activity
20232025
most citedDocTER: Evaluating Document-based Knowledge Editing

4 citations · 5 across the 5 of their papers we have counts for

collaborators

5 papers

cs.IR2025

Tool Graph Retriever: Exploring Dependency Graph-based Tool Retrieval for Large Language Models

Linfeng Gao, Yaoxiang Wang, Minlong Peng +4

With the remarkable advancement of AI agents, the number of their equipped tools is increasing rapidly. However, integrating all tool information into the limited model context bec…

cs.CL2024

One2set + Large Language Model: Best Partners for Keyphrase Generation

Liangying Shao, Liang Zhang, Minlong Peng +4

Keyphrase generation (KPG) aims to automatically generate a collection of phrases representing the core concepts of a given document. The dominant paradigms in KPG include one2seq…

cs.CL2023★ 4 cited

DocTER: Evaluating Document-based Knowledge Editing

Suhang Wu, Ante Wang, Minlong Peng +4

Knowledge editing aims to correct outdated or inaccurate knowledge in neural networks. In this paper, we explore knowledge editing using easily accessible documents instead of manu…

cs.CL2023

Actively Supervised Clustering for Open Relation Extraction

Jun Zhao, Yongxin Zhang, Qi Zhang +4

Current clustering-based Open Relation Extraction (OpenRE) methods usually adopt a two-stage pipeline. The first stage simultaneously learns relation representations and assignment…

cs.CL2023★ 1 cited

RE-Matching: A Fine-Grained Semantic Matching Method for Zero-Shot Relation Extraction

Jun Zhao, Wenyu Zhan, Xin Zhao +6

Semantic matching is a mainstream paradigm of zero-shot relation extraction, which matches a given input with a corresponding label description. The entities in the input should ex…