Follow the Gradient: Tracing Safety Degradation Back to Training Data Paper • 2610.37481 • Published 13 days ago • 32
ÜberWeb: Insights from Multilingual Curation for a 20-Trillion-Token Dataset Paper • 2602.15210 • Published Feb 25 • 1
The Finetuner's Fallacy: When to Pretrain with Your Finetuning Data Paper • 2603.16177 • Published Mar 21
20/20 Vision Language Models: A Prescription for Better VLMs through Data Curation Alone Paper • 2605.11405 • Published May 13
DatBench: Discriminative, Faithful, and Efficient VLM Evaluations Paper • 2601.02316 • Published Jan 5 • 10
Safety Pretraining: Toward the Next Generation of Safe AI Paper • 2504.16980 • Published Apr 23, 2025
Follow the Gradient: Tracing Safety Degradation Back to Training Data Paper • 2610.37481 • Published 13 days ago • 32
Harbor Adapters and Harbor-Index: Infrastructure and a Curated Meta-Dataset for Large-Scale Agentic Evaluation Paper • 2609.04298 • Published Sep 9 • 1
Terminal-Bench: Benchmarking Agents on Hard, Realistic Tasks in Command Line Interfaces Paper • 2601.11868 • Published Jan 17 • 38
LAION-BVD: A 10-Million-Hour Open Video Dataset for Multimodal Pre-training Paper • 2608.24845 • Published Aug 25 • 16
DataComp-VLM: Improved Open Datasets for Vision-Language Models Paper • 2606.28551 • Published Jun 26 • 52
Solving Spatial Supersensing Without Spatial Supersensing Paper • 2511.16655 • Published Nov 20, 2025