Kai Xiong

According to our database, Kai Xiong authored at least 17 papers between 2021 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Supervised Fine-Tuning: An Activation Pattern Optimization Process for Attention Heads.

Yang Zhao, Li Du, Xiao Ding, Kai Xiong, Ting Liu, Bing Qin

CoRR, 2024

Diagnosing and Remedying Knowledge Deficiencies in LLMs via Label-free Curricular Meaningful Learning.

Kai Xiong, Xiao Ding, Li Du, Jiahao Ying, Ting Liu, Bing Qin, Yixin Cao

CoRR, 2024

Meaningful Learning: Advancing Abstract Reasoning in Large Language Models via Generic Fact Guidance.

Kai Xiong, Xiao Ding, Ting Liu, Bing Qin, Dongliang Xu, Qing Yang, Hongtao Liu, Yixin Cao

CoRR, 2024

Deciphering the lmpact of Pretraining Data on Large Language Models through Machine Unlearning.

Yang Zhao, Li Du, Xiao Ding, Kai Xiong, Zhouhao Sun, Jun Shi, Ting Liu, Bing Qin

CoRR, 2024

Deciphering the Impact of Pretraining Data on Large Language Models through Machine Unlearning.

Yang Zhao, Li Du, Xiao Ding, Kai Xiong, Zhouhao Sun, Shi Jun, Ting Liu, Bing Qi

Proceedings of the Findings of the Association for Computational Linguistics, 2024

Intuitive or Dependent? Investigating LLMs' Behavior Style to Conflicting Prompts.

Jiahao Ying, Yixin Cao, Kai Xiong, Long Cui, Yidong He, Yongbin Liu

Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

2023

Intuitive or Dependent? Investigating LLMs' Robustness to Conflicting Prompts.

Jiahao Ying, Yixin Cao, Kai Xiong, Yidong He, Long Cui, Yongbin Liu

CoRR, 2023

Examining the Inter-Consistency of Large Language Models: An In-depth Analysis via Debate.

Kai Xiong, Xiao Ding, Yixin Cao, Ting Liu, Bing Qin

CoRR, 2023

Improving Cross-Task Generalization with Step-by-Step Instructions.

Yang Wu, Yanyan Zhao, Zhongyang Li, Bing Qin, Kai Xiong

CoRR, 2023

Examining Inter-Consistency of Large Language Models Collaboration: An In-depth Analysis via Debate.

Kai Xiong, Xiao Ding, Yixin Cao, Ting Liu, Bing Qin

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

2022

Enhancing pretrained language models with structured commonsense knowledge for textual inference.

Li Du, Xiao Ding, Kai Xiong, Ting Liu, Bing Qin

Knowl. Based Syst., 2022

ReCo: Reliable Causal Chain Reasoning via Structural Causal Recurrent Neural Networks.

Kai Xiong, Xiao Ding, Zhongyang Li, Li Du, Bing Qin, Yi Zheng, Baoxing Huai

CoRR, 2022

A Graph Enhanced BERT Model for Event Prediction.

Li Du, Xiao Ding, Yue Zhang, Kai Xiong, Ting Liu, Bing Qin

CoRR, 2022

ReCo: Reliable Causal Chain Reasoning via Structural Causal Recurrent Neural Networks.

Kai Xiong, Xiao Ding, Zhongyang Li, Li Du, Ting Liu, Bing Qin, Yi Zheng, Baoxing Huai

Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

e-CARE: a New Dataset for Exploring Explainable Causal Reasoning.

Li Du, Xiao Ding, Kai Xiong, Ting Liu, Bing Qin

Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

2021

Heterogeneous graph knowledge enhanced stock market prediction.

Kai Xiong, Xiao Ding, Li Du, Ting Liu, Bing Qin

AI Open, 2021

ExCAR: Event Graph Knowledge Enhanced Explainable Causal Reasoning.

Li Du, Xiao Ding, Kai Xiong, Ting Liu, Bing Qin

Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021