Search: “rag”

Personalization Toolkit: Training Free Personalization of Large Vision Language Models

model-releasesarxiv-cs-cv

arXiv:2502.02452v4 Announce Type: replace Abstract: Personalization of Large Vision-Language Models (LVLMs) involves customizing models to recognize specific users or object instances and to generate

29 Apr 2026

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Thinking About Thinking: Evaluating Reasoning in Post-Trained Language Models

DGX agent

arXiv:2510.16340v2 Announce Type: replace Abstract: Recent advances in post-training techniques have endowed Large Language Models (LLMs) with enhanced capabilities for tackling complex, logic-intensi

safetyarxiv-cs-cl

29 Apr 2026

DPEPO: Diverse Parallel Exploration Policy Optimization for LLM-based Agents

arXiv:2604.24320v1 Announce Type: new Abstract: Large language model (LLM) agents that follow the sequential 'reason-then-act' paradigm have achieved superior performance in many complex tasks.However

FinGround: Detecting and Grounding Financial Hallucinations via Atomic Claim Verification

arXiv:2604.23588v1 Announce Type: new Abstract: Financial AI systems must produce answers grounded in specific regulatory filings, yet current LLMs fabricate metrics, invent citations, and miscalculat

safetyarxiv-cs-ai

Learning Selective LLM Autonomy from Copilot Feedback in Enterprise Customer Support Workflows

arXiv:2604.23855v1 Announce Type: new Abstract: We present a deployed system that automates end-to-end customer support workflows inside an enterprise Business Process Management (BPM) platform. The a

LEGO: An LLM Skill-Based Front-End Design Generation Platform

arXiv:2604.23355v1 Announce Type: new Abstract: Existing LLM-based EDA agents are often isolated task-specific systems. This leads to repeated engineering effort and limited reuse of successful design

LoGeR: Long-Context Geometric Reconstruction with Hybrid Memory

arXiv:2603.03269v2 Announce Type: replace Abstract: Feedforward geometric foundation models achieve strong short-window reconstruction, yet scaling them to minutes-long videos is bottlenecked by quadr

safetyarxiv-cs-cv

OntoLogX: Ontology-Guided Knowledge Graph Extraction from Cybersecurity Logs with Large Language Models

arXiv:2510.01409v2 Announce Type: replace Abstract: System logs represent a valuable source of Cyber Threat Intelligence (CTI), capturing attacker behaviors, exploited vulnerabilities, and traces of m

PhySE: A Psychological Framework for Real-Time AR-LLM Social Engineering Attacks

arXiv:2604.23148v1 Announce Type: new Abstract: The emerging threat of AR-LLM-based Social Engineering (AR-LLM-SE) attacks (e.g. SEAR) poses a significant risk to real-world social interactions. In su

agentsarxiv-cs-ai

RCSB PDB AI Help Desk: retrieval-augmented generation for protein structure deposition support

arXiv:2604.22800v1 Announce Type: cross Abstract: Motivation: Structural Biologists have contributed more than 245,000 experimentally determined three-dimensional structures of biological macromolecul

Applications

RedParrot: Accelerating NL-to-DSL for Business Analytics via Query Semantic Caching

arXiv:2604.22758v1 Announce Type: cross Abstract: Recently, at Xiaohongshu, the rapid expansion of e-commerce and advertising demands real-time business analytics with high accuracy and low latency. T

applicationsarxiv-cs-ai

SoccerRef-Agents: Multi-Agent System for Automated Soccer Refereeing

arXiv:2604.23392v1 Announce Type: new Abstract: Refereeing is vital in sports, where fair, accurate, and explainable decisions are fundamental. While intelligent assistant technologies are being widel

Applications

Your Reviews Replicate You: LLM-Based Agents as Customer Digital Twins for Conjoint Analysis

arXiv:2604.22756v1 Announce Type: cross Abstract: Conjoint analysis is a cornerstone of market research for estimating consumer preferences; however, traditional methods face persistent challenges reg

applicationsarxiv-cs-ai

Evaluating LLM-Based Goal Extraction in Requirements Engineering: Prompting Strategies and Their Limitations

arXiv:2604.22207v1 Announce Type: cross Abstract: Due to the textual and repetitive nature of many Requirements Engineering (RE) artefacts, Large Language Models (LLMs) have proven useful to automate

HACHIMI: Scalable and Controllable Student Persona Generation via Orchestrated Agents

arXiv:2603.04855v3 Announce Type: replace Abstract: Student Personas (SPs) are emerging as infrastructure for educational LLMs, yet prior work often relies on ad-hoc prompting or hand-crafted profiles

agentsarxiv-cs-cl

How Large Language Models Balance Internal Knowledge with User and Document Assertions

arXiv:2604.22193v1 Announce Type: new Abstract: Large language models (LLMs) often need to balance their internal parametric knowledge with external information, such as user beliefs and content from

Learning from Natural Language Feedback for Personalized Question Answering

arXiv:2508.10695v2 Announce Type: replace-cross Abstract: Personalization is crucial for enhancing both the effectiveness and user satisfaction of language technologies, particularly in information-se

Navigating Large-Scale Document Collections: MuDABench for Multi-Document Analytical QA

arXiv:2604.22239v1 Announce Type: cross Abstract: This paper introduces the task of analytical question answering over large, semi-structured document collections. We present MuDABench, a benchmark fo

A Multimodal Text- and Graph-Based Approach for Open-Domain Event Extraction from Documents

arXiv:2604.21885v1 Announce Type: cross Abstract: Event extraction is essential for event understanding and analysis. It supports tasks such as document summarization and decision-making in emergency

AITP: Traffic Accident Responsibility Allocation via Multimodal Large Language Models

arXiv:2604.20878v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have achieved remarkable progress in Traffic Accident Detection (TAD) and Traffic Accident Understanding (TAU).

Forget, Then Recall: Learnable Compression and Selective Unfolding via Gist Sparse Attention

arXiv:2604.20920v1 Announce Type: new Abstract: Scaling large language models to long contexts is challenging due to the quadratic computational cost of full attention. Mitigation approaches include K

researcharxiv-cs-lg

From If-Statements to ML Pipelines: Revisiting Bias in Code-Generation

arXiv:2604.21716v1 Announce Type: new Abstract: Prior work evaluates code generation bias primarily through simple conditional statements, which represent only a narrow slice of real-world programming

It's High Time: A Survey of Temporal Question Answering

arXiv:2505.20243v4 Announce Type: replace Abstract: Time plays a critical role in how information is generated, retrieved, and interpreted. In this survey, we provide a comprehensive overview of Tempo

RV-HATE: Reinforced Multi-Module Voting for Implicit Hate Speech Detection

arXiv:2510.10971v2 Announce Type: replace-cross Abstract: Hate speech remains prevalent in human society and continues to evolve in its forms and expressions. Modern advancements in internet and onlin

Automatic Ontology Construction Using LLMs as an External Layer of Memory, Verification, and Planning for Hybrid Intelligent Systems

arXiv:2604.20795v1 Announce Type: new Abstract: This paper presents a hybrid architecture for intelligent systems in which large language models (LLMs) are extended with an external ontological memory

23 Apr 2026

Learning When Not to Decide: A Framework for Overcoming Factual Presumptuousness in AI Adjudication

arXiv:2604.19895v1 Announce Type: new Abstract: A well-known limitation of AI systems is presumptuousness: the tendency of AI systems to provide confident answers when information may be lacking. This

23 Apr 2026

Mol-Debate: Multi-Agent Debate Improves Structural Reasoning in Molecular Design

arXiv:2604.20254v1 Announce Type: new Abstract: Text-guided molecular design is a key capability for AI-driven drug discovery, yet it remains challenging to map sequential natural-language instruction

agentsarxiv-cs-ai

23 Apr 2026

CounterRefine: Answer-Conditioned Counterevidence Retrieval for Inference-Time Knowledge Repair in Factual Question Answering

arXiv:2603.16091v2 Announce Type: replace-cross Abstract: In factual question answering, many errors are not failures of access but failures of commitment: the system retrieves relevant evidence, yet

22 Apr 2026

Fine-Tuning Small Reasoning Models for Quantum Field Theory

arXiv:2604.18936v1 Announce Type: cross Abstract: Despite the growing application of Large Language Models (LLMs) to theoretical physics, there is little academic exploration into how domain-specific

22 Apr 2026

Neuro-Symbolic Resolution of Recommendation Conflicts in Multimorbidity Clinical Guidelines

arXiv:2604.17340v1 Announce Type: new Abstract: Clinical guidelines, typically developed by independent specialty societies, inherently exhibit substantial fragmentation, redundancy, and logical contr

21 Apr 2026

What Makes AI Research Replicable? Executable Knowledge Graphs as Scientific Knowledge Representations

arXiv:2510.17795v3 Announce Type: replace Abstract: Replicating AI research is a crucial yet challenging task for large language model (LLM) agents. Existing approaches often struggle to generate exec

agentsarxiv-cs-cl

21 Apr 2026

ZoFia: Zero-Shot Fake News Detection with Entity-Guided Retrieval and Multi-LLM Interaction

arXiv:2511.01188v2 Announce Type: replace Abstract: The rapid spread of fake news threatens social stability and public trust, highlighting the urgent need for its effective detection. Although large

21 Apr 2026

Can LLMs Understand the Impact of Trauma? Costs and Benefits of LLMs Coding the Interviews of Firearm Violence Survivors

arXiv:2604.16132v1 Announce Type: cross Abstract: Firearm violence is a pressing public health issue, yet research into survivors' lived experiences remains underfunded and difficult to scale. Qualita

Information-Consistent Language Model Recommendations through Group Relative Policy Optimization

arXiv:2512.12858v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are increasingly deployed in business-critical domains such as finance, education, healthcare, and customer suppo

safetyarxiv-cs-ai

Mitigating hallucinations and omissions in LLMs for invertible problems: An application to hardware logic design automation

arXiv:2512.03053v2 Announce Type: replace-cross Abstract: We show for invertible problems that transform data from a source domain (for example, Logic Condition Tables (LCTs)) to a destination domain

Multi-View Attention Multiple-Instance Learning Enhanced by LLM Reasoning for Cognitive Distortion Detection

arXiv:2509.17292v3 Announce Type: replace-cross Abstract: Cognitive distortions have been closely linked to mental health disorders, yet their automatic detection remains challenging due to contextual

SocialWise: LLM-Agentic Conversation Therapy for Individuals with Autism Spectrum Disorder to Enhance Communication Skills

arXiv:2604.15347v1 Announce Type: cross Abstract: Autism Spectrum Disorder (ASD) affects more than 75 million people worldwide. However, scalable support for practicing everyday conversation is scarce

agentsarxiv-cs-ai

Tutorials

A Pythonic Functional Approach for Semantic Data Harmonisation in the ILIAD Project

arXiv:2604.13042v1 Announce Type: cross Abstract: Semantic data harmonisation is a central requirement in the ILIAD project, where heterogeneous environmental data must be harmonised according to the

tutorialsarxiv-cs-ai

Building Trust in the Skies: A Knowledge-Grounded LLM-based Framework for Aviation Safety

arXiv:2604.13101v1 Announce Type: cross Abstract: The integration of Large Language Models (LLMs) into aviation safety decision-making represents a significant technological advancement, yet their sta

safetyarxiv-cs-ai

Controlling Authority Retrieval: A Missing Retrieval Objective for Authority-Governed Knowledge

arXiv:2604.14488v1 Announce Type: cross Abstract: In any domain where knowledge accumulates under formal authority -- law, drug regulation, software security -- a later document can formally void an e

LLMOrbit: A Circular Taxonomy of Large Language Models -From Scaling Walls to Agentic AI Systems

model-releasesarxiv-cs-cv

arXiv:2601.14053v2 Announce Type: replace-cross Abstract: The field of artificial intelligence has undergone a revolution from foundational Transformer architectures to reasoning-capable systems appro

The Cognitive Circuit Breaker: A Systems Engineering Framework for Intrinsic AI Reliability

arXiv:2604.13417v1 Announce Type: cross Abstract: As Large Language Models (LLMs) are increasingly deployed in mission-critical software systems, detecting hallucinations and ``faked truthfulness'' ha

ASTRA: Enhancing Multi-Subject Generation with Retrieval-Augmented Pose Guidance and Disentangled Position Embedding

model-releasesarxiv-cs-cv

arXiv:2604.13938v1 Announce Type: new Abstract: Subject-driven image generation has shown great success in creating personalized content, but its capabilities are largely confined to single subjects i

Applications

Automatically Inferring Teachers' Geometric Content Knowledge: A Skills Based Approach

arXiv:2604.13666v1 Announce Type: cross Abstract: Assessing teachers' geometric content knowledge is essential for geometry instructional quality and student learning, but difficult to scale. The Van

applicationsarxiv-cs-lg

Beyond Arrow's Impossibility: Fairness as an Emergent Property of Multi-Agent Collaboration

arXiv:2604.13705v1 Announce Type: new Abstract: Fairness in language models is typically studied as a property of a single, centrally optimized model. As large language models become increasingly agen

ChartNet: A Million-Scale, High-Quality Multimodal Dataset for Robust Chart Understanding

arXiv:2603.27064v2 Announce Type: replace-cross Abstract: Understanding charts requires models to jointly reason over geometric visual patterns, structured numerical data, and natural language -- a ca

Doc-V*:Coarse-to-Fine Interactive Visual Reasoning for Multi-Page Document VQA

arXiv:2604.13731v1 Announce Type: new Abstract: Multi-page Document Visual Question Answering requires reasoning over semantics, layouts, and visual elements in long, visually dense documents. Existin

EVE: A Domain-Specific LLM Framework for Earth Intelligence

arXiv:2604.13071v1 Announce Type: new Abstract: We introduce Earth Virtual Expert (EVE), the first open-source, end-to-end initiative for developing and deploying domain-specialized LLMs for Earth Int