Image de couverture de livre

Why Language Models Hallucinate

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Kalai, Adam Tauman, Nachum, Ofir, Vempala, Santosh S., Zhang, Edwin
Format:	Preprint
Publié:	2025
Sujets:	Computation and Language
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Calibrated Language Models Must Hallucinate
par: Kalai, Adam Tauman, et autres
Publié: (2023)

Meta-Prompting: Enhancing Language Models with Task-Agnostic Scaffolding
par: Suzgun, Mirac, et autres
Publié: (2024)

Do Language Models Know When They're Hallucinating References?
par: Agrawal, Ayush, et autres
Publié: (2023)

On Non-interactive Evaluation of Animal Communication Translators
par: Paradise, Orr, et autres
Publié: (2025)

Self-Taught Optimizer (STOP): Recursively Self-Improving Code Generation
par: Zelikman, Eric, et autres
Publié: (2023)

Consensus Sampling for Safer Generative AI
par: Kalai, Adam Tauman, et autres
Publié: (2025)

UtilityMax Prompting: A Formal Framework for Multi-Objective Large Language Model Tasks
par: Marom, Ofir
Publié: (2026)

First-Person Fairness in Chatbots
par: Eloundou, Tyna, et autres
Publié: (2024)

Compiling Any $\mathsf{MIP}^{*}$ into a (Succinct) Classical Interactive Argument
par: Huang, Andrew, et autres
Publié: (2025)

Parallel Repetition for Post-Quantum Arguments
par: Huang, Andrew, et autres
Publié: (2025)

The Pitfalls of Publishing in the Age of LLMs: Strange and Surprising Adventures with a High-Impact NLP Journal
par: Verma, Rakesh M., et autres
Publié: (2024)

ULTRA: Unleash LLMs' Potential for Event Argument Extraction through Hierarchical Modeling and Pair-wise Self-Refinement
par: Zhang, Xinliang Frederick, et autres
Publié: (2024)

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

Mitigating Hallucinations in Large Vision-Language Models by Self-Injecting Hallucinations
par: Lu, Yifan, et autres
Publié: (2025)

Style Classification of Rabbinic Literature for Detection of Lost Midrash Tanhuma Material
par: Tannor, Shlomo, et autres
Publié: (2022)

The Hallucinations Leaderboard -- An Open Effort to Measure Hallucinations in Large Language Models
par: Hong, Giwon, et autres
Publié: (2024)

Why and How LLMs Hallucinate: Connecting the Dots with Subsequence Associations
par: Sun, Yiyou, et autres
Publié: (2025)

Estimating the Influence of Sequentially Correlated Literary Properties in Textual Classification: A Data-Centric Hypothesis-Testing Approach
par: Yoffe, Gideon, et autres
Publié: (2024)

CPLLM: Clinical Prediction with Large Language Models
par: Shoham, Ofir Ben, et autres
Publié: (2023)

Hallucination Detection and Evaluation of Large Language Model
par: Zhang, Chenggong, et autres
Publié: (2025)

Efficiently Batching Unambiguous Interactive Proofs
par: Berger, Bonnie, et autres
Publié: (2025)

Prompt-Guided Internal States for Hallucination Detection of Large Language Models
par: Zhang, Fujie, et autres
Publié: (2024)

Multilingual Hallucination Gaps in Large Language Models
par: Chataigner, Cléa, et autres
Publié: (2024)

Exploring Causal Effect of Social Bias on Faithfulness Hallucinations in Large Language Models
par: Zhang, Zhenliang, et autres
Publié: (2025)

Knowledge Overshadowing Causes Amalgamated Hallucination in Large Language Models
par: Zhang, Yuji, et autres
Publié: (2024)

Leveraging NTPs for Efficient Hallucination Detection in VLMs
par: Azachi, Ofir, et autres
Publié: (2025)

Quantity Matters: Towards Assessing and Mitigating Number Hallucination in Large Vision-Language Models
par: Zhang, Huixuan, et autres
Publié: (2024)

Exploring and Mitigating Fawning Hallucinations in Large Language Models
par: Shangguan, Zixuan, et autres
Publié: (2025)

Measuring Language Model Hallucinations Through Distributional Correctness
par: Burns, Thomas F
Publié: (2025)

Large Language Models Hallucination: A Comprehensive Survey
par: Alansari, Aisha, et autres
Publié: (2025)

Language Models Hallucinate, but May Excel at Fact Verification
par: Guan, Jian, et autres
Publié: (2023)

Fine-grained Hallucination Detection and Editing for Language Models
par: Mishra, Abhika, et autres
Publié: (2024)

Mitigating Large Language Model Hallucination with Faithful Finetuning
par: Hu, Minda, et autres
Publié: (2024)

Look Within, Why LLMs Hallucinate: A Causal Perspective
par: Li, He, et autres
Publié: (2024)

Hallucination Detection with Small Language Models
par: Cheung, Ming
Publié: (2025)

HAD: HAllucination Detection Language Models Based on a Comprehensive Hallucination Taxonomy
par: Xu, Fan, et autres
Publié: (2025)

Loki's Dance of Illusions: A Comprehensive Survey of Hallucination in Large Language Models
par: Li, Chaozhuo, et autres
Publié: (2025)

Knowledge Editing in Language Models via Adapted Direct Preference Optimization
par: Rozner, Amit, et autres
Publié: (2024)

Copy-Paste to Mitigate Large Language Model Hallucinations
par: Long, Yongchao, et autres
Publié: (2025)

ANAH: Analytical Annotation of Hallucinations in Large Language Models
par: Ji, Ziwei, et autres
Publié: (2024)