Focus on interpretability, fairness and ethics of AI, causal inference .
Ex-graduate Intern at Capital One.
(1/n) Link: arxiv.org/abs/2509.16400
(1/n) Link: arxiv.org/abs/2509.16400
hsp2025.github.io/abstracts/19...
hsp2025.github.io/abstracts/19...
We just released IssueBench – the largest, most realistic benchmark of its kind – to answer this question more robustly than ever before.
Long 🧵with spicy results 👇
We just released IssueBench – the largest, most realistic benchmark of its kind – to answer this question more robustly than ever before.
Long 🧵with spicy results 👇
AI at Work: Building and Evaluating Trust
Presented by our Trustworthy AI in Law & Society (TRIALS) institute.
Feb 3-4
Washington DC
Open to all!
Details and registration at: trails.gwu.edu/trailscon-2025
Sponsorship details at: trails.gwu.edu/media/556
AI at Work: Building and Evaluating Trust
Presented by our Trustworthy AI in Law & Society (TRIALS) institute.
Feb 3-4
Washington DC
Open to all!
Details and registration at: trails.gwu.edu/trailscon-2025
Sponsorship details at: trails.gwu.edu/media/556
There are lots of hate datasets with different nuances. We show how to pretrain on a COT-enhanced dataset to get great performance on data du jour.
by Huy Nghiem +al EMNLP’24
hal3.name/docs/daume24...
>
There are lots of hate datasets with different nuances. We show how to pretrain on a COT-enhanced dataset to get great performance on data du jour.
by Huy Nghiem +al EMNLP’24
hal3.name/docs/daume24...
>