Search: “retrieval”

Where Should Agents Live? Energy-Memory Characterization of Agentic AI for the Edge-Cloud Continuum

arXiv:2609.18283v1 Announce Type: new Abstract: As telecommunication networks evolve toward autonomous 5G-Advanced and 6G operations, agentic artificial intelligence (AI) workflows, where large langua

17 Sept 2026

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Affect-Prototype Guided Fusion for Open-Vocabulary Incomplete Multi-modal Emotion Recognition

DGX agent

arXiv:2609.16962v1 Announce Type: new Abstract: Open-vocabulary multimodal emotion recognition (OV-MER) aims to generate open natural-language emotion labels from multimodal affective cues. In real-wo

applicationsarxiv-cs-ai

16 Sept 2026

Artificial intelligence and biosecurity: capabilities, threat pathways, and defense-in-depth governance

arXiv:2609.16213v1 Announce Type: new Abstract: Artificial intelligence is reshaping biological research across an increasingly connected digital-to-physical workflow. General-purpose large language m

Beyond the Name: Demographic Leakage in De-Identified Resumes and Evaluation Artifacts in LLM Bias Audits

arXiv:2609.16501v1 Announce Type: cross Abstract: De-identified resume screening assumes that redacting explicit fields prevents ethnocultural inference; however, recent audits attribute residual leak

DriveMCP: An Agentic AI framework for Advanced Driver Assistance System

arXiv:2609.17247v1 Announce Type: new Abstract: An agentic AI driver-assistance framework that integrates perception, compliance reasoning, vehicle-state interpretation, and safety arbitration into a

safetyarxiv-cs-ro

EviScope: Paired Counterfactual Evidence Diagnostics for Faithful and Efficient Grounded Language Models

arXiv:2609.17081v1 Announce Type: new Abstract: Grounded language-model systems are often evaluated by final answer accuracy, yet a correct answer can be unsupported, drawn from the wrong source, or p

Glyph: A Multi-Strategy Agentic System for Column Description and Sensitivity-Ontology Tagging of Enterprise Data Catalogs

Enterprise data lakes accumulate tables faster than human stewards can document or classify them, leaving columns with missing descriptions and unassigned governance labels. This documentation debt un

agentsapple-ml-research

HintMiner: Automatic Question Hints Mining From Q&A Web Posts with Language Model via Self-Supervised Learning

arXiv:2609.16060v1 Announce Type: cross Abstract: Users often need ask questions and seek answers online. The Question - Answering (QA) forums such as Stack Overflow cannot always respond to the quest

researcharxiv-cs-ai

Hyperbolic Contrastive Learning with Entailment for Spatial Transcriptomics

arXiv:2609.16207v1 Announce Type: new Abstract: Spatial Transcriptomics (ST) has transformed biomedical research by enabling the spatial mapping of gene expression across tissue sections. However, hig

researcharxiv-cs-cv

InfoTaxa: Information-Calibrated Label-Free Clustering for Fine-Grained Visual Taxonomy

arXiv:2609.17218v1 Announce Type: new Abstract: Label-free clustering of frozen pretrained visual embeddings offers a scalable route to biodiversity monitoring, but image-only fine-grained taxonomy ex

researcharxiv-cs-cv

Interactive Memory Learning for Long-Term Conversations

arXiv:2609.17088v1 Announce Type: new Abstract: Recent advancements in large language models have significantly enhanced the capabilities of agents in modeling long-term conversations. Despite these s

LLM Inference in a Flash!

model-releasesarxiv-cs-lg

arXiv:2609.16161v1 Announce Type: new Abstract: Large Language Models (LLMs) have shown impressive capabilities across a range of natural language processing tasks, and LLM inference has emerged as a

Tutorials

LLMs as Master Forgers: Generating Synthetic Time Series Data for Manufacturing

arXiv:2609.16155v1 Announce Type: cross Abstract: This paper presents a novel framework leveraging Large Language Models (LLMs) to generate synthetic time series data for manufacturing processes. Moti

tutorialsarxiv-cs-ai

Tutorials

M4N VM family, now GA: Highest per-core IOPS and throughput for I/O and memory-bound workloads

As enterprise organizations scale mission-critical applications, storage I/O and memory access can become severe operational bottlenecks. Whether its Oracle databases, in-memory databases like SAP HAN

tutorialsgoogle-cloud-ai

MDN-Control: Mask-Depth-Noise Guided Region Control for Multi-Subject Video Editing

arXiv:2609.16475v1 Announce Type: new Abstract: Multi subject video editing modifies designated subjects while preserving non target content, but faces cross subject attribute leakage, and occlusion a

safetyarxiv-cs-cv

Models as Governed Interfaces for AI-Native MBSE: Read-Side Adequacy and Write-Side Admissibility

arXiv:2609.16252v1 Announce Type: cross Abstract: Machine-readable models such as SysML v2 are now programmatically accessible, and a growing body of work treats that access as the enabling condition

Multi-modal Knowledge Preserving Adapter for Embedding Backward Compatibility

arXiv:2609.16875v1 Announce Type: new Abstract: Upgrading embedding models typically requires expensive database re-indexing, as new query embeddings are incompatible with existing database embeddings

researcharxiv-cs-cv

Applications

Nepali Legal Expertise through Generative and Extractive Pre-trained Transformers (NepLEGiT)

arXiv:2609.16010v1 Announce Type: new Abstract: The complexity of legal language and limited accessibility to legal information pose significant challenges to justice delivery in Nepal. Traditional le

applicationsarxiv-cs-cl

Not Another Text Benchmark: Putting the 'Visual' Back in Visual Question Answering for Large Video Models

model-releasesarxiv-cs-cv

arXiv:2609.17112v1 Announce Type: new Abstract: Large video models have exhibited impressive performance on a wide range of visual question answering tasks, owing to the rise of powerful, pretrained t

Tutorials

On the Importance of Gating: Memorization vs. In-Context Learning in State Space Models

arXiv:2609.16540v1 Announce Type: cross Abstract: State Space Models (SSMs) have emerged as a compelling alternative to Transformers, enabling sequence modeling with constant memory and linear compute

tutorialsarxiv-cs-ai

Post-Training Large Language Models via Reinforcement Learning from Self-Feedback

arXiv:2507.21931v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) often produce plausible but poorly-calibrated answers, limiting their reliability on reasoning-intensive tasks. R

Local Ai

ProtoLIP: From Sentence-Level to Object-Level Evidence Disentanglement

arXiv:2609.16284v1 Announce Type: cross Abstract: Query-conditioned vision--language models enable fine-grained interpretation by revealing how visual evidence changes with textual queries. However, e

local-aiarxiv-cs-ai

RiskChainBench: A Benchmark for Obfuscated Platform Message Restoration and Evidence-Grounded Web Investigation

arXiv:2609.16900v1 Announce Type: new Abstract: Platform abuse campaigns conceal redirection instructions with emojis, homophones, character decomposition, and redundant symbols, then route users thro

Same Problem, Different Field: Cross-Domain Solution Import via Domain-Stripped Computational Fingerprints

arXiv:2609.07595v2 Announce Type: replace-cross Abstract: The same underlying computational problem is solved across unrelated fields under different names: recursive Bayesian state estimation appears

SAVOR: Self-Aware Visual Grounding via Confidence-Calibrated Reinforcement Learning for Multimodal Hallucination Mitigation

arXiv:2609.16601v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) have made strong progress on visual question answering and image captioning, yet they still produce fluent clai

safetyarxiv-cs-cv

Semantic-Spatial Agreement Verification for Mitigating Object Hallucination in Multimodal Large Language Models

arXiv:2609.17269v1 Announce Type: new Abstract: Multimodal large language models generate natural-language responses from visual inputs, yet may mention objects absent from an image. In medication ass

safetyarxiv-cs-cv

SITA: Learning Speaker-Invariant and Tone-Aware Speech Representations for Low-Resource Tonal Languages

arXiv:2601.09050v2 Announce Type: replace Abstract: Tonal low-resource languages are widely spoken but remain underserved by modern speech technologies. A central challenge is learning speech represen

researcharxiv-cs-cl

Style-Debiased DPO: Updating LLM Knowledge with Factuality-Aware Synthetic Preference Data

arXiv:2609.16532v1 Announce Type: new Abstract: Continued pretraining (CPT) with data augmentation such as paraphrasing can store inside a large language model (LLM) the knowledge of a small source co

Symbolic Separation: Grounding Deep Agents in Knowledge Graphs for Trustworthy Operational Data Analytics

arXiv:2609.17107v1 Announce Type: new Abstract: Generative AI promises natural language access to the massive numerical telemetry of data centers and Industry 4.0 installations, yet text-to-query and

SyncVoice: Simple and Effective Automatic Video Dubbing with Vision-Augmented TTS

arXiv:2512.05126v2 Announce Type: replace-cross Abstract: Automatic video dubbing aims to generate high-fidelity speech that is temporally aligned with visual content. However, existing methods still

researcharxiv-cs-ai

TEDi: Temporal Memory-Enhanced and Denoising Transformer for Surgical Instrument Segmentation

model-releasesarxiv-cs-cv

arXiv:2609.16797v1 Announce Type: new Abstract: Query-based segmentation methods have shown promising potential for surgical instrument segmentation and recognition, which is essential for scene under

World Model Science: Self-Organized Criticality, Weak Chaos, and Metastable Belief Dynamics in Long-Horizon LLM Agents

arXiv:2609.17419v1 Announce Type: new Abstract: Long-horizon LLM agents must maintain task state across extended sequences of observations, actions, tool calls, and intermediate beliefs. We study thes

A Controlled Reevaluation of Coreference Resolution Models

arXiv:2404.00727v3 Announce Type: replace Abstract: All state-of-the-art coreference resolution (CR) models involve finetuning a pretrained language model. Whether the superior performance of one CR m

researcharxiv-cs-cl

A Multi-Stage Agentic Framework for Effective Counter-Narrative Generation and Refinement

arXiv:2609.14178v1 Announce Type: new Abstract: The rapid diffusion of hate speech and misinformation on social networks challenges democratic societies, since direct suppression efforts may deepen po

safetyarxiv-cs-cl

A parameter-efficient three-branch architecture for multimodal misinformation detection with limited annotations

model-releasesarxiv-cs-cv

arXiv:2512.20257v2 Announce Type: replace Abstract: With the rise of easily accessible generative tools for creating and manipulating multimedia content, the threat of realistic synthetic alterations

Assembling the CREW: A Collaborative Multi-agent Reinforcement Learning Framework for Automated Related Work Generation

model-releasesarxiv-cs-lg

arXiv:2609.15721v1 Announce Type: new Abstract: Automatic Related Work Generation (RWG) significantly reduces the human time and effort required to author the Related Work Section (RWS) of a research

Local Ai

Augmenting Large Audio-Language Models with Frame-Level Grounding for Fine-Grained Temporal Perception

arXiv:2609.15215v1 Announce Type: cross Abstract: Large Audio-Language Models (LALMs) have substantially advanced general audio understanding, yet they remain limited in fine-grained temporal percepti

local-aiarxiv-cs-ai

Authorship attribution and aesthetic evaluation of AI poetry: a case study with Haiku

arXiv:2609.15511v1 Announce Type: cross Abstract: This paper investigates the generation and human evaluation of Japanese haiku by contemporary Large Language Models (LLMs), focusing on authorship per

BusMA: A Bus Communication Substrate for Multi-Agent Systems

arXiv:2609.15054v1 Announce Type: new Abstract: Multi-Agent (MA) systems are effective at solving complex tasks that demand planning, tool use, and the synthesis of evidence from multiple sources. Exi

Local Ai

DeepDiscovery: A Location-Inference Framework for Task-Level Repository Understanding

arXiv:2606.22906v2 Announce Type: replace-cross Abstract: Large language models have shown strong performance on software engineering (SE) tasks, yet understanding large industrial repositories remain

local-aiarxiv-cs-ai

Applications

Discovering Hierarchy-Grounded Domains with Adaptive Granularity for Clinical Domain Generalization

arXiv:2506.06977v4 Announce Type: replace-cross Abstract: Domain generalization has become a critical challenge in predictive healthcare, where different patient groups exhibit shifting data distribut

applicationsarxiv-cs-ai

Domain-Specific Jargon in Large Language Models: A Comparative Analysis between General-Purpose and Specialist Models

arXiv:2609.13556v1 Announce Type: cross Abstract: Large Language Models (LLMs) have shown remarkable proficiency on general-purpose tasks, yet their performance often degrades in highly-specialized te

Fabrication After Tool Failure: Tool-Augmented Agents Assert Values Their Tools Did Not Return

arXiv:2609.14758v1 Announce Type: cross Abstract: Tool-augmented language models are evaluated on whether they reach the right answer, not on whether they report honestly when a tool fails to supply o

GeoSkill:Experience-Driven Hierarchical Skill Learning with Collaborative Revision forGeospatialAgents

arXiv:2609.13667v1 Announce Type: new Abstract: Geospatial agents are increasingly expected to support recurring and evolving analytical tasks rather than execute isolated workflows. In such settings,

Grounded Adjudication of Variations across Extracted TimeLines (GAVEL): Comparing Clinical Timelines Against Their Case Reports

arXiv:2609.13475v1 Announce Type: new Abstract: Existing pipelines for clinical timeline extraction from case reports are evaluated using an expert reference and are limited by imperfect reference ann

HarnessVLN: Unifying Training-Free Embodied Navigation through an Agent Harness

arXiv:2609.15195v1 Announce Type: new Abstract: Embodied navigation requires agents to interpret visual observations, accumulate spatial knowledge, and execute actions to follow instructions or locate

agentsarxiv-cs-ro

High-Density Automated Valet Parking with Relocation-Free Sequential Operations

arXiv:2603.23803v2 Announce Type: replace-cross Abstract: In this paper, we present DROP, high-Density Relocation-free sequential OPerations in automated valet parking. DROP addresses the challenges i

researcharxiv-cs-ro

JumpStart Your Policy Learning with Lessons from 160,000 Training Runs

model-releasesarxiv-cs-lg

arXiv:2609.13730v1 Announce Type: new Abstract: Reliable progress in offline policy learning depends on careful reporting, well-tuned baselines, and evaluation across diverse conditions. Prior work ha