Search Results for author: Keyan Zhou

Found 3 papers, 3 papers with code

L-CiteEval: Do Long-Context Models Truly Leverage Context for Responding?

2 code implementations3 Oct 2024 Zecheng Tang, Keyan Zhou, Juntao Li, Baibei Ji, Jianye Hou, Min Zhang

Long-context models (LCMs) have made remarkable strides in recent years, offering users great convenience for handling tasks that involve long context, such as document summarization.

8k Document Summarization +2

CMD: a framework for Context-aware Model self-Detoxification

3 code implementations16 Aug 2023 Zecheng Tang, Keyan Zhou, Juntao Li, Yuyang Ding, Pinzheng Wang, Bowen Yan, Rejie Hua, Min Zhang

In view of this, we introduce a Context-aware Model self-Detoxification~(CMD) framework that pays attention to both the context and the detoxification process, i. e., first detoxifying the context and then making the language model generate along the safe context.

Language Modeling Language Modelling

Can Diffusion Model Achieve Better Performance in Text Generation? Bridging the Gap between Training and Inference!

1 code implementation8 May 2023 Zecheng Tang, Pinzheng Wang, Keyan Zhou, Juntao Li, Ziqiang Cao, Min Zhang

Diffusion models have been successfully adapted to text generation tasks by mapping the discrete text into the continuous space.

Text Generation

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