3 citations · 4 across the 11 of their papers we have counts for
11 papers
GameEngineBench: Evaluating Coding Agents on Real C++ Runtime Environments
Brian La, Sejoon Chang, Ben Kim +5
Game engines provide real-time simulation, rendering, physics, interaction, networking, and asset pipelines, making them valuable not only for games but also for 3D applications in…
On the Reliability of Computer Use Agents
Gonzalo Gonzalez-Pumariega, Saaket Agashe, Jiachen Yang +2
Computer-use agents have rapidly improved on real-world tasks such as web navigation, desktop automation, and software interaction, in some cases surpassing human performance. Yet…
Scaling Agents for Computer Use
Gonzalo Gonzalez-Pumariega, Vincent Tu, Chih-Lun Lee +3
Computer-use agents (CUAs) hold promise for automating everyday digital tasks, but their performance on long-horizon, complex problems remains unreliable. Single-rollout execution…
Skill-Aligned Fairness in Multi-Agent Learning for Collaboration in Healthcare
Promise Osaine Ekpo, Brian La, Thomas Wiener +5
Fairness in multi-agent reinforcement learning (MARL) is often framed as a workload balance problem, overlooking agent expertise and the structured coordination required in real-wo…
Robotouille: An Asynchronous Planning Benchmark for LLM Agents
Gonzalo Gonzalez-Pumariega, Leong Su Yean, Neha Sunkara +1
Effective asynchronous planning, or the ability to efficiently reason and plan over states and actions that must happen in parallel or sequentially, is essential for agents that mu…
Multi-Turn Code Generation Through Single-Step Rewards
Arnav Kumar Jain, Gonzalo Gonzalez-Pumariega, Wayne Chen +3
We address the problem of code generation from multi-turn execution feedback. Existing methods either generate code without feedback or use complex, hierarchical reinforcement lear…