2 code implementations • 10 Apr 2024 • Linan Yue, Qi Liu, Lili Zhao, Li Wang, Weibo Gao, Yanqing An
Then, we incorporate the extracted events into court view generation by merging case facts and events.
1 code implementation • 12 Mar 2024 • Linan Yue, Qi Liu, Yichao Du, Li Wang, Weibo Gao, Yanqing An
Since existing methods still suffer from adopting the shortcuts in data to compose rationales and limited large-scale annotated rationales by human, in this paper, we propose a Shortcuts-fused Selective Rationalization (SSR) method, which boosts the rationalization by discovering and exploiting potential shortcuts.
1 code implementation • 10 Mar 2024 • Linan Yue, Qi Liu, Ye Liu, Weibo Gao, Fangzhou Yao, Wenfeng Li
To address these challenges, in this paper, we propose a Cooperative Classification and Rationalization (C2R) method, consisting of the classification and the rationalization module.
no code implementations • 18 Jan 2024 • Yichao Du, Zhirui Zhang, Linan Yue, Xu Huang, Yuqing Zhang, Tong Xu, Linli Xu, Enhong Chen
To protect privacy and meet legal regulations, federated learning (FL) has gained significant attention for training speech-to-text (S2T) systems, including automatic speech recognition (ASR) and speech translation (ST).
Automatic Speech Recognition Automatic Speech Recognition (ASR) +2
2 code implementations • 20 Dec 2023 • Weibo Gao, Qi Liu, Hao Wang, Linan Yue, Haoyang Bi, Yin Gu, Fangzhou Yao, Zheng Zhang, Xin Li, Yuanjing He
Consequently, we refine the cognitive states of cold-start students as diagnostic outcomes via virtual data, aligning with the diagnosis-oriented goal.
1 code implementation • 15 Sep 2023 • Linan Yue, Qi Liu, Yichao Du, Weibo Gao, Ye Liu, Fangzhou Yao
To this end, in this paper, we propose the first Federated Legal Large Language Model (FedJudge) framework, which fine-tunes Legal LLMs efficiently and effectively.