4 citations · 6 across the 17 of their papers we have counts for
Showing cs.AIShow all
3 papers · 1 filter
cs.AI2026
Learning What to Forget: Distributional Unlearning for LLM Representation Spaces
Pinaki Mohanty, Haoran Tang, Maggie Makar +1
Machine learning systems increasingly face the need to remove the influence of entire data domains, such as toxic language, harmful behavior, or topical content, rather than isolat…
cs.AI2026
From Fallback to Frontline: When Can LLMs be Superior Annotators of Human Perspectives?
Hasan Amin, Harry Yizhou Tian, Xiaoni Duan +3
Although large language models (LLMs) are increasingly used as annotators at scale, they are typically treated as a pragmatic fallback rather than a faithful estimator of human per…
cs.AI2026
Align When They Want, Complement When They Need! Human-Centered Ensembles for Adaptive Human-AI Collaboration
Hasan Amin, Ming Yin, Rajiv Khanna
In human-AI decision making, designing AI that complements human expertise has been a natural strategy to enhance human-AI collaboration, yet it often comes at the cost of decrease…