Search: “retrieval”

Agentic publications: redesigning scientific publishing in the age of thinking large language models

arXiv:2505.13246v2 Announce Type: replace Abstract: Purpose: This paper introduces the concept of 'Agentic Publication,' a novel LLM-driven framework designed to complement traditional scientific publ

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Agents

ARIS: Autonomous Research via Adversarial Multi-Agent Collaboration

DGX agent

arXiv:2605.03042v1 Announce Type: cross Abstract: This report describes ARIS (Auto-Research-in-sleep), an open-source research harness for autonomous research, including its architecture, assurance me

agentsarxiv-cs-ai

7 May 2026

Assessing Cognitive Effort in L2 Idiomatic Processing: An Eye-Tracking Dataset

arXiv:2605.04857v1 Announce Type: new Abstract: This paper presents the development and validation of an eye-tracking dataset designed to investigate how second-language (L2) learners process idiomati

ContextPilot: Fast Long-Context Inference via Context Reuse

arXiv:2511.03475v4 Announce Type: replace Abstract: AI applications increasingly depend on long-context inference, where LLMs consume substantial context to support stronger reasoning. Common examples

agentsarxiv-cs-lg

DiCLIP: Diffusion Model Enhances CLIP's Dense Knowledge for Weakly Supervised Semantic Segmentation

arXiv:2605.04593v1 Announce Type: new Abstract: Weakly Supervised Semantic Segmentation (WSSS) with image-level labels typically leverages Class Activation Maps (CAMs) to achieve pixel-level predictio

local-aiarxiv-cs-cv

Frontier Lag: A Bibliometric Audit of Capability Misrepresentation in Academic AI Evaluation

arXiv:2605.04135v1 Announce Type: cross Abstract: Readers of applied-domain LLM capability evaluations want to know what AI systems can currently do. That literature answers a related, but consequenti

GeoDecider: A Coarse-to-Fine Agentic Workflow for Explainable Lithology Classification

arXiv:2605.03383v1 Announce Type: new Abstract: Lithology classification aims to infer subsurface rock types from well-logging signals, supporting downstream applications like reservoir characterizati

Graph-Augmented LLMs for Swiss MP Ideology Prediction

arXiv:2605.04643v1 Announce Type: new Abstract: Approximating the ideological position of Members of Parliament (MPs) is a fundamental task in political science, helping researchers understand legisla

safetyarxiv-cs-cl

Ilov3Splat: Instance-Level Open-Vocabulary 3D Scene Understanding in Gaussian Splatting

arXiv:2605.04506v1 Announce Type: new Abstract: We introduce Ilov3Splat, a novel framework for instance-level open-vocabulary 3D scene understanding built on 3D Gaussian Splatting (3D-GS). Most prior

researcharxiv-cs-cv

Low-Cost Black-Box Detection of LLM Hallucinations via Dynamical System Prediction

arXiv:2605.05134v1 Announce Type: new Abstract: Large Language Models (LLMs) frequently generate plausible but non-factual content, a phenomenon known as hallucination. While existing detection method

researcharxiv-cs-lg

OpenSearch-VL: An Open Recipe for Frontier Multimodal Search Agents

arXiv:2605.05185v1 Announce Type: new Abstract: Deep search has become a crucial capability for frontier multimodal agents, enabling models to solve complex questions through active search, evidence v

agentsarxiv-cs-cv

Physics-Grounded Multi-Agent Architecture for Traceable, Risk-Aware Human-AI Decision Support in Manufacturing

arXiv:2605.04003v1 Announce Type: cross Abstract: High-precision CNC machining of free-form aerospace components requires bounded compensations informed by inspection, simulation, and process knowledg

POMA-3D: The Point Map Way to 3D Scene Understanding

arXiv:2511.16567v3 Announce Type: replace Abstract: In this paper, we introduce POMA-3D, the first self-supervised 3D representation model learned from point maps. Point maps encode explicit 3D coordi

safetyarxiv-cs-cv

Sentiment Analysis and Customer Satisfaction Prediction on E-Commerce Platforms Based on YouTube Comments Using the XGBoost Algorithm

arXiv:2605.04887v1 Announce Type: new Abstract: The exponential expansion of digital commerce in Indonesia has significantly shifted consumer interactions toward video-centric social networks, particu

researcharxiv-cs-cl

Text Corpora as Concept Fields: Black-Box Hallucination and Novelty Measurement

arXiv:2605.05103v1 Announce Type: new Abstract: We introduce the **Concept Field** of a text corpus: a local drift field with pointwise uncertainty, estimated in sentence-embedding space from the delt

local-aiarxiv-cs-cl

UFAL-CUNI at SemEval-2026 Task 11: An Efficient Modular Neuro-symbolic Method for Syllogistic Reasoning

arXiv:2605.04941v1 Announce Type: new Abstract: This paper describes our system submitted to SemEval-2026 Task 11: Disentangling Content and Formal Reasoning in Large Language Models. We present an ef

A Compound AI Agent for Conversational Grant Discovery

arXiv:2605.02366v1 Announce Type: new Abstract: Research funding discovery remains fundamentally fragmented: researchers navigate disparate agency portals (e.g., in the United States, NSF, NIH, DARPA,

A Knowledge-Driven LLM-Based Decision-Support System for Explainable Defect Analysis and Mitigation Guidance in Laser Powder Bed Fusion

arXiv:2605.01100v1 Announce Type: new Abstract: This work presents a knowledge-driven decision-support system that integrates structured defect knowledge with LLM-based reasoning to provide explainabl

safetyarxiv-cs-ai

AI and Open-data Driven Scalable Solar Power Profiling

arXiv:2605.02738v1 Announce Type: new Abstract: Solar photovoltaic (PV) deployment is expanding rapidly, yet detailed, up-to-date information on the spatial distribution and capacity of rooftop PV rem

ClinicBot: A Guideline-Grounded Clinical Chatbot with Prioritized Evidence RAG and Verifiable Citations

arXiv:2605.00846v1 Announce Type: new Abstract: Clinical diagnosis requires answers that are accurate, verifiable, and explicitly grounded in official guidelines. While large language models excel at

Empowering LLM Agents with Geospatial Awareness: Toward Grounded Reasoning for Wildfire Response

arXiv:2510.12061v2 Announce Type: replace Abstract: Effective disaster response is essential for safeguarding lives and property. Existing statistical approaches often lack semantic context, generaliz

researcharxiv-cs-ai

EngiBench: A Benchmark for Evaluating Large Language Models on Engineering Problem Solving

arXiv:2509.17677v2 Announce Type: replace Abstract: Large language models (LLMs) have shown strong performance on mathematical reasoning under well-defined conditions. However, real-world engineering

MEMAUDIT: An Exact Package-Oracle Evaluation Protocol for Budgeted Long-Term LLM Memory Writing

arXiv:2605.02199v1 Announce Type: new Abstract: Long-term LLM agents must compress streams of past interactions into persistent memory before future queries are known. Existing evaluations usually mea

researcharxiv-cs-ai

MILD: Mediator Agent System with Bidirectional Perception and Multi-Layered Alignment for Human-Vehicle Collaboration

arXiv:2605.01507v1 Announce Type: new Abstract: Prior studies report that partial driving automation can increase the cognitive demands on human drivers. This effect largely arises from human drivers'

safetyarxiv-cs-ai

MindMelody: A Closed-Loop EEG-Driven System for Personalized Music Intervention

arXiv:2605.01235v1 Announce Type: cross Abstract: Driven by the escalating global burden of mental health conditions, music-based interventions have attracted significant attention as a non-invasive,

local-aiarxiv-cs-ai

Tutorials

Natural Language Processing: A Comprehensive Practical Guide from Tokenisation to RLHF

arXiv:2605.03799v1 Announce Type: new Abstract: This preprint presents a systematic, research-oriented practicum that guides the reader through the entire modern NLP pipeline: from tokenisation and ve

tutorialsarxiv-cs-cl

NEURON: A Neuro-symbolic System for Grounded Clinical Explainability

arXiv:2605.01189v1 Announce Type: new Abstract: Clinical AI adoption is hindered by the black-box/grey-box nature of high-performing models, which lack the ontological grounding and narrative transpar

researcharxiv-cs-ai

OCRR: A Benchmark for Online Correction Recovery under Distribution Shift

arXiv:2605.03153v1 Announce Type: cross Abstract: Static benchmarks measure a model frozen at training time. Real systems face distribution shift: new categories, paraphrased queries, drift: and must

ORPilot: A Production-Oriented Agentic LLM-for-OR Tool for Optimization Modeling

arXiv:2605.02728v1 Announce Type: new Abstract: This paper presents ORPilot, an open-source agentic AI system that translates real-world business problems into solver-ready optimization models. Unlike

PatRe: A Full-Stage Office Action and Rebuttal Generation Benchmark for Patent Examination

arXiv:2605.03571v1 Announce Type: new Abstract: Patent examination is a complex, multi-stage process requiring both technical expertise and legal reasoning, increasingly challenged by rising applicati

PhysicianBench: Evaluating LLM Agents in Real-World EHR Environments

arXiv:2605.02240v1 Announce Type: new Abstract: We introduce PhysicianBench, a benchmark for evaluating LLM agents on physician tasks grounded in real clinical setting within electronic health record

PrismAgent: Illuminating Harm in Memes via a Zero-Shot Interpretable Multi-Agent Framework

arXiv:2605.02940v1 Announce Type: new Abstract: The rapid spread of memes makes harmful content detection increasingly crucial, as effective identification can curb the circulation of misinformation.

agentsarxiv-cs-lg

Seeking Information with RAG-Assistants: Does Model Size Matter in Human-AI Collaborations?

arXiv:2605.00964v1 Announce Type: cross Abstract: Much research on LLMs has focused on increasing benchmark performance. However, the evaluation of such models in real-world collaborative human-AI wor

Task Vector Geometry Underlies Dual Modes of Task Inference in Transformers

arXiv:2605.03780v1 Announce Type: cross Abstract: Transformers are effective at inferring the latent task from context via two inference modes: recognizing a task seen during training, and adapting to

researcharxiv-cs-cl

Workspace-Bench 1.0: Benchmarking AI Agents on Workspace Tasks with Large-Scale File Dependencies

arXiv:2605.03596v1 Announce Type: cross Abstract: Workspace learning requires AI agents to identify, reason over, exploit, and update explicit and implicit dependencies among heterogeneous files in a

Act2See: Emergent Active Visual Perception for Video Reasoning

arXiv:2605.01657v1 Announce Type: new Abstract: Vision-Language Models (VLMs) typically rely on static initial frames for video reasoning, restricting their ability to incorporate essential dynamic in

researcharxiv-cs-cv

ARIS: Agentic and Relationship Intelligence System for Social Robots

model-releasesarxiv-cs-ro

arXiv:2605.00943v1 Announce Type: new Abstract: Foundational models have advanced social robotics, enabling richer perception and communicative interaction with users. However, current systems still s

Assistance Without Interruption: A Benchmark and LLM-based Framework for Non-Intrusive Human-Robot Assistance

model-releasesarxiv-cs-ro

arXiv:2605.01368v1 Announce Type: new Abstract: Human-robot interaction (HRI) has long studied how agents and people coordinate to achieve shared goals. In this work, we formalize and benchmark the no

Automated In-the-Wild Data Collection for Continual AI Generated Image Detection

arXiv:2605.02567v1 Announce Type: new Abstract: The rapid advancement of generative Artificial Intelligence (AI) has introduced significant challenges for reliable AI-generated image detection. Existi

researcharxiv-cs-cv

Automated Interpretability and Feature Discovery in Language Models with Agents

arXiv:2605.01555v1 Announce Type: new Abstract: We introduce an autonomous multiagent framework for mechanistic interpretability that automates both explaining and finding internal features in large l

Bridging the Experimental Last Mile: Digitizing Laboratory Know-How for Safe AI-Assisted Support

arXiv:2604.16345v2 Announce Type: replace-cross Abstract: While advances in materials informatics have accelerated the development of Self-Driving Laboratories (SDLs), human-led experiments remain sta

local-aiarxiv-cs-ai

Causal2Vec: Improving Decoder-only LLMs as Embedding Models through a Contextual Token

arXiv:2507.23386v3 Announce Type: replace Abstract: Decoder-only large language models (LLMs) have been increasingly adopted to build embedding models for diverse tasks. To overcome the inherent limit

Combining Trained Models in Reinforcement Learning

arXiv:2605.02159v1 Announce Type: new Abstract: Deep reinforcement learning (DRL) has delivered strong results in domains such as Atari and Go, but it still suffers from high sample cost and weak tran

safetyarxiv-cs-lg

Applications

CoRAL: Contact-Rich Adaptive LLM-based Control for Robotic Manipulation

arXiv:2605.02600v1 Announce Type: new Abstract: While Large Language Models (LLMs) and Vision-Language Models (VLMs) demonstrate remarkable capabilities in high-level reasoning and semantic understand

applicationsarxiv-cs-ro

Decompose and Recompose: Reasoning New Skills from Existing Abilities for Cross-Task Robotic Manipulation

model-releasesarxiv-cs-cv

arXiv:2605.01448v1 Announce Type: cross Abstract: Cross-task generalization is a core challenge in open-world robotic manipulation, and the key lies in extracting transferable manipulation knowledge f

Disciplined Diffusion: Text-to-Image Diffusion Model against NSFW Generation

arXiv:2605.01113v1 Announce Type: new Abstract: Text-to-image (T2I) diffusion models have the ability to build high-quality pictures from text prompts, but they pose safety concerns because they can g

safetyarxiv-cs-cv

E-mem: Multi-agent based Episodic Context Reconstruction for LLM Agent Memory

arXiv:2601.21714v2 Announce Type: replace Abstract: The evolution of Large Language Model (LLM) agents towards System~2 reasoning, characterized by deliberative, high-precision problem-solving, requir

Embedding-based In-Context Prompt Training for Enhancing LLMs as Text Encoders

arXiv:2605.01372v1 Announce Type: new Abstract: Large language models (LLMs) have been widely explored for embedding generation. While recent studies show that in-context learning (ICL) effectively en