21 citations · 43 across the 5 of their papers we have counts for
5 papers
MoE-CT: A Novel Approach For Large Language Models Training With Resistance To Catastrophic Forgetting
Tianhao Li, Shangjie Li, Binbin Xie +2
The advent of large language models (LLMs) has predominantly catered to high-resource languages, leaving a disparity in performance for low-resource languages. Conventional Continu…
PolyLM: An Open Source Polyglot Large Language Model
Xiangpeng Wei, Haoran Wei, Huan Lin +15
Large language models (LLMs) demonstrate remarkable ability to comprehend, reason, and generate following nature language instructions. However, the development of LLMs has been pr…
From Statistical Methods to Deep Learning, Automatic Keyphrase Prediction: A Survey
Binbin Xie, Jia Song, Liangying Shao +6
Keyphrase prediction aims to generate phrases (keyphrases) that highly summarizes a given document. Recently, researchers have conducted in-depth studies on this task from various…
WR-ONE2SET: Towards Well-Calibrated Keyphrase Generation
Binbin Xie, Xiangpeng Wei, Baosong Yang +5
Keyphrase generation aims to automatically generate short phrases summarizing an input document. The recently emerged ONE2SET paradigm (Ye et al., 2021) generates keyphrases as a s…
Improving Tree-Structured Decoder Training for Code Generation via Mutual Learning
Binbin Xie, Jinsong Su, Yubin Ge +4
Code generation aims to automatically generate a piece of code given an input natural language utterance. Currently, among dominant models, it is treated as a sequence-to-tree task…