2 citations · 3 across the 3 of their papers we have counts for
3 papers
cs.CL2025
Learning to Rewrite Prompts for Bootstrapping LLMs on Downstream Tasks
Qinhao Zhou, Xiang Xiang, Kun He +1
In recent years, the growing interest in Large Language Models (LLMs) has significantly advanced prompt engineering, transitioning from manual design to model-based optimization. P…
cs.CL2024★ 1 cited
Enhancing the General Agent Capabilities of Low-Parameter LLMs through Tuning and Multi-Branch Reasoning
Qinhao Zhou, Zihan Zhang, Xiang Xiang +3
Open-source pre-trained Large Language Models (LLMs) exhibit strong language understanding and generation capabilities, making them highly successful in a variety of tasks. However…
cs.CV2024★ 2 cited
Continual Adapter Tuning with Semantic Shift Compensation for Class-Incremental Learning
Qinhao Zhou, Yuwen Tan, Boqing Gong +1
Class-incremental learning (CIL) aims to enable models to continuously learn new classes while overcoming catastrophic forgetting. The introduction of pre-trained models has brough…