8 citations · 42 across the 24 of their papers we have counts for
5 papers · 1 filter
MentalArena: Self-play Training of Language Models for Diagnosis and Treatment of Mental Health Disorders
Cheng Li, May Fung, Qingyun Wang +4
Mental health disorders are one of the most serious diseases in the world. Most people with such a disease lack access to adequate care, which highlights the importance of training…
Knowledge Overshadowing Causes Amalgamated Hallucination in Large Language Models
Yuji Zhang, Sha Li, Jiateng Liu +5
Hallucination is often regarded as a major impediment for using large language models (LLMs), especially for knowledge-intensive tasks. Even when the training corpus consists solel…
Why Does New Knowledge Create Messy Ripple Effects in LLMs?
Jiaxin Qin, Zixuan Zhang, Manling Li +2
Extensive previous research has focused on post-training knowledge editing (KE) for language models (LMs) to ensure that knowledge remains accurate and up-to-date. One desired prop…
Visually Descriptive Language Model for Vector Graphics Reasoning
Zhenhailong Wang, Joy Hsu, Xingyao Wang +4
Despite significant advancements, large multimodal models (LMMs) still struggle to bridge the gap between low-level visual perception -- focusing on shapes, sizes, and layouts -- a…
Can LLMs Produce Faithful Explanations For Fact-checking? Towards Faithful Explainable Fact-Checking via Multi-Agent Debate
Kyungha Kim, Sangyun Lee, Kung-Hsiang Huang +3
Fact-checking research has extensively explored verification but less so the generation of natural-language explanations, crucial for user trust. While Large Language Models (LLMs)…