DenoSent: A Denoising Objective for Self-Supervised Sentence Representation Learning

1 code implementation • 24 Jan 2024 • Xinghao Wang, Junliang He, Pengyu Wang, Yunhua Zhou, Tianxiang Sun, Xipeng Qiu

These methods regularize the representation space by pulling similar sentence representations closer and pushing away the dissimilar ones and have been proven effective in various NLP tasks, e. g., semantic textual similarity (STS) tasks.

Contrastive Learning Denoising +4

Evaluating Hallucinations in Chinese Large Language Models

2 code implementations • 5 Oct 2023 • Qinyuan Cheng, Tianxiang Sun, Wenwei Zhang, Siyin Wang, Xiangyang Liu, Mozhi Zhang, Junliang He, Mianqiu Huang, Zhangyue Yin, Kai Chen, Xipeng Qiu

We analyze the primary types of hallucinations in different types of models and their causes.

Hallucination Question Answering

BERTScore is Unfair: On Social Bias in Language Model-Based Metrics for Text Generation

1 code implementation • 14 Oct 2022 • Tianxiang Sun, Junliang He, Xipeng Qiu, Xuanjing Huang

Automatic evaluation metrics are crucial to the development of generative systems.

Fairness Language Modelling +1

Towards Efficient NLP: A Standard Evaluation and A Strong Baseline

1 code implementation • NAACL 2022 • Xiangyang Liu, Tianxiang Sun, Junliang He, Jiawen Wu, Lingling Wu, Xinyu Zhang, Hao Jiang, Zhao Cao, Xuanjing Huang, Xipeng Qiu

ELUE is dedicated to depict the Pareto Frontier for various language understanding tasks, such that it can tell whether and how much a method achieves Pareto improvement.