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*
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*
Excited to be in Albuquerque presenting our paper this afternoon at @naaclmeeting 2025!
Excited to be in Albuquerque presenting our paper this afternoon at @naaclmeeting 2025!
@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)
@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)
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?
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?
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...
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...
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.
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.