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Hallucinate at the Last in Long Response Generation: A Case Study on Long Document Summarization
v1v2v3 (latest)

Hallucinate at the Last in Long Response Generation: A Case Study on Long Document Summarization

21 May 2025
Joonho Yang
Seunghyun Yoon
Hwan Chang
Byeongjeong Kim
Hwanhee Lee
    HILM
ArXiv (abs)PDFHTMLGithub (67466★)

Papers citing "Hallucinate at the Last in Long Response Generation: A Case Study on Long Document Summarization"

5 / 5 papers shown
The Curious Case of Factual (Mis)Alignment between LLMs' Short- and Long-Form Answers
The Curious Case of Factual (Mis)Alignment between LLMs' Short- and Long-Form Answers
Saad Obaid ul Islam
Anne Lauscher
Goran Glavaš
HILM
222
0
0
13 Oct 2025
Evaluating Evaluation Metrics -- The Mirage of Hallucination Detection
Evaluating Evaluation Metrics -- The Mirage of Hallucination Detection
Atharva Kulkarni
Yuan-kang Zhang
Joel Ruben Antony Moniz
Xiou Ge
Bo-Hsiang Tseng
Dhivya Piraviperumal
Siyang Song
Hong-ye Yu
HILM
383
5
0
25 Apr 2025
Mitigating Hallucinations in Large Vision-Language Models via Summary-Guided Decoding
Mitigating Hallucinations in Large Vision-Language Models via Summary-Guided DecodingNorth American Chapter of the Association for Computational Linguistics (NAACL), 2024
Kyungmin Min
Minbeom Kim
Kang-il Lee
Dongryeol Lee
Kyomin Jung
MLLM
454
13
0
20 Feb 2025
Learning to Summarize from LLM-generated Feedback
Learning to Summarize from LLM-generated FeedbackNorth American Chapter of the Association for Computational Linguistics (NAACL), 2024
Hwanjun Song
Taewon Yun
Yuho Lee
Jihwan Oh
Gihun Lee
Jason (Jinglun) Cai
Hang Su
367
16
0
28 Jan 2025
AdaCAD: Adaptively Decoding to Balance Conflicts between Contextual and Parametric Knowledge
AdaCAD: Adaptively Decoding to Balance Conflicts between Contextual and Parametric KnowledgeNorth American Chapter of the Association for Computational Linguistics (NAACL), 2024
Han Wang
Archiki Prasad
Elias Stengel-Eskin
Joey Tianyi Zhou
475
18
0
11 Sep 2024
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