1 citations · 1 across the 4 of their papers we have counts for
4 papers
Pipelined Decoder for Efficient Context-Aware Text Generation
Zixian Huang, Chenxu Niu, Yu Gu +3
As the basis of generative AI, an autoregressive model requires the generation of a new token depending on all the previously generated tokens, which brings high quality but also r…
MindMerger: Efficient Boosting LLM Reasoning in non-English Languages
Zixian Huang, Wenhao Zhu, Gong Cheng +2
Reasoning capabilities are crucial for Large Language Models (LLMs), yet a notable gap exists between English and non-English languages. To bridge this disparity, some works fine-t…
Enhancing In-Context Learning with Answer Feedback for Multi-Span Question Answering
Zixian Huang, Jiaying Zhou, Gengyang Xiao +1
Whereas the recent emergence of large language models (LLMs) like ChatGPT has exhibited impressive general performance, it still has a large gap with fully-supervised models on spe…
Clues Before Answers: Generation-Enhanced Multiple-Choice QA
Zixian Huang, Ao Wu, Jiaying Zhou +3
A trending paradigm for multiple-choice question answering (MCQA) is using a text-to-text framework. By unifying data in different tasks into a single text-to-text format, it train…