69 citations · 174 across the 31 of their papers we have counts for
6 papers · 1 filter
Event Extraction in Large Language Model
Bobo Li, Xudong Han, Jiang Liu +11
Large language models (LLMs) and multimodal LLMs are changing event extraction (EE): prompting and generation can often produce structured outputs in zero shot or few shot settings…
UniVA: Universal Video Agent towards Open-Source Next-Generation Video Generalist
Zhengyang Liang, Daoan Zhang, Huichi Zhou +8
While specialized AI models excel at isolated video tasks like generation or understanding, real-world applications demand complex, iterative workflows that combine these capabilit…
Zero-Shot Conversational Stance Detection: Dataset and Approaches
Yuzhe Ding, Kang He, Bobo Li +5
Stance detection, which aims to identify public opinion towards specific targets using social media data, is an important yet challenging task. With the increasing number of online…
FormFactory: An Interactive Benchmarking Suite for Multimodal Form-Filling Agents
Bobo Li, Yuheng Wang, Hao Fei +4
Online form filling is a common yet labor-intensive task involving extensive keyboard and mouse interactions. Despite the long-standing vision of automating this process with "one…
On Path to Multimodal Generalist: General-Level and General-Bench
Hao Fei, Yuan Zhou, Juncheng Li +29
The Multimodal Large Language Model (MLLM) is currently experiencing rapid growth, driven by the advanced capabilities of LLMs. Unlike earlier specialists, existing MLLMs are evolv…
NUS-Emo at SemEval-2024 Task 3: Instruction-Tuning LLM for Multimodal Emotion-Cause Analysis in Conversations
Meng Luo, Han Zhang, Shengqiong Wu +3
This paper describes the architecture of our system developed for Task 3 of SemEval-2024: Multimodal Emotion-Cause Analysis in Conversations. Our project targets the challenges of…