5 citations · 5 across the 5 of their papers we have counts for
6 papers
Towards Event Extraction with Massive Types: LLM-based Collaborative Annotation and Partitioning Extraction
Wenxuan Liu, Zixuan Li, Long Bai +5
Developing a general-purpose extraction system that can extract events with massive types is a long-standing target in Event Extraction (EE). In doing so, the challenge comes from…
Code-Vision: Evaluating Multimodal LLMs Logic Understanding and Code Generation Capabilities
Hanbin Wang, Xiaoxuan Zhou, Zhipeng Xu +7
This paper introduces Code-Vision, a benchmark designed to evaluate the logical understanding and code generation capabilities of Multimodal Large Language Models (MLLMs). It chall…
KnowCoder-X: Boosting Multilingual Information Extraction via Code
Yuxin Zuo, Wenxuan Jiang, Wenxuan Liu +7
Empirical evidence indicates that LLMs exhibit spontaneous cross-lingual alignment. However, although LLMs show promising cross-lingual alignment in Information Extraction (IE), a…
KnowCoder: Coding Structured Knowledge into LLMs for Universal Information Extraction
Zixuan Li, Yutao Zeng, Yuxin Zuo +14
In this paper, we propose KnowCoder, a Large Language Model (LLM) to conduct Universal Information Extraction (UIE) via code generation. KnowCoder aims to develop a kind of unified…
DSCom: A Data-Driven Self-Adaptive Community-Based Framework for Influence Maximization in Social Networks
Yuxin Zuo, Haojia Sun, Yongyi Hu +2
Influence maximization aims to find a subset of seeds that maximize the influence spread under a given budget. In this paper, we mainly address the data-driven version of this prob…
Incorporating Probing Signals into Multimodal Machine Translation via Visual Question-Answering Pairs
Yuxin Zuo, Bei Li, Chuanhao Lv +3
This paper presents an in-depth study of multimodal machine translation (MMT), examining the prevailing understanding that MMT systems exhibit decreased sensitivity to visual infor…