3 citations · 4 across the 11 of their papers we have counts for
12 papers
CWE-bench: Refocusing Agentic Security from Exploitation to Defense
Gonzalo Gonzalez-Pumariega, Ajay Jagannath, Adit Jain +3
Cybersecurity evaluations of AI agents have focused largely on offense, yet a working exploit does not show that an agent can make software safe. An attacker needs to exploit only…
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…
Query-Efficient Planning with Language Models
Gonzalo Gonzalez-Pumariega, Wayne Chen, Kushal Kedia +1
Planning in complex environments requires an agent to efficiently query a world model to find a feasible sequence of actions from start to goal. Recent work has shown that Large La…
APRICOT: Active Preference Learning and Constraint-Aware Task Planning with LLMs
Huaxiaoyue Wang, Nathaniel Chin, Gonzalo Gonzalez-Pumariega +5
Home robots performing personalized tasks must adeptly balance user preferences with environmental affordances. We focus on organization tasks within constrained spaces, such as ar…
MOSAIC: Modular Foundation Models for Assistive and Interactive Cooking
Huaxiaoyue Wang, Kushal Kedia, Juntao Ren +14
We present MOSAIC, a modular architecture for coordinating multiple robots to (a) interact with users using natural language and (b) manipulate an open vocabulary of everyday objec…
Demo2Code: From Summarizing Demonstrations to Synthesizing Code via Extended Chain-of-Thought
Huaxiaoyue Wang, Gonzalo Gonzalez-Pumariega, Yash Sharma +1
Language instructions and demonstrations are two natural ways for users to teach robots personalized tasks. Recent progress in Large Language Models (LLMs) has shown impressive per…
CuttleSys: Data-Driven Resource Management forInteractive Applications on Reconfigurable Multicores
Neeraj Kulkarni, Gonzalo Gonzalez-Pumariega, Amulya Khurana +3
Multi-tenancy for latency-critical applications leads to re-source interference and unpredictable performance. Core reconfiguration opens up more opportunities for colocation,as it…