Research
I work on research at the intersection of neuroscience, cognitive science, and artificial
intelligence.
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Instruction-tuning Aligns LLMs to the Human Brain
Khai Loong Aw,
Syrielle Montariol1,
Badr AlKhamissi1,
Martin Schrimpf2,
Antoine Bosselut2
arXiv, 2023
arXiv
We investigate how instruction-tuning affects language models from a neuroscientific perspective, revealing that it generally improves their alignment with human brain activity, with model size and world knowledge playing key roles.
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Training language models to summarize narratives improves brain
alignment
Khai Loong Aw,
Mariya Toneva
ICLR, 2023   (Notable Top 25%)
arXiv
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GitHub
We show that training language models to summarize narratives (i.e., deeper understanding of characters,
emotions, and relationships) results in richer representations that are more aligned to human brain
activity.
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Detecting False Alarms from Automatic Static Analysis Tools: How Far are We?
Hong Jin Kang,
Khai Loong Aw,
David Lo
ICSE, 2022   (Distinguished Paper Nominee)
arXiv
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Poster
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Video
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