7 citations · 11 across the 12 of their papers we have counts for
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cs.AI2023★ 7 cited
TPTU-v2: Boosting Task Planning and Tool Usage of Large Language Model-based Agents in Real-world Systems
Yilun Kong, Jingqing Ruan, Yihong Chen +9
Large Language Models (LLMs) have demonstrated proficiency in addressing tasks that necessitate a combination of task planning and the usage of external tools that require a blend…
cs.CL2023
To be or not to be? an exploration of continuously controllable prompt engineering
Yuhan Sun, Mukai Li, Yixin Cao +4
As the use of large language models becomes more widespread, techniques like parameter-efficient fine-tuning and other methods for controlled generation are gaining traction for cu…
cs.CV2023
Aligning Data Selection with Performance: Performance-driven Reinforcement Learning for Active Learning in Object Detection
Zhixuan Liang, Xingyu Zeng, Rui Zhao +1
Active learning strategies aim to train high-performance models with minimal labeled data by selecting the most informative instances for labeling. However, existing methods for as…