On the Effectiveness of Distillation in Mitigating Backdoors in Pre-trained Encoder

1 code implementation • 6 Mar 2024 • Tingxu Han, Shenghan Huang, Ziqi Ding, Weisong Sun, Yebo Feng, Chunrong Fang, Jun Li, Hanwei Qian, Cong Wu, Quanjun Zhang, Yang Liu, Zhenyu Chen

Distillation aims to distill knowledge from a given model (a. k. a the teacher net) and transfer it to another (a. k. a the student net).

Image Classification

From Nuisance to News Sense: Augmenting the News with Cross-Document Evidence and Context

1 code implementation • 6 Oct 2023 • Jeremiah Milbauer, Ziqi Ding, Zhijin Wu, Tongshuang Wu

Reading and understanding the stories in the news is increasingly difficult.

Fact Verification Misinformation

LLMs as Workers in Human-Computational Algorithms? Replicating Crowdsourcing Pipelines with LLMs

no code implementations • 19 Jul 2023 • Tongshuang Wu, Haiyi Zhu, Maya Albayrak, Alexis Axon, Amanda Bertsch, Wenxing Deng, Ziqi Ding, Bill Guo, Sireesh Gururaja, Tzu-Sheng Kuo, Jenny T. Liang, Ryan Liu, Ihita Mandal, Jeremiah Milbauer, Xiaolin Ni, Namrata Padmanabhan, Subhashini Ramkumar, Alexis Sudjianto, Jordan Taylor, Ying-Jui Tseng, Patricia Vaidos, Zhijin Wu, Wei Wu, Chenyang Yang

We reflect on human and LLMs' different sensitivities to instructions, stress the importance of enabling human-facing safeguards for LLMs, and discuss the potential of training humans and LLMs with complementary skill sets.

Automatic tagging of knowledge points for K12 math problems

no code implementations • 21 Aug 2022 • Xiaolu Wang, Ziqi Ding, Liangyu Chen

In this paper, K12 math problems taken as the research object, the LABS model based on label-semantic attention and multi-label smoothing combining textual features is proposed to improve the automatic tagging of knowledge points for math problems.

Math text-classification +1