Summary of Comal: Collaborative Multi-agent Large Language Models For Mixed-autonomy Traffic, by Huaiyuan Yao et al.
CoMAL: Collaborative Multi-Agent Large Language Models for Mixed-Autonomy Trafficby Huaiyuan Yao, Longchao Da, Vishnu Nandam,…
CoMAL: Collaborative Multi-Agent Large Language Models for Mixed-Autonomy Trafficby Huaiyuan Yao, Longchao Da, Vishnu Nandam,…
Utilizing Large Language Models for Event Deconstruction to Enhance Multimodal Aspect-Based Sentiment Analysisby Xiaoyong Huang,…
Interpretable end-to-end Neurosymbolic Reinforcement Learning agentsby Nils Grandien, Quentin Delfosse, Kristian KerstingFirst submitted to arxiv…
Transformer Guided Coevolution: Improved Team Selection in Multiagent Adversarial Team Gamesby Pranav Rajbhandari, Prithviraj Dasgupta,…
PRefLexOR: Preference-based Recursive Language Modeling for Exploratory Optimization of Reasoning and Agentic Thinkingby Markus J.…
Revisiting Benchmark and Assessment: An Agent-based Exploratory Dynamic Evaluation Framework for LLMsby Wanying Wang, Zeyu…
Innovative Thinking, Infinite Humor: Humor Research of Large Language Models through Structured Thought Leapsby Han…
OpenR: An Open Source Framework for Advanced Reasoning with Large Language Modelsby Jun Wang, Meng…
Generalization of Compositional Tasks with Logical Specification via Implicit Planningby Duo Xu, Faramarz FekriFirst submitted…
Public Transport Network Design for Equality of Accessibility via Message Passing Neural Networks and Reinforcement…