Summary of On the Modeling Capabilities Of Large Language Models For Sequential Decision Making, by Martin Klissarov et al.
On the Modeling Capabilities of Large Language Models for Sequential Decision Makingby Martin Klissarov, Devon…
Summary of Improving Portfolio Optimization Results with Bandit Networks, by Gustavo De Freitas Fonseca et al.
Improving Portfolio Optimization Results with Bandit Networksby Gustavo de Freitas Fonseca, Lucas Coelho e Silva,…
Summary of Mindscope: Exploring Cognitive Biases in Large Language Models Through Multi-agent Systems, by Zhentao Xie et al.
MindScope: Exploring cognitive biases in large language models through Multi-Agent Systemsby Zhentao Xie, Jiabao Zhao,…
Summary of Aligning Llms with Individual Preferences Via Interaction, by Shujin Wu et al.
Aligning LLMs with Individual Preferences via Interactionby Shujin Wu, May Fung, Cheng Qian, Jeonghwan Kim,…
Summary of Guided Stream Of Search: Learning to Better Search with Language Models Via Optimal Path Guidance, by Seungyong Moon et al.
Guided Stream of Search: Learning to Better Search with Language Models via Optimal Path Guidanceby…
Summary of Logic-free Building Automation: Learning the Control Of Room Facilities with Wall Switches and Ceiling Camera, by Hideya Ochiai et al.
Logic-Free Building Automation: Learning the Control of Room Facilities with Wall Switches and Ceiling Cameraby…
Summary of Choices Are More Important Than Efforts: Llm Enables Efficient Multi-agent Exploration, by Yun Qu et al.
Choices are More Important than Efforts: LLM Enables Efficient Multi-Agent Explorationby Yun Qu, Boyuan Wang,…
Summary of Grounded Answers For Multi-agent Decision-making Problem Through Generative World Model, by Zeyang Liu et al.
Grounded Answers for Multi-agent Decision-making Problem through Generative World Modelby Zeyang Liu, Xinrui Yang, Shiguang…
Summary of Rlef: Grounding Code Llms in Execution Feedback with Reinforcement Learning, by Jonas Gehring et al.
RLEF: Grounding Code LLMs in Execution Feedback with Reinforcement Learningby Jonas Gehring, Kunhao Zheng, Jade…
Summary of Finding Path and Cycle Counting Formulae in Graphs with Deep Reinforcement Learning, by Jason Piquenot et al.
Finding path and cycle counting formulae in graphs with Deep Reinforcement Learningby Jason Piquenot, Maxime…