Han-yu (Henry) Wang
Applied Artificial Intelligence undergraduate at the University of Hong Kong. My research examines how people learn and generalise, how language models represent and use information, and how AI changes human thinking when people work with it. I use behavioural experiments, computational modelling, mechanistic analysis, and conceptual work.
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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