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Reasoning Capacity in Multi-Agent Systems: Limitations, Challenges and Human-Centered Solutions
We present a formal definition of reasoning capacity and illustrate its utility in identifying limitations within each component of the system.
Towards Multifaceted Human-Centered AI
Human-centered AI workflows involve stakeholders with multiple roles interacting with each other and automated agents to accomplish diverse tasks.
MEGAnno: Exploratory Labeling for NLP in Computational Notebooks
We present MEGAnno, a novel exploratory annotation framework designed for NLP researchers and practitioners.
HEIDL: Learning Linguistic Expressions with Deep Learning and Human-in-the-Loop
While the role of humans is increasingly recognized in machine learning community, representation of and interaction with models in current human-in-the-loop machine learning (HITL-ML) approaches are too low-level and far-removed from human's conceptual models.
