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cs.CL2026
Ultra-Low-Dimensional Prompt Tuning via Random Projection
Zijun Wu, Yongchang Hao, Lili Mou
Large language models achieve state-of-the-art performance but are increasingly costly to fine-tune. Prompt tuning is a parameter-efficient fine-tuning method that addresses parame…
cs.CL2026
TokMem: One-Token Procedural Memory for Large Language Models
Zijun Wu, Yongchang Hao, Lili Mou
Large language models are typically controlled via prompts, which must be repeatedly re-processed for every new query and are difficult to reuse modularly. We introduce TokMem, a p…
cs.CL2024
LLMR: Knowledge Distillation with a Large Language Model-Induced Reward
Dongheng Li, Yongchang Hao, Lili Mou
Large language models have become increasingly popular and demonstrated remarkable performance in various natural language processing (NLP) tasks. However, these models are typical…