16 citations · 19 across the 6 of their papers we have counts for
6 papers
Enabling Rapid Shared Human-AI Mental Model Alignment via the After-Action Review
Edward Gu, Ho Chit Siu, Melanie Platt +3
In this work, we present two novel contributions toward improving research in human-machine teaming (HMT): 1) a Minecraft testbed to accelerate testing and deployment of collaborat…
In Pursuit of Predictive Models of Human Preferences Toward AI Teammates
Ho Chit Siu, Jaime D. Peña, Yutai Zhou +1
We seek measurable properties of AI agents that make them better or worse teammates from the subjective perspective of human collaborators. Our experiments use the cooperative card…
Syndeo: Portable Ray Clusters with Secure Containerization
William Li, Rodney S. Lafuente Mercado, Jaime D. Pena +1
We present Syndeo: a software framework for container orchestration of Ray on Slurm. In general the idea behind Syndeo is to write code once and deploy anywhere. Specifically, Synd…
STL: Still Tricky Logic (for System Validation, Even When Showing Your Work)
Isabelle Hurley, Rohan Paleja, Ashley Suh +2
As learned control policies become increasingly common in autonomous systems, there is increasing need to ensure that they are interpretable and can be checked by human stakeholder…
Why Would You Suggest That? Human Trust in Language Model Responses
Manasi Sharma, Ho Chit Siu, Rohan Paleja +1
The emergence of Large Language Models (LLMs) has revealed a growing need for human-AI collaboration, especially in creative decision-making scenarios where trust and reliance are…
Evaluation of Human-AI Teams for Learned and Rule-Based Agents in Hanabi
Ho Chit Siu, Jaime D. Pena, Edenna Chen +5
Deep reinforcement learning has generated superhuman AI in competitive games such as Go and StarCraft. Can similar learning techniques create a superior AI teammate for human-machi…