news

Jun 22, 2024 One paper was put on the arXiv: RuleR: Improving LLM Controllability by Rule-based Data Recycling, where we proposed an augmentation method that incorporates multiple rule-based constraints into the original instruction data. Repo: RuleR.
May 23, 2024 One paper was put on the arXiv: Mosaic IT: Enhancing Instruction Tuning with Data Mosaics, where we proposed an augmentation method for instruction tuning, which concurrently improves the LLM performances and lowers the training expenses. Repo: Mosaic-IT.
May 16, 2024 Three papers were accepted by ACL 2024!
1 Superfiltering: Weak-to-Strong Data Filtering for Fast Instruction-Tuning;
2 Selective Reflection-Tuning: Student-Selected Data Recycling for LLM Instruction-Tuning;
3 Can LLMs Speak For Diverse People? Tuning LLMs via Debate to Generate Controllable Controversial Statements (DEBATunE).
Mar 13, 2024 One paper was accepted by NAACL 2024!
From Quantity to Quality: Boosting LLM Performance with Self-Guided Data Selection for Instruction Tuning (Cherry LLM (IFD))
Feb 21, 2024 I will join Adobe (based in San Jose) as a Research Scientist/Engineer Intern this Summer~
Feb 20, 2024 One Survey was put on the arXiv: A Survey on Knowledge Distillation of Large Language Models. Repo: Awesome-Knowledge-Distillation-of-LLMs.
Oct 28, 2023 One paper was accepted by Instruction Workshop @ NeurIPS 2023!
Reflection-Tuning: Data Recycling Improves LLM Instruction-Tuning.
Oct 07, 2023 One paper was accepted by EMNLP 2023!
PRCA: Fitting Black-Box Large Language Models for Retrieval Question Answering via Pluggable Reward-Driven Contextual Adapter.
Sep 01, 2023 I arrived at the University of Maryland, officially beginning my journey for a Ph.D. ✌️
Jun 01, 2023 I obtained my Master’s in Computer Science at Texas A&M University.