Brihi Joshi

Brihi Joshi

@brihi.bsky.social

NLP PhD @ USC Everything language, humans, felines and music (and an infrequent shit-poster) brihijoshi.github.io

814 Followers 462 Following 14 Posts Joined Nov 2024
10 months ago
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Improving LLM Personas via Rationalization with Psychological Scaffolds Language models prompted with a user description or persona can predict a user's preferences and opinions, but existing approaches to building personas -- based solely on a user's demographic attribut...

๐Ÿ“– So fun to collaborate with amazing folks at USC (Xiang Ren, @swabhs.bsky.social ) and Apple (Rik Koncel-Kedziorski, Tim Paek) on this work! ๐Ÿค๐Ÿ’ก๐Ÿ“ฃ
Excited to finally share thisโ€”let us know what you think! ๐Ÿ™Œ๐Ÿฝโœจ๐ŸŽ‰

More details in our draft here: arxiv.org/abs/2504.17993

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10 months ago
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๐ŸŒŽ PB&J improvements do not hinge on any particular groupโ€”we see gains across education, race, income, and gender. ๐ŸŒˆ๐Ÿ“Š๐Ÿค

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10 months ago

๐Ÿ’ก Itโ€™s not just about having more reasoning tokensโ€”itโ€™s about what those tokens convey. ๐Ÿง๐Ÿ”โœจ
We found that *human-written rationales* improved personas the most, but LLM-generated ones came close, showing that good scaffolds are very useful for personas. ๐Ÿง‘โ€๐Ÿ’ป๐Ÿ“ˆ๐Ÿ”ฌ

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๐Ÿ“Š We tested PB&J on two tasks: predicting opinions and movie ratings. PB&J consistently outperformed methods based on demographics and/or judgments. Using scaffolds boosted performance even more! ๐ŸŽฅ๐Ÿ—ณ๏ธ๐Ÿ†

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10 months ago

๐Ÿ”ง We propose psychological scaffoldsโ€”frameworks based on life experiences, personality traits, or core beliefsโ€”to further guide the structure of LLM rationales. ๐Ÿ› ๏ธ๐Ÿงฌ๐ŸŽจ

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10 months ago
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๐Ÿง  We introduce PB&J (Psychology of Behaviour and Judgments) that draws from folk psychologyโ€”the way people naturally explain each otherโ€™s actions. PB&J adds LLM-generated rationales to personas, helping models better represent user behavior. ๐Ÿ“š๐Ÿงฉ๐Ÿ’ฌ

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10 months ago

๐Ÿค– LLMs can mimic human behavior with personas, but most current approaches focus only on demographics or past responses as user context, often overlooking the reasons why users think or act a certain way. ๐Ÿง๐Ÿ’ญ๐Ÿ”„

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10 months ago
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Reasoning about the "why" behind user behavior can improve LLM personas! โœจ๐Ÿง ๐Ÿ“ˆ

๐Ÿ“Excited to share our new work: Improving LLM Personas via Rationalization with Psychological Scaffolds

๐Ÿ”— arxiv.org/abs/2504.17993
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1 year ago

omggg itโ€™s amazing ๐Ÿ˜ญ combined together gave me queen vibes!!

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1 year ago

๐Ÿ™‹๐Ÿปโ€โ™€๏ธ๐Ÿ™‹๐Ÿปโ€โ™€๏ธ

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1 year ago

UGH ADORABLE

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1 year ago

omg this can be 3D printed at the makerspace!!

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1 year ago
How I Use "AI" I don't think that AI models (by which I mean: large language models) are over-hyped. In this post I will list 50 ways I've used them.

These days, Iโ€™ve been obsessed with reading about how people use LLMs and this blog by Nicholas Carlini has been my TOP read since August - nicholas.carlini.com/writing/2024...

Not a lot of us who work with LLMs โ€œuseโ€ them, and this is such a great starter to all of that!

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1 year ago

@justachetan.bsky.social!!!

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1 year ago

Netflix needs to stop asking if Iโ€™m still watching and start asking if I moved the laundry to the dryer

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1 year ago
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#EMNLP2024 has been a treat so far! Of course it doesn't hurt to win an outstanding paper award with my incredible PhD students Jaspreet Ranjit and @brihi.bsky.social and our wonderful collaborators at USC ๐Ÿ˜œ
Paper: dill-lab.github.io/oath-frames/

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