:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	García, Fernando Gabriela, Shi, Qiyang, Feng, Zilin
Format:	Preprint
Published:	2025
Subjects:	Computation and Language
Online Access:	https://arxiv.org/abs/2509.05741
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

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

Factuality or Fiction? Benchmarking Modern LLMs on Ambiguous QA with Citations
by: Patel, Maya, et al.
Published: (2024)

Self-Alignment for Factuality: Mitigating Hallucinations in LLMs via Self-Evaluation
by: Zhang, Xiaoying, et al.
Published: (2024)

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

FACTS&EVIDENCE: An Interactive Tool for Transparent Fine-Grained Factual Verification of Machine-Generated Text
by: Boonsanong, Varich, et al.
Published: (2025)

Context-Enhanced Language Models for Generating Multi-Paper Citations
by: Anand, Avinash, et al.
Published: (2024)

Beyond Self-Consistency: Ensemble Reasoning Boosts Consistency and Accuracy of LLMs in Cancer Staging
by: Chang, Chia-Hsuan, et al.
Published: (2024)

DnDScore: Decontextualization and Decomposition for Factuality Verification in Long-Form Text Generation
by: Wanner, Miriam, et al.
Published: (2024)

Trustworthy Reasoning: Evaluating and Enhancing Factual Accuracy in LLM Intermediate Thought Processes
by: Jiao, Rui, et al.
Published: (2025)

Better To Ask in English? Evaluating Factual Accuracy of Multilingual LLMs in English and Low-Resource Languages
by: Rohera, Pritika, et al.
Published: (2025)

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

CiteFix: Enhancing RAG Accuracy Through Post-Processing Citation Correction
by: Maheshwari, Harsh, et al.
Published: (2025)

UAQFact: Evaluating Factual Knowledge Utilization of LLMs on Unanswerable Questions
by: Tan, Chuanyuan, et al.
Published: (2025)

Multi-FAct: Assessing Factuality of Multilingual LLMs using FActScore
by: Shafayat, Sheikh, et al.
Published: (2024)

Aligning Knowledge Graphs and Language Models for Factual Accuracy
by: Nishat, Nur A Zarin, et al.
Published: (2025)

Evaluating Factual Density in Multi-Source RAG: A Study in Medical AI Accuracy
by: DeMarco, Michael R.
Published: (2026)

Building Task Bots with Self-learning for Enhanced Adaptability, Extensibility, and Factuality
by: Zhang, Xiaoying
Published: (2025)

Grounded Visual Factualization: Factual Anchor-Based Finetuning for Enhancing MLLM Factual Consistency
by: Morbiato, Filippo, et al.
Published: (2025)

LongCite: Enabling LLMs to Generate Fine-grained Citations in Long-context QA
by: Zhang, Jiajie, et al.
Published: (2024)

DiVA: Fine-grained Factuality Verification with Agentic-Discriminative Verifier
by: Huang, Hui, et al.
Published: (2026)

Enhancing Presentation Slide Generation by LLMs with a Multi-Staged End-to-End Approach
by: Bandyopadhyay, Sambaran, et al.
Published: (2024)

TOOLVERIFIER: Generalization to New Tools via Self-Verification
by: Mekala, Dheeraj, et al.
Published: (2024)

Inside-Out: Hidden Factual Knowledge in LLMs
by: Gekhman, Zorik, et al.
Published: (2025)

LLMs as Repositories of Factual Knowledge: Limitations and Solutions
by: Mousavi, Seyed Mahed, et al.
Published: (2025)

Investigating Factuality in Long-Form Text Generation: The Roles of Self-Known and Self-Unknown
by: Tu, Lifu, et al.
Published: (2024)

MoleculeQA: A Dataset to Evaluate Factual Accuracy in Molecular Comprehension
by: Lu, Xingyu, et al.
Published: (2024)

Systematic Task Exploration with LLMs: A Study in Citation Text Generation
by: Şahinuç, Furkan, et al.
Published: (2024)

Citation-Enhanced Generation for LLM-based Chatbots
by: Li, Weitao, et al.
Published: (2024)

Improving Factuality in LLMs via Inference-Time Knowledge Graph Construction
by: Wu, Shanglin, et al.
Published: (2025)

ART: Attention Replacement Technique to Improve Factuality in LLMs
by: Luo, Ziqin, et al.
Published: (2026)

Beyond Factual Accuracy: Evaluating Global Reasoning Integrity in RAG Systems with LogicScore
by: Yan, Zhichao, et al.
Published: (2026)

Persuasion Tokens for Editing Factual Knowledge in LLMs
by: Youssef, Paul, et al.
Published: (2026)

Mask-DPO: Generalizable Fine-grained Factuality Alignment of LLMs
by: Gu, Yuzhe, et al.
Published: (2025)

AMRFact: Enhancing Summarization Factuality Evaluation with AMR-Driven Negative Samples Generation
by: Qiu, Haoyi, et al.
Published: (2023)

Prompting Science Report 4: Playing Pretend: Expert Personas Don't Improve Factual Accuracy
by: Basil, Savir, et al.
Published: (2025)

Improving Factual Accuracy of Neural Table-to-Text Output by Addressing Input Problems in ToTTo
by: Sundararajan, Barkavi, et al.
Published: (2024)

Self-Consistent Decoding for More Factual Open Responses
by: Malon, Christopher, et al.
Published: (2024)

Is Factuality Enhancement a Free Lunch For LLMs? Better Factuality Can Lead to Worse Context-Faithfulness
by: Bi, Baolong, et al.
Published: (2024)

Exploring the Generalizability of Factual Hallucination Mitigation via Enhancing Precise Knowledge Utilization
by: Zhang, Siyuan, et al.
Published: (2025)

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