Check out our work on preference modeling through latent (& interpretable) attribute representation learning! PrefPalette allows you to understand _why_ something is preferred and _how_ preference varies depending on context 🎨

Stella Li@stellali.bsky.social · last yr.

WHY do you prefer something over another? Reward models treat preference as a black-box😶‍🌫️but human brains🧠decompose decisions into hidden attributes We built the first system to mirror how people really make decisions in our recent COLM paper🎨PrefPalette✨ Why it matters👉🏻🧵

WHY do you prefer something over another? Reward models treat preference as a black-box😶‍🌫️but human brains🧠decompose decisions into hidden attributes We built the first system to mirror how people really make decisions in our recent COLM paper🎨PrefPalette✨ Why it matters👉🏻🧵

See our work on procedurally generating challenging reasoning problems on detecting inconsistencies in stories! FlawedFictions is a great example of what I'm most excited about: reliable synthetic data for reasoning in under-explored domains. (I'm at ICLR to chat, DMs open!)

Kabir Ahuja@kabirahuja2431.bsky.social · last yr.

📢 New Paper! Tired 😴 of reasoning benchmarks full of math & code? In our work we consider the problem of reasoning for plot holes in stories -- inconsistencies in a storyline that break the internal logic or rules of a story’s world 🌎 W @melaniesclar.bsky.social, and @tsvetshop.bsky.social 1/n

Excited to be at #ICLR2025 🤩 I'll be giving an oral presentation for Creativity Index on Fri 25th 11:06, Garnet 212&219 🎙️ I'll also be presenting posters: 📍ExploreToM, Sat 26th 10:00, Hall 3 + 2B #49 📍CreativityIndex, Fri 25th 15:00, Hall 3 + 2B #618 Hope to see you there!

📢 New Paper! Tired 😴 of reasoning benchmarks full of math & code? In our work we consider the problem of reasoning for plot holes in stories -- inconsistencies in a storyline that break the internal logic or rules of a story’s world 🌎 W @melaniesclar.bsky.social, and @tsvetshop.bsky.social 1/n

🚨New Paper! So o3-mini and R1 seem to excel on math & coding. But how good are they on other domains where verifiable rewards are not easily available, such as theory of mind (ToM)? Do they show similar behavioral patterns? 🤔 What if I told you it's...interesting, like the below?🧵

LLMs generate novel word sequences not contained in their pretraining data. However, compared to humans, models generate significantly fewer novel n-grams. RLHF = 30% *more* copying than base! Awesome work from the awesome Ximing Lu (gloriaximinglu.github.io) et al. 🤩 arxiv.org/pdf/2410.04265

Are LLMs 🤖 as creative as humans 👩‍🎓? Not quite! Introducing CREATIVITY INDEX: a metric that quantifies the linguistic creativity of a text by reconstructing it from existing text snippets on the web. Spoiler: professional human writers like Hemingway are still far more creative than LLMs! 😲