1 code implementation • 2 Jun 2024 • Xianghe Ma, Dominik Schlechtweg, Wei Zhao
It leverages a graph-based clustering approach to predict mappings between unknown word usages and dictionary entries for Subtask 1, and generates dictionary-like definitions for those novel word usages through the state-of-the-art Large Language Models such as GPT-4 and LLaMA-3 for Subtask 2.
1 code implementation • 1 Feb 2024 • Xianghe Ma, Michael Strube, Wei Zhao
To address this issue, we propose a graph-based clustering approach to capture nuanced changes in both high- and low-frequency word senses across time and languages, including the acquisition and loss of these senses over time.
no code implementations • 25 Oct 2023 • Yingjie Zhou, ZiCheng Zhang, Wei Sun, Xiongkuo Min, Xianghe Ma, Guangtao Zhai
In this paper, we develop a novel no-reference (NR) method based on Transformer to deal with DHQA in a multi-task manner.