New Paper Day! For EMNLP findings—in LM red-teaming, we show you have to optimize for **both** perplexity and toxicity for high-probability, hard to filter, and natural attacks!
@juliekallini.bsky.social
New Paper Day! For ACL 2025 Findings: You should **drop dropout** when you are training your LMs AND MLMs!
I might be able to hire a postdoc for this fall in computational linguistics at UT Austin. Topics in the general LLM + cognitive space (particularly reasoning, chain of thought, LLMs + code) and LLM + linguistic space. If this could be of interest, feel free to get in touch!
Life update! Excited to announce that I’ll be starting as an assistant professor at Cornell Info Sci in August 2026! I’ll be recruiting students this upcoming cycle! An abundance of thanks to all my mentors and friends who helped make this possible!!
If you’re at #ICLR2025, come see me present 💪MrT5 on Thursday (4/24)! 🪧 Poster: 10–12:30 in Hall 3 + 2B (#273) ⚡️ Lightning talk: right after in Opal 103–104 (Session on Tokenizer-Free, End-to-end Architectures) Plus, MrT5 has many exciting updates 🧵
🎙️ Speech recognition is great - if you speak the right language. Our new @stanfordnlp.bsky.social paper introduces CTC-DRO, a training method that reduces worst-language errors by up to 47.1%. Work w/ Ananjan, Moussa, @jurafsky.bsky.social, Tatsu Hashimoto and Karen Livescu. Here’s how it works 🧵
"Mission: Impossible" was featured in Quanta Magazine! Big thank you to @benbenbrubaker.bsky.social for the wonderful article covering our work on impossible languages. Ben was so thoughtful and thorough in all our conversations, and it really shows in his writing!
Large language models may not be so omnipotent after all. New research shows that LLMs, like humans, prefer to learn some linguistic patterns over others. @benbenbrubaker.bsky.social reports: www.quantamagazine.org/can-ai-model...
Quanta write-up of our Mission: Impossible Language Models work, led by @juliekallini.bsky.social. As the photos suggest, Richard, @isabelpapad.bsky.social, and I do all our work sitting together around a single laptop and pointing at the screen.
Large language models may not be so omnipotent after all. New research shows that LLMs, like humans, prefer to learn some linguistic patterns over others. @benbenbrubaker.bsky.social reports: www.quantamagazine.org/can-ai-model...