It predicts pretty well—not just shifts in the last week, but also: 1. Who’s working an overnight shift (in our data + external validation in MIMIC) 2. Who’s working on a disruptive circadian schedule 3. How many patients has the doc seen *on the current shift*

🧑‍⚖️How well can LLMs summarize complex legal documents? And can we use LLMs to evaluate? Excited to be in Albuquerque presenting our paper this afternoon at @naaclmeeting 2025!

Although I cannot make #NAACL2025, @chicagohai.bsky.social will be there. Please say hi! @chachachen.bsky.social GPT ❌ x-rays (Friday 9-10:30) @mheddaya.bsky.social CaseSumm and LLM 🧑‍⚖️ (Thursday 2-3:30) @haokunliu.bsky.social @qiaoyu-rosa.bsky.social hypothesis generation 🔬 (Saturday at 4pm)

1/n You may know that large language models (LLMs) can be biased in their decision-making, but ever wondered how those biases are encoded internally and whether we can surgically remove them?

Spent a great day at Boulder meeting new students and old colleagues. I used to take this view every day. Here are the slides for my talk titled "Alignment Beyond Human Preferences: Use Human Goals to Guide AI towards Complementary AI": chenhaot.com/talks/alignm...

How do everyday narratives reveal hidden cause-and-effect patterns that shape our beliefs and behaviors? In our paper, we propose Causal Micro-Narratives to uncover narratives from real-world data. As a case study, we characterize the narratives about inflation in news.