18 citations · 28 across the 7 of their papers we have counts for
4 papers · 1 filter
Learning to Reason via Mixture-of-Thought for Logical Reasoning
Tong Zheng, Lichang Chen, Simeng Han +2
Human beings naturally utilize multiple reasoning modalities to learn and solve logical problems, i.e., different representational formats such as natural language, code, and symbo…
Reflection-Tuning: Data Recycling Improves LLM Instruction-Tuning
Ming Li, Lichang Chen, Jiuhai Chen +4
Recent advancements in Large Language Models (LLMs) have expanded the horizons of natural language understanding and generation. Notably, the output control and alignment with the…
Backdoor Learning on Sequence to Sequence Models
Lichang Chen, Minhao Cheng, Heng Huang
Backdoor learning has become an emerging research area towards building a trustworthy machine learning system. While a lot of works have studied the hidden danger of backdoor attac…
PTP: Boosting Stability and Performance of Prompt Tuning with Perturbation-Based Regularizer
Lichang Chen, Heng Huang, Minhao Cheng
Recent studies show that prompt tuning can better leverage the power of large language models than fine-tuning on downstream natural language understanding tasks. However, the exis…