Cover Image

Theoretical Foundations and Mitigation of Hallucination in Large Language Models

Fuente: arXiv

Saved in:

Bibliographic Details
Main Author:	Gumaan, Esmail
Format:	Preprint
Published:	2025
Subjects:	Computation and Language Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

ExpertRAG: Efficient RAG with Mixture of Experts -- Optimizing Context Retrieval for Adaptive LLM Responses
by: Gumaan, Esmail
Published: (2025)

Mixture of Attention Schemes (MoAS): Learning to Route Between MHA, GQA, and MQA
by: Gumaan, Esmail
Published: (2025)

Universal Approximation Theorem for a Single-Layer Transformer
by: Gumaan, Esmail
Published: (2025)

Whispers that Shake Foundations: Analyzing and Mitigating False Premise Hallucinations in Large Language Models
by: Yuan, Hongbang, et al.
Published: (2024)

An Evolutionary Large Language Model for Hallucination Mitigation
by: Boulesnane, Abdennour, et al.
Published: (2024)

Copy-Paste to Mitigate Large Language Model Hallucinations
by: Long, Yongchao, et al.
Published: (2025)

Counterfactual Probing for Hallucination Detection and Mitigation in Large Language Models
by: Feng, Yijun
Published: (2025)

Delta -- Contrastive Decoding Mitigates Text Hallucinations in Large Language Models
by: Huang, Cheng Peng, et al.
Published: (2025)

Noise Augmented Fine Tuning for Mitigating Hallucinations in Large Language Models
by: Khadangi, Afshin, et al.
Published: (2025)

Galvatron: Automatic Distributed Training for Large Transformer Models
by: Gumaan, Esmail
Published: (2025)

HICD: Hallucination-Inducing via Attention Dispersion for Contrastive Decoding to Mitigate Hallucinations in Large Language Models
by: Jiang, Xinyan, et al.
Published: (2025)

Mitigating Hallucinated Translations in Large Language Models with Hallucination-focused Preference Optimization
by: Tang, Zilu, et al.
Published: (2025)

MALM: A Multi-Information Adapter for Large Language Models to Mitigate Hallucination
by: Jia, Ao, et al.
Published: (2025)

Mitigating Multilingual Hallucination in Large Vision-Language Models
by: Qu, Xiaoye, et al.
Published: (2024)

Mitigating Hallucinations in Large Language Models via Causal Reasoning
by: Li, Yuangang, et al.
Published: (2025)

Credal Transformer: A Principled Approach for Quantifying and Mitigating Hallucinations in Large Language Models
by: Ji, Shihao, et al.
Published: (2025)

HAVE: Head-Adaptive Gating and ValuE Calibration for Hallucination Mitigation in Large Language Models
by: Tong, Xin, et al.
Published: (2025)

Beyond Fine-Tuning: Effective Strategies for Mitigating Hallucinations in Large Language Models for Data Analytics
by: Rumiantsau, Mikhail, et al.
Published: (2024)

CPR: Mitigating Large Language Model Hallucinations with Curative Prompt Refinement
by: Shim, Jung-Woo, et al.
Published: (2025)

Multi-stage Prompt Refinement for Mitigating Hallucinations in Large Language Models
by: Shim, Jung-Woo, et al.
Published: (2025)

Self-contradictory Hallucinations of Large Language Models: Evaluation, Detection and Mitigation
by: Mündler, Niels, et al.
Published: (2023)

Mechanistic Understanding and Mitigation of Language Model Non-Factual Hallucinations
by: Yu, Lei, et al.
Published: (2024)

Alleviating Hallucinations of Large Language Models through Induced Hallucinations
by: Zhang, Yue, et al.
Published: (2023)

Mitigating Hallucination in Large Language Models (LLMs): An Application-Oriented Survey on RAG, Reasoning, and Agentic Systems
by: Li, Yihan, et al.
Published: (2025)

Mitigating Behavioral Hallucination in Multimodal Large Language Models for Sequential Images
by: You, Liangliang, et al.
Published: (2025)

Investigating and Mitigating the Multimodal Hallucination Snowballing in Large Vision-Language Models
by: Zhong, Weihong, et al.
Published: (2024)

Hallucination Detection and Hallucination Mitigation: An Investigation
by: Luo, Junliang, et al.
Published: (2024)

Hybrid Retrieval for Hallucination Mitigation in Large Language Models: A Comparative Analysis
by: Mala, Chandana Sree, et al.
Published: (2025)

Uncertainty-Aware Fusion: An Ensemble Framework for Mitigating Hallucinations in Large Language Models
by: Dey, Prasenjit, et al.
Published: (2025)

Mitigating Hallucination in Multimodal Large Language Model via Hallucination-targeted Direct Preference Optimization
by: Fu, Yuhan, et al.
Published: (2024)

Mitigating Hallucinations in Large Vision-Language Models via Summary-Guided Decoding
by: Min, Kyungmin, et al.
Published: (2024)

Delve into Visual Contrastive Decoding for Hallucination Mitigation of Large Vision-Language Models
by: Lee, Yi-Lun, et al.
Published: (2024)

Detection and Mitigation of Hallucination in Large Reasoning Models: A Mechanistic Perspective
by: Sun, Zhongxiang, et al.
Published: (2025)

Mitigating Geospatial Knowledge Hallucination in Large Language Models: Benchmarking and Dynamic Factuality Aligning
by: Wang, Shengyuan, et al.
Published: (2025)

Ever: Mitigating Hallucination in Large Language Models through Real-Time Verification and Rectification
by: Kang, Haoqiang, et al.
Published: (2023)

Mitigating Hallucinations in Large Vision-Language Models with Instruction Contrastive Decoding
by: Wang, Xintong, et al.
Published: (2024)

Mitigating Hallucinations Using Ensemble of Knowledge Graph and Vector Store in Large Language Models to Enhance Mental Health Support
by: Muqtadir, Abdul, et al.
Published: (2024)

Interactive DualChecker for Mitigating Hallucinations in Distilling Large Language Models
by: Wang, Meiyun, et al.
Published: (2024)

Mitigating Hallucinations in Large Vision-Language Models (LVLMs) via Language-Contrastive Decoding (LCD)
by: Manevich, Avshalom, et al.
Published: (2024)

The Impact of Negated Text on Hallucination with Large Language Models
by: Seo, Jaehyung, et al.
Published: (2025)