Zayne Sprague
@zaynesprague.bsky.social
Ph.D. student at the University of Texas in Austin. My interest is in NLP, RL and CogSci research focused on reasoning in AI models.
Reposted by Zayne Sprague
How do LLMs learn to reason from data? Are they ~retrieving the answers from parametric knowledge🦜? In our new preprint, we look at the pretraining data and find evidence against this:
Procedural knowledge in pretraining drives LLM reasoning ⚙️🔢
🧵⬇️
Procedural knowledge in pretraining drives LLM reasoning ⚙️🔢
🧵⬇️
November 20, 2024 at 4:35 PM
How do LLMs learn to reason from data? Are they ~retrieving the answers from parametric knowledge🦜? In our new preprint, we look at the pretraining data and find evidence against this:
Procedural knowledge in pretraining drives LLM reasoning ⚙️🔢
🧵⬇️
Procedural knowledge in pretraining drives LLM reasoning ⚙️🔢
🧵⬇️
Reposted by Zayne Sprague
We got an 🥂 Outstanding Paper Award!! Cannot be more grateful 🥹 This is super validating for our long pursuit of computational work on QUD.
Congrats to the amazing @yatingwu.bsky.social, Ritika Mangla, Alex Dimakis, @gregdnlp.bsky.social
Congrats to the amazing @yatingwu.bsky.social, Ritika Mangla, Alex Dimakis, @gregdnlp.bsky.social
Wednesday at #EMNLP: @yatingwu.bsky.social will present our work connecting curiosity and questions in discourse. We built strong models to predict salience, outperforming large LLMs.
👉[Oral] Discourse+Phonology+Syntax2 10:30-12:00 @ Flagler
also w/ Ritika Mangla @gregdnlp.bsky.social Alex Dimakis
👉[Oral] Discourse+Phonology+Syntax2 10:30-12:00 @ Flagler
also w/ Ritika Mangla @gregdnlp.bsky.social Alex Dimakis
November 15, 2024 at 1:12 PM
We got an 🥂 Outstanding Paper Award!! Cannot be more grateful 🥹 This is super validating for our long pursuit of computational work on QUD.
Congrats to the amazing @yatingwu.bsky.social, Ritika Mangla, Alex Dimakis, @gregdnlp.bsky.social
Congrats to the amazing @yatingwu.bsky.social, Ritika Mangla, Alex Dimakis, @gregdnlp.bsky.social
Reposted by Zayne Sprague
New paper from Martha Lewis and me:
"Evaluating the Robustness of Analogical Reasoning in Large Language Models"
Preprint:
arxiv.org/pdf/2411.14215
This is a much-extended follow-up on our earlier pre-print on "counterfactual tasks" in letter-string analogies.
🧵
"Evaluating the Robustness of Analogical Reasoning in Large Language Models"
Preprint:
arxiv.org/pdf/2411.14215
This is a much-extended follow-up on our earlier pre-print on "counterfactual tasks" in letter-string analogies.
🧵
arxiv.org
November 22, 2024 at 2:32 PM
New paper from Martha Lewis and me:
"Evaluating the Robustness of Analogical Reasoning in Large Language Models"
Preprint:
arxiv.org/pdf/2411.14215
This is a much-extended follow-up on our earlier pre-print on "counterfactual tasks" in letter-string analogies.
🧵
"Evaluating the Robustness of Analogical Reasoning in Large Language Models"
Preprint:
arxiv.org/pdf/2411.14215
This is a much-extended follow-up on our earlier pre-print on "counterfactual tasks" in letter-string analogies.
🧵