3 citations · 3 across the 3 of their papers we have counts for
4 papers
"I Didn't Make the Micro Decisions": Measuring, Inducing, and Exposing Goal-Level AI Contributions in Collaboration
Eunsu Kim, Jessica R. Mindel, Kyungjin Kim +1
As large language models (LLMs) increasingly shape how users form, refine, and extend their goals, attributing contributions in human-AI collaboration becomes critical for users ca…
Reinforcing Human Behavior Simulation via Verbal Feedback
Weiwei Sun, Xuhui Zhou, Jiarui Liu +13
Humans learn social norms and behaviors from verbal feedback (e.g., a parent saying "that was rude" or a friend explaining "here's why that hurt"). Yet, learning from feedback for…
From Human-Human Collaboration to Human-Agent Collaboration: A Vision, Design Philosophy, and an Empirical Framework for Achieving Successful Partnerships Between Humans and LLM Agents
Bingsheng Yao, Chaoran Chen, April Yi Wang +3
The emergence of Large Language Model (LLM) agents enables us to build agent-based intelligent systems that move beyond the role of a "tool" to become genuine collaborators with hu…
Generating Situated Reflection Triggers about Alternative Solution Paths: A Case Study of Generative AI for Computer-Supported Collaborative Learning
Atharva Naik, Jessica Ruhan Yin, Anusha Kamath +6
An advantage of Large Language Models (LLMs) is their contextualization capability - providing different responses based on student inputs like solution strategy or prior discussio…