Saved in:
| Main Authors: | Zhang, Xiao, Li, Miao, Wu, Ji |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2409.14057 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Conditional Language Learning with Context
by: Zhang, Xiao, et al.
Published: (2024)
by: Zhang, Xiao, et al.
Published: (2024)
Relation Also Knows: Rethinking the Recall and Editing of Factual Associations in Auto-Regressive Transformer Language Models
by: Liu, Xiyu, et al.
Published: (2024)
by: Liu, Xiyu, et al.
Published: (2024)
Fine-tuning Large Language Models for Improving Factuality in Legal Question Answering
by: Hu, Yinghao, et al.
Published: (2025)
by: Hu, Yinghao, et al.
Published: (2025)
Improving Factuality in Large Language Models via Decoding-Time Hallucinatory and Truthful Comparators
by: Yang, Dingkang, et al.
Published: (2024)
by: Yang, Dingkang, et al.
Published: (2024)
AutoHall: Automated Factuality Hallucination Dataset Generation for Large Language Models
by: Cao, Zouying, et al.
Published: (2023)
by: Cao, Zouying, et al.
Published: (2023)
SimpleVQA: Multimodal Factuality Evaluation for Multimodal Large Language Models
by: Cheng, Xianfu, et al.
Published: (2025)
by: Cheng, Xianfu, et al.
Published: (2025)
UFO: a Unified and Flexible Framework for Evaluating Factuality of Large Language Models
by: Huang, Zhaoheng, et al.
Published: (2024)
by: Huang, Zhaoheng, et al.
Published: (2024)
The Dawn After the Dark: An Empirical Study on Factuality Hallucination in Large Language Models
by: Li, Junyi, et al.
Published: (2024)
by: Li, Junyi, et al.
Published: (2024)
Investigating the Factual Knowledge Boundary of Large Language Models with Retrieval Augmentation
by: Ren, Ruiyang, et al.
Published: (2023)
by: Ren, Ruiyang, et al.
Published: (2023)
CodeSimpleQA: Scaling Factuality in Code Large Language Models
by: Yang, Jian, et al.
Published: (2025)
by: Yang, Jian, et al.
Published: (2025)
Locating and Editing Factual Associations in Mamba
by: Sharma, Arnab Sen, et al.
Published: (2024)
by: Sharma, Arnab Sen, et al.
Published: (2024)
DHI: Leveraging Diverse Hallucination Induction for Enhanced Contrastive Factuality Control in Large Language Models
by: Guo, Jiani, et al.
Published: (2026)
by: Guo, Jiani, et al.
Published: (2026)
Language Models' Factuality Depends on the Language of Inquiry
by: Aggarwal, Tushar, et al.
Published: (2025)
by: Aggarwal, Tushar, et al.
Published: (2025)
Gradient Co-occurrence Analysis for Detecting Unsafe Prompts in Large Language Models
by: Yang, Jingyuan, et al.
Published: (2025)
by: Yang, Jingyuan, et al.
Published: (2025)
Interpreting Key Mechanisms of Factual Recall in Transformer-Based Language Models
by: Lv, Ang, et al.
Published: (2024)
by: Lv, Ang, et al.
Published: (2024)
Factuality Challenges in the Era of Large Language Models
by: Augenstein, Isabelle, et al.
Published: (2023)
by: Augenstein, Isabelle, et al.
Published: (2023)
Towards Understanding Continual Factual Knowledge Acquisition of Language Models: From Theory to Algorithm
by: Wang, Haoyu, et al.
Published: (2026)
by: Wang, Haoyu, et al.
Published: (2026)
Towards Statistical Factuality Guarantee for Large Vision-Language Models
by: Li, Zhuohang, et al.
Published: (2025)
by: Li, Zhuohang, et al.
Published: (2025)
Unmasking the Factual-Conceptual Gap in Persian Language Models
by: Sakhaeirad, Alireza, et al.
Published: (2026)
by: Sakhaeirad, Alireza, et al.
Published: (2026)
Reasoning Factual Knowledge in Structured Data with Large Language Models
by: Huang, Sirui, et al.
Published: (2024)
by: Huang, Sirui, et al.
Published: (2024)
Retrieval Head Mechanistically Explains Long-Context Factuality
by: Wu, Wenhao, et al.
Published: (2024)
by: Wu, Wenhao, et al.
Published: (2024)
Factuality of Large Language Models: A Survey
by: Wang, Yuxia, et al.
Published: (2024)
by: Wang, Yuxia, et al.
Published: (2024)
Factual Consistency of Multilingual Pretrained Language Models
by: Fierro, Constanza, et al.
Published: (2022)
by: Fierro, Constanza, et al.
Published: (2022)
Generating Benchmarks for Factuality Evaluation of Language Models
by: Muhlgay, Dor, et al.
Published: (2023)
by: Muhlgay, Dor, et al.
Published: (2023)
Conformal Language Model Reasoning with Coherent Factuality
by: Rubin-Toles, Maxon, et al.
Published: (2025)
by: Rubin-Toles, Maxon, et al.
Published: (2025)
Editing Factual Knowledge and Explanatory Ability of Medical Large Language Models
by: Xu, Derong, et al.
Published: (2024)
by: Xu, Derong, et al.
Published: (2024)
Multilingual Knowledge Editing with Language-Agnostic Factual Neurons
by: Zhang, Xue, et al.
Published: (2024)
by: Zhang, Xue, et al.
Published: (2024)
Language Models with Conformal Factuality Guarantees
by: Mohri, Christopher, et al.
Published: (2024)
by: Mohri, Christopher, et al.
Published: (2024)
PretrainRL: Alleviating Factuality Hallucination of Large Language Models at the Beginning
by: Liu, Langming, et al.
Published: (2026)
by: Liu, Langming, et al.
Published: (2026)
FactBench: A Dynamic Benchmark for In-the-Wild Language Model Factuality Evaluation
by: Bayat, Farima Fatahi, et al.
Published: (2024)
by: Bayat, Farima Fatahi, et al.
Published: (2024)
Hierarchical Concept Geometry in Language Models Emerges from Word Co-occurrence
by: Nava, Andres, et al.
Published: (2026)
by: Nava, Andres, et al.
Published: (2026)
SWEA: Updating Factual Knowledge in Large Language Models via Subject Word Embedding Altering
by: Li, Xiaopeng, et al.
Published: (2024)
by: Li, Xiaopeng, et al.
Published: (2024)
The Illusionist's Prompt: Exposing the Factual Vulnerabilities of Large Language Models with Linguistic Nuances
by: Wang, Yining, et al.
Published: (2025)
by: Wang, Yining, et al.
Published: (2025)
CoCoTen: Detecting Adversarial Inputs to Large Language Models through Latent Space Features of Contextual Co-occurrence Tensors
by: Kadali, Sri Durga Sai Sowmya, et al.
Published: (2025)
by: Kadali, Sri Durga Sai Sowmya, et al.
Published: (2025)
Exploring the Factual Consistency in Dialogue Comprehension of Large Language Models
by: She, Shuaijie, et al.
Published: (2023)
by: She, Shuaijie, et al.
Published: (2023)
RULE: Reliable Multimodal RAG for Factuality in Medical Vision Language Models
by: Xia, Peng, et al.
Published: (2024)
by: Xia, Peng, et al.
Published: (2024)
Investigating Multi-Hop Factual Shortcuts in Knowledge Editing of Large Language Models
by: Ju, Tianjie, et al.
Published: (2024)
by: Ju, Tianjie, et al.
Published: (2024)
The Curious Case of Factuality Finetuning: Models' Internal Beliefs Can Improve Factuality
by: Newman, Benjamin, et al.
Published: (2025)
by: Newman, Benjamin, et al.
Published: (2025)
On the Distinctive Co-occurrence Characteristics of Antonymy
by: Cao, Zhihan, et al.
Published: (2025)
by: Cao, Zhihan, et al.
Published: (2025)
Temporally Consistent Factuality Probing for Large Language Models
by: Bajpai, Ashutosh, et al.
Published: (2024)
by: Bajpai, Ashutosh, et al.
Published: (2024)
Similar Items
-
Conditional Language Learning with Context
by: Zhang, Xiao, et al.
Published: (2024) -
Relation Also Knows: Rethinking the Recall and Editing of Factual Associations in Auto-Regressive Transformer Language Models
by: Liu, Xiyu, et al.
Published: (2024) -
Fine-tuning Large Language Models for Improving Factuality in Legal Question Answering
by: Hu, Yinghao, et al.
Published: (2025) -
Improving Factuality in Large Language Models via Decoding-Time Hallucinatory and Truthful Comparators
by: Yang, Dingkang, et al.
Published: (2024) -
AutoHall: Automated Factuality Hallucination Dataset Generation for Large Language Models
by: Cao, Zouying, et al.
Published: (2023)