Search Results for author: Yilin Niu

Found 9 papers, 7 papers with code

ChatGLM-RLHF: Practices of Aligning Large Language Models with Human Feedback

no code implementations1 Apr 2024 Zhenyu Hou, Yilin Niu, Zhengxiao Du, Xiaohan Zhang, Xiao Liu, Aohan Zeng, Qinkai Zheng, Minlie Huang, Hongning Wang, Jie Tang, Yuxiao Dong

The work presents our practices of aligning LLMs with human preferences, offering insights into the challenges and solutions in RLHF implementations.

Towards Efficient Exact Optimization of Language Model Alignment

2 code implementations1 Feb 2024 Haozhe Ji, Cheng Lu, Yilin Niu, Pei Ke, Hongning Wang, Jun Zhu, Jie Tang, Minlie Huang

This leads to the same mode-seeking solution, while enables efficient optimization by circumventing the complexities of RL.

Language Modelling Reinforcement Learning (RL)

A Self-Training Method for Machine Reading Comprehension with Soft Evidence Extraction

1 code implementation ACL 2020 Yilin Niu, Fangkai Jiao, Mantong Zhou, Ting Yao, Jingfang Xu, Minlie Huang

Neural models have achieved great success on machine reading comprehension (MRC), many of which typically consist of two components: an evidence extractor and an answer predictor.

Machine Reading Comprehension Multi-Choice MRC +1

CoTK: An Open-Source Toolkit for Fast Development and Fair Evaluation of Text Generation

1 code implementation3 Feb 2020 Fei Huang, Dazhen Wan, Zhihong Shao, Pei Ke, Jian Guan, Yilin Niu, Xiaoyan Zhu, Minlie Huang

In text generation evaluation, many practical issues, such as inconsistent experimental settings and metric implementations, are often ignored but lead to unfair evaluation and untenable conclusions.

Text Generation

Word Embedding based Edit Distance

no code implementations25 Oct 2018 Yilin Niu, chao qiao, Hang Li, Minlie Huang

Text similarity calculation is a fundamental problem in natural language processing and related fields.

text similarity

Improved Word Representation Learning with Sememes

1 code implementation ACL 2017 Yilin Niu, Ruobing Xie, Zhiyuan Liu, Maosong Sun

The key idea is to utilize word sememes to capture exact meanings of a word within specific contexts accurately.

Common Sense Reasoning Language Modelling +6

Cannot find the paper you are looking for? You can Submit a new open access paper.