🚀Introducing TMLR Beyond PDF!
🎬This is a new, HTML-based submission format for TMLR, that supports interactive figures and videos, along with the usual LaTeX and images.
🎉Thanks to TMLR Editors in Chief @hugo_larochelle @thegautamkamath @NailaMurray Nihar B. Shah @lcharlin!View quoted post on X
Thrilled to share our latest research on verifying CoT reasonings, completed during my recent internship at FAIR @metaai. In this work, we introduce Circuit-based Reasoning Verification (CRV), a new white-box method to analyse and verify how LLMs reason, step-by-step.View quoted post on X
We at TMLR are proud to announce that selected papers will now be eligible for an opportunity to present at the joint NeurIPS/ICML/ICLR Journal-to-Conference (J2C) Track:View quoted post on X
medium.com/@TmlrOrg/tmlr-…
Introducing DINOv3: a state-of-the-art computer vision model trained with self-supervised learning (SSL) that produces powerful, high-resolution image features. For the first time, a single frozen vision backbone outperforms specialized solutions on multiple long-standing dense prediction tasks.
Learn more about DINOv3 here: ai.meta.com/blog/dinov3-se…View quoted post on X
LLMs for code should do much better if they can iterate on tests -- but they don't. Our new work (RLEF) addresses this with execution feedback at RL *training time* to use execution feedback at *inference time*. arxiv.org/abs/2410.02089 is just out! 1/6View quoted post on X
