1 citations · 1 across the 3 of their papers we have counts for
5 papers
Overhearing LLM Agents: A Survey, Taxonomy, and Roadmap
Andrew Zhu, Chris Callison-Burch
Imagine AI assistants that enhance conversations without interrupting them: quietly providing relevant information during a medical consultation, seamlessly preparing materials as…
PAL: Designing Conversational Agents as Scalable, Cooperative Patient Simulators for Palliative-Care Training
Neil K. R. Sehgal, Hita Kambhamettu, Allen Chang +3
Effective communication in serious illness and palliative care is essential but often under-taught due to limited access to training resources like standardized patients. We presen…
First Steps Towards Overhearing LLM Agents: A Case Study With Dungeons & Dragons Gameplay
Andrew Zhu, Evan Osgood, Chris Callison-Burch
Much work has been done on conversational LLM agents which directly assist human users with tasks. We present an alternative paradigm for interacting with LLM agents, which we call…
GenAI Content Detection Task 3: Cross-Domain Machine-Generated Text Detection Challenge
Liam Dugan, Andrew Zhu, Firoj Alam +3
Recently there have been many shared tasks targeting the detection of generated text from Large Language Models (LLMs). However, these shared tasks tend to focus either on cases wh…
You Have Thirteen Hours in Which to Solve the Labyrinth: Enhancing AI Game Masters with Function Calling
Jaewoo Song, Andrew Zhu, Chris Callison-Burch
Developing a consistent and reliable AI game master for text-based games is a challenging task due to the limitations of large language models (LLMs) and the complexity of the game…