Han-yu (Henry) Wang
Applied Artificial Intelligence undergraduate at the University of Hong Kong, working where cognitive science meets AI. My research examines how people learn and remember, how language models represent and reason, and how human thinking changes when the two work together, using behavioral experiments, computational modeling, mechanistic analysis, and conceptual theory-building.
Publications & preprints
Human learning & cognition
- The Resolving Power of Transfer Experiments: When Can Designs Distinguish Accounts of Generalization? (under review)
- Functional Encoding and Representational Binding in Componential Transfer (under review)
- When Does a Smooth Learning Curve Mean Smooth Learning? Representational Format, Identifiability, and the Bounded Averaging Artifact (under review)
- Humans Disengage, Reasoning Models Persist: Separating Difficulty Registration from Deliberation Allocation (under review)
Language models: mechanisms & behavior
- BRIGHT: A Realistic and Challenging Benchmark for Reasoning-Intensive Retrieval (ICLR 2025 Spotlight)
- Priors Persist Through Suppression: A Stroop Paradigm for Lexical Override (under review)
- Function-Vector Heads Are Two Populations: Writers and Cancellers in In-Context Learning (under review)
CV (PDF) · GitHub · LinkedIn · whenry6688@gmail.com
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