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UW NLP

@uwnlp.bsky.social
645 followers 18 following 2 posts

The NLP group at the University of Washington.

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Stella Li @stellali.bsky.social · 06/12/2024
31% of US adults use generative AI for healthcare 🤯But most AI systems answer questions assertively—even when they don’t have the necessary context. Introducing #MediQ a framework that enables LLMs to recognize uncertainty🤔and ask the right questions❓when info is missing: 🧵
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Melanie Sclar @melaniesclar.bsky.social · 24/04/2025
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!
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Kabir Ahuja @kabirahuja2431.bsky.social · 22/04/2025
📢 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
A screenshot of the first page of the paper, containing the paper title: Finding Flawed Fictions: Evaluating Complex Reasoning in Language Models via Plot Hole Detection and the names of the authors: Kabir Ahuja, Melanie Sclar, and Yulia Tsvetkov. All the three authors are from CSE department in the University of Washington in Seattle, USA. They can be reached at {kahuja,msclar,yuliats}@cs.washington.edu
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Abhilasha Ravichander @lasha.bsky.social · 21/03/2025
Want to know what training data has been memorized by models like GPT-4? We propose information-guided probes, a method to uncover memorization evidence in *completely black-box* models, without requiring access to 🙅‍♀️ Model weights 🙅‍♀️ Training data 🙅‍♀️ Token probabilities 🧵 (1/5)
arxiv.org
Information-Guided Identification of Training Data Imprint in (Proprietary) Large Language Models
High-quality training data has proven crucial for developing performant large language models (LLMs). However, commercial LLM providers disclose few, if any, details about the data used for training. ...
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Hyunwoo Kim @hyunwoo-kim.bsky.social · 20/02/2025
🚨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?🧵
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Abhilasha Ravichander @lasha.bsky.social · 31/01/2025
We are launching HALoGEN💡, a way to systematically study *when* and *why* LLMs still hallucinate. New work w/ Shrusti Ghela*, David Wadden, and Yejin Choi 💫 📝 Paper: arxiv.org/abs/2501.08292 🚀 Code/Data: github.com/AbhilashaRav... 🌐 Website: halogen-hallucinations.github.io 🧵 [1/n]
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Akari Asai @akariasai.bsky.social · 04/12/2024
I’m on the academic job market this year! I’m completing my @uwcse.bsky.social @uwnlp.bsky.social Ph.D. (2025), focusing on overcoming LLM limitations like hallucinations, by building new LMs. My Ph.D. work focuses on Retrieval-Augmented LMs to create more reliable AI systems 🧵
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Jiacheng Liu @liujch1998.bsky.social · 09/12/2024
Want to predict the task performance of LMs before pretraining them? We develop task scaling laws and model ladders, which predict the accuracy on individual tasks by OLMo 2 7B & 13B models within 2 points of absolute error. The cost is 1% of the compute used to pretrain them.
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Alisa Liu @alisawuffles.bsky.social · 11/12/2024
excited to be at #NeurIPS2024! I'll be presenting our data mixture inference attack 🗓️ Thu 4:30pm w/ @jon.jon.ke — stop by to learn what trained tokenizers reveal about LLM development (‼️) and chat about all things tokenizers. 🔗 arxiv.org/abs/2407.16607
poster for paper
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UW NLP @uwnlp.bsky.social · 22/11/2024
See our latest work on (among other things) machine text detection through linguistic creativity measurement!
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Akari Asai @akariasai.bsky.social · 19/11/2024
1/ Introducing ᴏᴘᴇɴꜱᴄʜᴏʟᴀʀ: a retrieval-augmented LM to help scientists synthesize knowledge 📚 @uwnlp.bsky.social & Ai2 With open models & 45M-paper datastores, it outperforms proprietary systems & match human experts. Try out our demo! openscholar.allen.ai
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UW NLP @uwnlp.bsky.social · 19/11/2024
We'd love to be in your starter pack!
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