An Autonomous Large Language Model Agent for Chemical Literature Data Mining

no code implementations • 20 Feb 2024 • Kexin Chen, Hanqun Cao, Junyou Li, Yuyang Du, Menghao Guo, Xin Zeng, Lanqing Li, Jiezhong Qiu, Pheng Ann Heng, Guangyong Chen

The proposed approach marks a significant advancement in automating chemical literature extraction and demonstrates the potential for AI to revolutionize data management and utilization in chemistry.

Drug Discovery Language Modelling +2

Affordable Generative Agents

1 code implementation • 3 Feb 2024 • Yangbin Yu, Qin Zhang, Junyou Li, Qiang Fu, Deheng Ye

The emergence of large language models (LLMs) has significantly advanced the simulation of believable interactive agents.

More Agents Is All You Need

no code implementations • 3 Feb 2024 • Junyou Li, Qin Zhang, Yangbin Yu, Qiang Fu, Deheng Ye

We find that, simply via a sampling-and-voting method, the performance of large language models (LLMs) scales with the number of agents instantiated.

Chemist-X: Large Language Model-empowered Agent for Reaction Condition Recommendation in Chemical Synthesis

no code implementations • 16 Nov 2023 • Kexin Chen, Junyou Li, Kunyi Wang, Yuyang Du, Jiahui Yu, Jiamin Lu, Lanqing Li, Jiezhong Qiu, Jianzhang Pan, Yi Huang, Qun Fang, Pheng Ann Heng, Guangyong Chen

Recent AI research plots a promising future of automatic chemical reactions within the chemistry society.

Contrastive Learning Drug Discovery +3

Pretraining in Deep Reinforcement Learning: A Survey

no code implementations • 8 Nov 2022 • Zhihui Xie, Zichuan Lin, Junyou Li, Shuai Li, Deheng Ye

The past few years have seen rapid progress in combining reinforcement learning (RL) with deep learning.

reinforcement-learning Reinforcement Learning (RL)

Revisiting Discrete Soft Actor-Critic

1 code implementation • 21 Sep 2022 • Haibin Zhou, Zichuan Lin, Junyou Li, Qiang Fu, Wei Yang, Deheng Ye

We study the adaption of soft actor-critic (SAC) from continuous action space to discrete action space.

Atari Games Q-Learning

MetaRF: Differentiable Random Forest for Reaction Yield Prediction with a Few Trails

no code implementations • 22 Aug 2022 • Kexin Chen, Guangyong Chen, Junyou Li, Yuansheng Huang, Pheng-Ann Heng

In high-throughput experimentation (HTE) datasets, the average yield of our methodology's top 10 high-yield reactions is relatively close to the results of ideal yield selection.

Dimensionality Reduction Few-Shot Learning

MineRL Diamond 2021 Competition: Overview, Results, and Lessons Learned

no code implementations • 17 Feb 2022 • Anssi Kanervisto, Stephanie Milani, Karolis Ramanauskas, Nicholay Topin, Zichuan Lin, Junyou Li, Jianing Shi, Deheng Ye, Qiang Fu, Wei Yang, Weijun Hong, Zhongyue Huang, Haicheng Chen, Guangjun Zeng, Yue Lin, Vincent Micheli, Eloi Alonso, François Fleuret, Alexander Nikulin, Yury Belousov, Oleg Svidchenko, Aleksei Shpilman

With this in mind, we hosted the third edition of the MineRL ObtainDiamond competition, MineRL Diamond 2021, with a separate track in which we permitted any solution to promote the participation of newcomers.

JueWu-MC: Playing Minecraft with Sample-efficient Hierarchical Reinforcement Learning

no code implementations • 7 Dec 2021 • Zichuan Lin, Junyou Li, Jianing Shi, Deheng Ye, Qiang Fu, Wei Yang

To address this, we propose JueWu-MC, a sample-efficient hierarchical RL approach equipped with representation learning and imitation learning to deal with perception and exploration.

Efficient Exploration Hierarchical Reinforcement Learning +4

Neural Entity Summarization with Joint Encoding and Weak Supervision

1 code implementation • 1 May 2020 • Junyou Li, Gong Cheng, Qingxia Liu, Wen Zhang, Evgeny Kharlamov, Kalpa Gunaratna, Huajun Chen

In a large-scale knowledge graph (KG), an entity is often described by a large number of triple-structured facts.