:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Wang, Jiaxin, Zhang, Lingling, Liu, Jun, Guo, Tianlin, Wu, Wenjun
Format:	Preprint
Published:	2024
Subjects:	Computation and Language
Online Access:	https://arxiv.org/abs/2401.06327
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Locomo-Plus: Beyond-Factual Cognitive Memory Evaluation Framework for LLM Agents
by: Li, Yifei, et al.
Published: (2026)

Few-shot Open Relation Extraction with Gaussian Prototype and Adaptive Margin
by: Guo, Tianlin, et al.
Published: (2024)

UniArk: Improving Generalisation and Consistency for Factual Knowledge Extraction through Debiasing
by: Yang, Yijun, et al.
Published: (2024)

General Phrase Debiaser: Debiasing Masked Language Models at a Multi-Token Level
by: Shi, Bingkang, et al.
Published: (2023)

Dual Debiasing: Remove Stereotypes and Keep Factual Gender for Fair Language Modeling and Translation
by: Limisiewicz, Tomasz, et al.
Published: (2025)

Semantic Consistency-Based Uncertainty Quantification for Factuality in Radiology Report Generation
by: Wang, Chenyu, et al.
Published: (2024)

Detecting Response Generation Not Requiring Factual Judgment
by: Kamei, Ryohei, et al.
Published: (2024)

Reducing Hallucinations in LLMs via Factuality-Aware Preference Learning
by: Chaduvula, Sindhuja, et al.
Published: (2026)

CLR-Fact: Evaluating the Complex Logical Reasoning Capability of Large Language Models over Factual Knowledge
by: Zheng, Tianshi, et al.
Published: (2024)

Only Say What You Know: Calibration-Aware Generation for Long-Form Factuality
by: Luo, Wen, et al.
Published: (2026)

A Diagnostic Benchmark for Sweden-Related Factual Knowledge
by: Kunz, Jenny
Published: (2025)

Memorization, Emergence, and Explaining Reversal Failures: A Controlled Study of Relational Semantics in LLMs
by: Zhu, Yihua, et al.
Published: (2026)

BARREL: Boundary-Aware Reasoning for Factual and Reliable LRMs
by: Yang, Junxiao, et al.
Published: (2025)

A Multi-LLM Debiasing Framework
by: Owens, Deonna M., et al.
Published: (2024)

Learning to Reason for Factuality
by: Chen, Xilun, et al.
Published: (2025)

Knowledgeable In-Context Tuning: Exploring and Exploiting Factual Knowledge for In-Context Learning
by: Wang, Jianing, et al.
Published: (2023)

CodeSimpleQA: Scaling Factuality in Code Large Language Models
by: Yang, Jian, et al.
Published: (2025)

Teacher-Student Training for Debiasing: General Permutation Debiasing for Large Language Models
by: Liusie, Adian, et al.
Published: (2024)

Factual and Edit-Sensitive Graph-to-Sequence Generation via Graph-Aware Adaptive Noising
by: Shahane, Aditya Hemant, et al.
Published: (2026)

Beyond Precision: Importance-Aware Recall for Factuality Evaluation in Long-Form LLM Generation
by: Jafari, Nazanin, et al.
Published: (2026)

Learning to Adapt SFT Data for Better Reasoning Generalization
by: Sun, Lisong, et al.
Published: (2026)

CPTuning: Contrastive Prompt Tuning for Generative Relation Extraction
by: Duan, Jiaxin, et al.
Published: (2025)

Co-occurrence is not Factual Association in Language Models
by: Zhang, Xiao, et al.
Published: (2024)

Learning to Generate Answers with Citations via Factual Consistency Models
by: Aly, Rami, et al.
Published: (2024)

Debiasing Multimodal Large Language Models via Noise-Aware Preference Optimization
by: Zhang, Zefeng, et al.
Published: (2025)

Localizing Factual Inconsistencies in Attributable Text Generation
by: Cattan, Arie, et al.
Published: (2024)

Happy: A Debiased Learning Framework for Continual Generalized Category Discovery
by: Ma, Shijie, et al.
Published: (2024)

Think Through Uncertainty: Improving Long-Form Generation Factuality via Reasoning Calibration
by: Liu, Xin, et al.
Published: (2026)

Relation Also Knows: Rethinking the Recall and Editing of Factual Associations in Auto-Regressive Transformer Language Models
by: Liu, Xiyu, et al.
Published: (2024)

A Debiased Nearest Neighbors Framework for Multi-Label Text Classification
by: Cheng, Zifeng, et al.
Published: (2024)

JointCQ: Improving Factual Hallucination Detection with Joint Claim and Query Generation
by: Xu, Fan, et al.
Published: (2025)

Factuality on Demand: Controlling the Factuality-Informativeness Trade-off in Text Generation
by: Gong, Ziwei, et al.
Published: (2026)

TruthfulRAG: Resolving Factual-level Conflicts in Retrieval-Augmented Generation with Knowledge Graphs
by: Liu, Shuyi, et al.
Published: (2025)

Beyond Factual Grounding: The Case for Opinion-Aware Retrieval-Augmented Generation
by: Agrawal, Aditya, et al.
Published: (2026)

Towards Statistical Factuality Guarantee for Large Vision-Language Models
by: Li, Zhuohang, et al.
Published: (2025)

Beyond Factual Accuracy: Evaluating Coverage of Diverse Factual Information in Long-form Text Generation
by: Samarinas, Chris, et al.
Published: (2025)

Fictitious Synthetic Data Can Improve LLM Factuality via Prerequisite Learning
by: Liu, Yujian, et al.
Published: (2024)

Evaluating Robustness of Generative Search Engine on Adversarial Factual Questions
by: Hu, Xuming, et al.
Published: (2024)

FLAME: Factuality-Aware Alignment for Large Language Models
by: Lin, Sheng-Chieh, et al.
Published: (2024)

Knowledge-Level Consistency Reinforcement Learning: Dual-Fact Alignment for Long-Form Factuality
by: Li, Junliang, et al.
Published: (2025)