5 papers
DataComp-VLM: Improved Open Datasets for Vision-Language Models
Matteo Farina, Vishaal Udandarao, Thao Nguyen +34
Building performant Vision-Language Models (VLMs) requires carefully curating large-scale training datasets, yet the community lacks systematic benchmarks for evaluating such curat…
Solving Spatial Supersensing Without Spatial Supersensing
Vishaal Udandarao, Shyamgopal Karthik, Surabhi S. Nath +3
Cambrian-S aims to take the first steps towards improving video world models with spatial supersensing by introducing (i) two benchmarks, VSI-Super-Recall (VSR) and VSI-Super-Count…
Mapping Post-Training Forgetting in Language Models at Scale
Jackson Harmon, Andreas Hochlehnert, Matthias Bethge +1
Scaled post-training now drives many of the largest capability gains in language models (LMs), yet its effect on pretrained knowledge remains poorly understood. Not all forgetting…
A Sober Look at Progress in Language Model Reasoning: Pitfalls and Paths to Reproducibility
Andreas Hochlehnert, Hardik Bhatnagar, Vishaal Udandarao +3
Reasoning has emerged as the next major frontier for language models (LMs), with rapid advances from both academic and industrial labs. However, this progress often outpaces method…
Project Alexandria: Towards Freeing Scientific Knowledge from Copyright Burdens via LLMs
Christoph Schuhmann, Gollam Rabby, Ameya Prabhu +9
Paywalls, licenses and copyright rules often restrict the broad dissemination and reuse of scientific knowledge. We take the position that it is both legally and technically feasib…