SH2: Self-Highlighted Hesitation Helps You Decode More Truthfully

11 January 2024

Papers citing "SH2: Self-Highlighted Hesitation Helps You Decode More Truthfully"

9 / 9 papers shown

Title
Improving Factuality in Large Language Models via Decoding-Time Hallucinatory and Truthful Comparators Dingkang Yang Dongling Xiao Jinjie Wei Mingcheng Li Zhaoyu Chen Ke Li Li Zhang HILM 94 3 0 28 Jan 2025
HaloScope: Harnessing Unlabeled LLM Generations for Hallucination Detection Xuefeng Du Chaowei Xiao Yixuan Li HILM 37 18 0 26 Sep 2024
Paying More Attention to Image: A Training-Free Method for Alleviating Hallucination in LVLMs Shiping Liu Kecheng Zheng Wei Chen MLLM 52 34 0 31 Jul 2024
Mitigating Large Language Model Hallucination with Faithful Finetuning Minda Hu Bowei He Yufei Wang Liangyou Li Chen Ma Irwin King HILM 46 7 0 17 Jun 2024
TruthX: Alleviating Hallucinations by Editing Large Language Models in Truthful Space Shaolei Zhang Tian Yu Yang Feng HILM KELM 37 39 0 27 Feb 2024
Generating Benchmarks for Factuality Evaluation of Language Models Dor Muhlgay Ori Ram Inbal Magar Yoav Levine Nir Ratner Yonatan Belinkov Omri Abend Kevin Leyton-Brown Amnon Shashua Y. Shoham HILM 33 91 0 13 Jul 2023
How Language Model Hallucinations Can Snowball Muru Zhang Ofir Press William Merrill Alisa Liu Noah A. Smith HILM LRM 88 257 0 22 May 2023
Measuring Association Between Labels and Free-Text Rationales Sarah Wiegreffe Ana Marasović Noah A. Smith 282 170 0 24 Oct 2020
Teaching Machines to Read and Comprehend Karl Moritz Hermann Tomás Kociský Edward Grefenstette L. Espeholt W. Kay Mustafa Suleyman Phil Blunsom 211 3,513 0 10 Jun 2015