new Abstract: Two-sided service marketplaces are moving from deterministic request-form intake to AI-native probabilistic matching, enabled by large language models (

applicationsarxiv-cs-ai

Breaking the Structural Identity: Personalized Federated LoRA Fine-tuning under Rank Heterogeneity

arXiv:2609.00632v1 Announce Type: cross Abstract: Large Language Models (LLMs) have achieved remarkable success across diverse domains, but their adaptation to privacy-sensitive, distributed datasets

Hardware

CacheBridge: Efficient Cross-Model KV Cache Transfer

arXiv:2609.00891v1 Announce Type: new Abstract: Sharing context between LLMs in a multi-model system requires the receiving model to prefill the shared prefix because KV caches are model-specific. Rec

hardwarearxiv-cs-ai

Candidate-Expanding Routing with Permutation-Stabilized Experts for Mixed-Format Medical VQA

arXiv:2609.00959v1 Announce Type: new Abstract: Mixed-format medical visual question answering (VQA) requires stable option selection and machine-readable free-text output. The two formats fail differ

researcharxiv-cs-cv

CERF: Communication-Efficient and Retraining-Free Collaborative Perception

arXiv:2609.00951v1 Announce Type: new Abstract: Collaborative perception shares information among multiple agents to obtain a comprehensive scene representation, enhancing the perceptual capability of

agentsarxiv-cs-cv

Channel-Adaptive Edge AI: Maximizing Inference Throughput by Adapting Computational Complexity to Channel States

arXiv:2603.03146v2 Announce Type: replace-cross Abstract: Integrated communication and computation (IC^2) has emerged as a new paradigm for enabling efficient edge inference in sixth-generation (6G) n

local-aiarxiv-cs-ai

CoLT-Drive: Counterfactual Long-Tail Benchmarking and Knowledge-Preserving Adaptation for Driving Affordance Prediction

arXiv:2609.00242v1 Announce Type: cross Abstract: Long-tail autonomous driving failures are often framed as rare-object recognition errors. We argue that this view is incomplete: the decision-critical

Conversation Coach: A Voice-enabled AI System that Helps Practice Difficult Workplace Conversations

arXiv:2609.00441v1 Announce Type: new Abstract: Effective manager-employee communication is critical for retaining high performers and developing underperformers, yet training managers in these skills

safetyarxiv-cs-ai

CRAD: Class-wise Reliability-Aware Distillation for Decentralized Heterogeneous Federated Learning

model-releasesarxiv-cs-cv

arXiv:2609.00446v1 Announce Type: cross Abstract: Conventional federated learning (FL) relies on parameter averaging, which forces clients to be doubly homogeneous: it demands an identical architectur

CRAFT: Fine-Tuning Pre-hoc Explainability in AI-native 6G RAN

arXiv:2609.00590v1 Announce Type: new Abstract: The next generation of mobile networks is envisioned as fully AI-native, with AI-RAN architectures embedding small language models (SLMs) to perform rea

safetyarxiv-cs-lg

Dependency-Aware Chain-of-Thought Compression for Financial Reasoning

arXiv:2609.00413v1 Announce Type: new Abstract: Chain of thought prompting improves complex reasoning, but its long intermediate traces create substantial inference cost and hinder practical deploymen

Designing Proactive Thought Partners for Writing

arXiv:2609.01588v1 Announce Type: cross Abstract: Writing involves diverse cognitive activities, from ideation to revision, and writers' needs vary across individuals and moments. Proactive AI promise

Hardware

Deterministic LLM Inference Across GPU Kernels: Power-of-Two INT8 Quantization Scales and the Limits of Tolerance-Based Conformance

arXiv:2609.00363v1 Announce Type: new Abstract: Conformance suites for quantized GEMM kernels ask whether two implementations agree within a tolerance. We measure what such a suite can detect. Injecti

hardwarearxiv-cs-lg

DGNet: Dual-knowledge Guided Network for Infrared Small Target Detection

arXiv:2609.00666v1 Announce Type: new Abstract: InfRared Small Target Detection (IRSTD) is a prominent and challenging task in computer vision. In recent years, text-guided methods have significantly

safetyarxiv-cs-cv

DynaNDE: Dynamic Near-Data Expert Scheduling for Batched MoE Inference

model-releasesarxiv-cs-lg

arXiv:2609.00407v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) models enable efficient scaling of large language model (LLM) inference but suffer from substantial data-movement overhead wh

EEG-AS: Instance-Level Foundation Model Selection for EEG Foundation Models via Behavior Reconstruction

arXiv:2609.00653v1 Announce Type: cross Abstract: Electroencephalography (EEG) is a non-invasive technique for measuring neural activity and has been widely used in neuroscience applications. Recent a

EGT-KG: Evidence-Grounded Typed KG Retrieval for Practical Scientific QA with Small Language Models

arXiv:2609.00479v1 Announce Type: new Abstract: For emerging scientific research domains, local Small Language Models (SLMs) are becoming more attractive, as they offer stronger privacy control and mo

Evaluating Multimodal LLMs as Generalist Vision-Language-Action Agents for Drone Control: Commanding, Approaching, Tracking and Searching

arXiv:2609.01404v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) are strong perceivers of images and video. We ask how far that reach extends into acting: dropping an MLLM di

Expert-like Bone Ultrasound Segmentation through Expert-in-the-loop Mask-conditioned Progressive Learning

model-releasesarxiv-cs-cv

arXiv:2609.00473v1 Announce Type: cross Abstract: Manual annotation remains a major bottleneck in ultrasound (US) bone segmentation, where experts typically iteratively refine rough brush masks rather

Facet-0: A Robotic Foundation Model for Contact-Rich Precise Manipulation

arXiv:2609.01596v1 Announce Type: cross Abstract: Real-world robotic assembly at sub-millimeter tolerances demands spatial precision, compliant interaction, and robustness to contact failures. We pres

safetyarxiv-cs-lg