36 citations · 42 across the 17 of their papers we have counts for
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cs.LG2024
Supervised Fine-Tuning Achieve Rapid Task Adaption Via Alternating Attention Head Activation Patterns
Yang Zhao, Li Du, Xiao Ding +3
LLMs' performance on complex tasks is still unsatisfactory. A key issue is that presently LLMs learn in a data-driven schema, while the instructions about these complex tasks are b…
cs.CL2024
Meaningful Learning: Enhancing Abstract Reasoning in Large Language Models via Generic Fact Guidance
Kai Xiong, Xiao Ding, Ting Liu +5
Large language models (LLMs) have developed impressive performance and strong explainability across various reasoning scenarios, marking a significant stride towards mimicking huma…
cs.CL2024
Deciphering the Impact of Pretraining Data on Large Language Models through Machine Unlearning
Yang Zhao, Li Du, Xiao Ding +5
Through pretraining on a corpus with various sources, Large Language Models (LLMs) have gained impressive performance. However, the impact of each component of the pretraining corp…