8 citations · 9 across the 22 of their papers we have counts for
5 papers · 1 filter
A Survey on the Honesty of Large Language Models
Siheng Li, Cheng Yang, Taiqiang Wu +12
Honesty is a fundamental principle for aligning large language models (LLMs) with human values, requiring these models to recognize what they know and don't know and be able to fai…
Think out Loud: Emotion Deducing Explanation in Dialogues
Jiangnan Li, Zheng Lin, Lanrui Wang +6
Humans convey emotions through daily dialogues, making emotion understanding a crucial step of affective intelligence. To understand emotions in dialogues, machines are asked to re…
Previously on the Stories: Recap Snippet Identification for Story Reading
Jiangnan Li, Qiujing Wang, Liyan Xu +5
Similar to the "previously-on" scenes in TV shows, recaps can help book reading by recalling the readers' memory about the important elements in previous texts to better understand…
Fine-Grained Modeling of Narrative Context: A Coherence Perspective via Retrospective Questions
Liyan Xu, Jiangnan Li, Mo Yu +1
This work introduces an original and practical paradigm for narrative comprehension, stemming from the characteristics that individual passages within narratives tend to be more co…
Identifying Factual Inconsistencies in Summaries: Grounding LLM Inference via Task Taxonomy
Liyan Xu, Zhenlin Su, Mo Yu +4
Factual inconsistencies pose a significant hurdle for the faithful summarization by generative models. While a major direction to enhance inconsistency detection is to derive stron…