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20212025
most citedCOOPERNAUT: End-to-End Driving with Cooperative Perception for Networked Vehicles

128 citations · 133 across the 7 of their papers we have counts for

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Showing 2025Show all

6 papers · 1 filter

cs.AI2025

Evaluating Generalization Capabilities of LLM-Based Agents in Mixed-Motive Scenarios Using Concordia

Chandler Smith, Marwa Abdulhai, Manfred Diaz +83

Large Language Model (LLM) agents have demonstrated impressive capabilities for social interaction and are increasingly being deployed in situations where they might engage with bo…

cs.RO2025

Learning Agile Striker Skills for Humanoid Soccer Robots from Noisy Sensory Input

Zifan Xu, Myoungkyu Seo, Dongmyeong Lee +8

Learning fast and robust ball-kicking skills is a critical capability for humanoid soccer robots, yet it remains a challenging problem due to the need for rapid leg swings, postura…

cs.RO2025

SocialNav-SUB: Benchmarking VLMs for Scene Understanding in Social Robot Navigation

Michael J. Munje, Chen Tang, Shuijing Liu +6

Robot navigation in dynamic, human-centered environments requires socially-compliant decisions grounded in robust scene understanding. Recent Vision-Language Models (VLMs) exhibit…

cs.AI2025

VGC-Bench: Towards Mastering Diverse Team Strategies in Competitive Pokémon

Cameron Angliss, Jiaxun Cui, Jiaheng Hu +2

Developing AI agents that can robustly adapt to varying strategic landscapes without retraining is a central challenge in multi-agent learning. Pokémon Video Game Championships (VG…

cs.AI2025

ROTATE: Regret-driven Open-ended Training for Ad Hoc Teamwork

Caroline Wang, Arrasy Rahman, Benjamin Nativi +4

Learning to collaborate with previously unseen partners is a fundamental generalization challenge, known as Ad Hoc Teamwork (AHT). Existing methods often adopt a two-stage pipeline…

cs.RO2025★ 1 cited

CoopReflect: Towards Natural Language Communication for Cooperative Autonomous Driving via Multi-Agent Learning

Jiaxun Cui, Chen Tang, Jarrett Holtz +4

Past work has demonstrated that autonomous vehicles can drive more safely if they communicate with each other. However, this communication is usually not human-understandable. Usin…