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cs.CL2026
Hitting a Moving Target: Test-Time Adaptation for AI Text Detection under Continual Distribution Shift
Kevin Ren, Manish Raghavan, Nikhil Garg
Deployed AI text detection approaches are supervised, relying on training-time access to labeled datasets of both human-written and AI-generated text. This approach is vulnerable t…
cs.HC2026
Incentives shape how humans co-create with generative AI
Nathanael Jo, Manish Raghavan
Generative AI is quickly becoming an integral part of people's everyday workflows. Early evidence has shown that while generative AI can increase individual-level productivity, it…
cs.CY2026
The Subjectivity of Monoculture
Nathanael Jo, Nikhil Garg, Manish Raghavan
Machine learning models---including large language models (LLMs)---are often said to exhibit monoculture, where outputs agree strikingly often. However, we present two experiments…