:: Library Catalog

Image de couverture de livre

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Rana, Annu, Kumar, Gaurav
Format:	Preprint
Publié:	2025
Sujets:	Artificial Intelligence
Accès en ligne:	https://arxiv.org/abs/2512.14474
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Can a Hallucinating Model help in Reducing Human "Hallucination"?
par: Sundaram, Sowmya S, et autres
Publié: (2024)

Cognitive Agent Compilation for Explicit Problem Solver Modeling
par: Moon, Hyeongdon, et autres
Publié: (2026)

OR-LLM-Agent: Automating Modeling and Solving of Operations Research Optimization Problems with Reasoning LLM
par: Zhang, Bowen, et autres
Publié: (2025)

A survey of agent interoperability protocols: Model Context Protocol (MCP), Agent Communication Protocol (ACP), Agent-to-Agent Protocol (A2A), and Agent Network Protocol (ANP)
par: Ehtesham, Abul, et autres
Publié: (2025)

A Novel Multi-Agent Architecture to Reduce Hallucinations of Large Language Models in Multi-Step Structural Modeling
par: Geng, Ziheng, et autres
Publié: (2026)

LLM Enhancement with Domain Expert Mental Model to Reduce LLM Hallucination with Causal Prompt Engineering
par: Kovalerchuk, Boris, et autres
Publié: (2025)

RAG-KG-IL: A Multi-Agent Hybrid Framework for Reducing Hallucinations and Enhancing LLM Reasoning through RAG and Incremental Knowledge Graph Learning Integration
par: Yu, Hong Qing, et autres
Publié: (2025)

Visual Description Grounding Reduces Hallucinations and Boosts Reasoning in LVLMs
par: Ghosh, Sreyan, et autres
Publié: (2024)

A Formal Security Framework for MCP-Based AI Agents: Threat Taxonomy, Verification Models, and Defense Mechanisms
par: Acharya, Nirajan, et autres
Publié: (2026)

Enhancing Decision-Making in Optimization through LLM-Assisted Inference: A Neural Networks Perspective
par: Singh, Gaurav, et autres
Publié: (2024)

The First Impression Problem: Internal Bias Triggers Overthinking in Reasoning Models
par: Dang, Renfei, et autres
Publié: (2025)

MM-Agent: LLM as Agents for Real-world Mathematical Modeling Problem
par: Liu, Fan, et autres
Publié: (2025)

LLM-Driven Collaborative Model for Untangling Commits via Explicit and Implicit Dependency Reasoning
par: Hou, Bo, et autres
Publié: (2025)

OptArgus: A Multi-Agent System to Detect Hallucinations in LLM-based Optimization Modeling
par: Li, Zhong, et autres
Publié: (2026)

Alleviating Hallucinations of Large Language Models through Induced Hallucinations
par: Zhang, Yue, et autres
Publié: (2023)

SIDiffAgent: Self-Improving Diffusion Agent
par: Garg, Shivank, et autres
Publié: (2026)

Exposing Weaknesses of Large Reasoning Models through Graph Algorithm Problems
par: Zhang, Qifan, et autres
Publié: (2026)

LinTree: Improving LLM Reasoning with Explicitly Structured Search Histories
par: Kang, Liwei, et autres
Publié: (2026)

Predictive Scheduling for Efficient Inference-Time Reasoning in Large Language Models
par: Brown, Katrina, et autres
Publié: (2026)

MIRAGE-Bench: LLM Agent is Hallucinating and Where to Find Them
par: Zhang, Weichen, et autres
Publié: (2025)

Reasoning Models Hallucinate More: Factuality-Aware Reinforcement Learning for Large Reasoning Models
par: Li, Junyi, et autres
Publié: (2025)

DrugR: Optimizing Molecular Drugs through LLM-based Explicit Reasoning
par: Liu, Haoran, et autres
Publié: (2026)

Measuring and Reducing LLM Hallucination without Gold-Standard Answers
par: Wei, Jiaheng, et autres
Publié: (2024)

Coarse-to-Fine Highlighting: Reducing Knowledge Hallucination in Large Language Models
par: Lv, Qitan, et autres
Publié: (2024)

Towards Trustworthy Legal AI through LLM Agents and Formal Reasoning
par: Chen, Linze, et autres
Publié: (2025)

Reasoning Matters: Mitigate Hallucination in Multimodal Large Reasoning Models via Reasoning-Conditioned Preference Optimization
par: Kong, Jiawei, et autres
Publié: (2026)

Enhancing Multi-Agent Consensus through Third-Party LLM Integration: Analyzing Uncertainty and Mitigating Hallucinations in Large Language Models
par: Duan, Zhihua, et autres
Publié: (2024)

Understanding LLM Scientific Reasoning through Promptings and Model's Explanation on the Answers
par: Rueda, Alice, et autres
Publié: (2025)

Reducing Hallucinations in LLM-based Scientific Literature Analysis Using Peer Context Outlier Detection
par: Xie, Daniel, et autres
Publié: (2026)

PRISM: Probing Reasoning, Instruction, and Source Memory in LLM Hallucinations
par: Wu, Yuhe, et autres
Publié: (2026)

Winning Big with Small Models: Knowledge Distillation vs. Self-Training for Reducing Hallucination in Product QA Agents
par: Lewis, Ashley, et autres
Publié: (2025)

Towards Reasoning Ability of Small Language Models
par: Srivastava, Gaurav, et autres
Publié: (2025)

The Reasoning Trap: How Enhancing LLM Reasoning Amplifies Tool Hallucination
par: Yin, Chenlong, et autres
Publié: (2025)

Multi-Modal Fact-Verification Framework for Reducing Hallucinations in Large Language Models
par: Patel, Piyushkumar
Publié: (2025)

Micro-Macro Retrieval: Reducing Long-Form Hallucination in Large Language Models
par: Feng, Yujie, et autres
Publié: (2026)

Orla: A Library for Serving LLM-Based Multi-Agent Systems
par: Shahout, Rana, et autres
Publié: (2026)

SALM: A Multi-Agent Framework for Language Model-Driven Social Network Simulation
par: Koley, Gaurav
Publié: (2025)

PruneHal: Reducing Hallucinations in Multi-modal Large Language Models through Adaptive KV Cache Pruning
par: Sun, Fengyuan, et autres
Publié: (2025)

Reinforce LLM Reasoning through Multi-Agent Reflection
par: Yuan, Yurun, et autres
Publié: (2025)

Entropy Distribution as a Fingerprint for Hallucinations in Generative Models
par: Villani, Mattia J., et autres
Publié: (2026)