An Empirical Study on Prompt Compression for Large Language Models.
CoRR, May, 2025
DVM: Towards Controllable LLM Agents in Social Deduction Games.
CoRR, January, 2025
PCToolkit: A Unified Plug-and-Play Prompt Compression Toolkit of Large Language Models.
CoRR, 2024
All in a Single Image: Large Multimodal Models are In-Image Learners.
CoRR, 2024
LLM-Based Agent Society Investigation: Collaboration and Confrontation in Avalon Gameplay.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024
LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models.
CoRR, 2023
LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023
Plan-and-Solve Prompting: Improving Zero-Shot Chain-of-Thought Reasoning by Large Language Models.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023
MWPToolkit: An Open-Source Framework for Deep Learning-Based Math Word Problem Solvers.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022