2 citations · 2 across the 3 of their papers we have counts for
3 papers
SVHalluc: Benchmarking Speech-Vision Hallucination in Audio-Visual Large Language Models
Chenshuang Zhang, Kyeong Seon Kim, Chengxin Liu +1
Despite the success of audio-visual large-language models (LLMs), they can produce plausible but ungrounded outputs, termed hallucination. Existing benchmarks focus on environmenta…
Blind to the Human Touch: Overlap Bias in LLM-Based Summary Evaluation
Jiangnan Fang, Cheng-Tse Liu, Hanieh Deilamsalehy +5
Large language model (LLM) judges have often been used alongside traditional, algorithm-based metrics for tasks like summarization because they better capture semantic information,…
Multi-LLM Text Summarization
Jiangnan Fang, Cheng-Tse Liu, Jieun Kim +9
In this work, we propose a Multi-LLM summarization framework, and investigate two different multi-LLM strategies including centralized and decentralized. Our multi-LLM summarizatio…