James Michaelov

77 posts

James Michaelov

James Michaelov

@jamichaelov

Postdoc @MIT. Previously: @CogSciUCSD, @CARTAUCSD, @AmazonScience, @InfAtEd, @SchoolofPPLS. Research: Language in humans and machines

Katılım Eylül 2017
768 Takip Edilen382 Takipçiler
James Michaelov
James Michaelov@jamichaelov·
Excited to announce that I’ll be presenting a paper at #NeurIPS this year! Reach out if you’re interested in chatting about LM training dynamics, architectural differences, shortcuts/heuristics, or anything at the CogSci/NLP/AI interface in general! #Neurips2025
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James Michaelov
James Michaelov@jamichaelov·
In the most extreme case, LMs assign sentences such as ‘the car was given a parking ticket by the explorer’ (unlikely but possible event) a lower probability than ‘the car was given a parking ticket by the brake’ (impossible event, related final word) over half of the time.
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James Michaelov
James Michaelov@jamichaelov·
New paper accepted at Findings of ACL! TL;DR: While language models generally predict sentences describing possible events to have a higher probability than impossible (animacy-violating) ones, this is not robust for generally unlikely events + is impacted by semantic relatedness
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James Michaelov
James Michaelov@jamichaelov·
@linguist_cat And the current wave of recurrent architectures has just started! As we see more and more new architectures and developments, it will be interesting to see how they compare. One thing does seem clear though: recurrent models are back with a vengeance!
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James Michaelov
James Michaelov@jamichaelov·
@linguist_cat With reading time, the results are more variable between experiments, and this seems like it might be related to the difference in stimuli (see paper for more details)
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James Michaelov
James Michaelov@jamichaelov·
New preprint with @linguist_cat and Ben Bergen! We’ve all heard of the new wave of recurrent language models, but how good are they for modeling human language comprehension? Quite good, it turns out! 🧵 arxiv.org/abs/2404.19178
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James Michaelov
James Michaelov@jamichaelov·
On the other hand, we show that the next-word prediction is sufficient to get both effects, at least qualitatively.
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