:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Sng, Grace, Zhang, Yanming, Mueller, Klaus
Format:	Preprint
Published:	2024
Subjects:	Computation and Language Artificial Intelligence
Online Access:	https://arxiv.org/abs/2411.12759
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

CausalChat: Interactive Causal Model Development and Refinement Using Large Language Models
by: Zhang, Yanming, et al.
Published: (2024)

Multi-Agent Causal Discovery Using Large Language Models
by: Le, Hao Duong, et al.
Published: (2024)

Large Language Models for Constrained-Based Causal Discovery
by: Cohrs, Kai-Hendrik, et al.
Published: (2024)

Hallucinate Less by Thinking More: Aspect-Based Causal Abstention for Large Language Models
by: Nguyen, Vy, et al.
Published: (2025)

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

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

Large Language Models for Causal Discovery: Current Landscape and Future Directions
by: Wan, Guangya, et al.
Published: (2024)

Measuring and Eliminating Refusals in Military Large Language Models
by: FitzGerald, Jack, et al.
Published: (2026)

CCHall: A Novel Benchmark for Joint Cross-Lingual and Cross-Modal Hallucinations Detection in Large Language Models
by: Zhang, Yongheng, 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)

ANAH: Analytical Annotation of Hallucinations in Large Language Models
by: Ji, Ziwei, et al.
Published: (2024)

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

PFME: A Modular Approach for Fine-grained Hallucination Detection and Editing of Large Language Models
by: Deng, Kunquan, et al.
Published: (2024)

Trustworthy AI for Medicine: Continuous Hallucination Detection and Elimination with CHECK
by: Garcia-Fernandez, Carlos, et al.
Published: (2025)

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

Can Large Language Models Code Like a Linguist?: A Case Study in Low Resource Sound Law Induction
by: Naik, Atharva, et al.
Published: (2024)

Probing Causality Manipulation of Large Language Models
by: Zhang, Chenyang, et al.
Published: (2024)

Triggering Hallucinations in LLMs: A Quantitative Study of Prompt-Induced Hallucination in Large Language Models
by: Sato, Makoto
Published: (2025)

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

How Large Language Models are Designed to Hallucinate
by: Ackermann, Richard, et al.
Published: (2025)

Confabulation: The Surprising Value of Large Language Model Hallucinations
by: Sui, Peiqi, et al.
Published: (2024)

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

Theoretical Foundations and Mitigation of Hallucination in Large Language Models
by: Gumaan, Esmail
Published: (2025)

Where does In-context Translation Happen in Large Language Models
by: Sia, Suzanna, et al.
Published: (2024)

Coarse-to-Fine Highlighting: Reducing Knowledge Hallucination in Large Language Models
by: Lv, Qitan, et al.
Published: (2024)

Hallucination Detection: Robustly Discerning Reliable Answers in Large Language Models
by: Chen, Yuyan, et al.
Published: (2024)

Reference-free Hallucination Detection for Large Vision-Language Models
by: Li, Qing, et al.
Published: (2024)

Beyond Facts: Evaluating Intent Hallucination in Large Language Models
by: Hao, Yijie, et al.
Published: (2025)

HALO: An Ontology for Representing and Categorizing Hallucinations in Large Language Models
by: Nananukul, Navapat, et al.
Published: (2023)

Investigating Hallucinations in Pruned Large Language Models for Abstractive Summarization
by: Chrysostomou, George, et al.
Published: (2023)

Neural Probe-Based Hallucination Detection for Large Language Models
by: Liang, Shize, et al.
Published: (2025)

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

ANAH-v2: Scaling Analytical Hallucination Annotation of Large Language Models
by: Gu, Yuzhe, et al.
Published: (2024)

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

Disjoint Processing Mechanisms of Hierarchical and Linear Grammars in Large Language Models
by: Sankaranarayanan, Aruna, et al.
Published: (2025)

Large Legal Fictions: Profiling Legal Hallucinations in Large Language Models
by: Dahl, Matthew, et al.
Published: (2024)

Causality for Large Language Models
by: Wu, Anpeng, et al.
Published: (2024)

Micro-Macro Retrieval: Reducing Long-Form Hallucination in Large Language Models
by: Feng, Yujie, et al.
Published: (2026)

Measuring the Impact of Lexical Training Data Coverage on Hallucination Detection in Large Language Models
by: Zhang, Shuo, et al.
Published: (2025)

Causal Inference with Large Language Model: A Survey
by: Ma, Jing
Published: (2024)