Model-tuning Via Prompts Makes NLP Models Adversarially Robust Paper • 2303.07320 • Published Mar 13, 2023
Scaling Laws for Data Filtering -- Data Curation cannot be Compute Agnostic Paper • 2404.07177 • Published Apr 10, 2024
Rethinking LLM Memorization through the Lens of Adversarial Compression Paper • 2404.15146 • Published Apr 23, 2024
OpenUnlearning: Accelerating LLM Unlearning via Unified Benchmarking of Methods and Metrics Paper • 2506.12618 • Published Jun 14
BeyondWeb: Lessons from Scaling Synthetic Data for Trillion-scale Pretraining Paper • 2508.10975 • Published 9 days ago • 53
Distributionally Robust Optimization with Bias and Variance Reduction Paper • 2310.13863 • Published Oct 21, 2023
The Benefits of Balance: From Information Projections to Variance Reduction Paper • 2408.15065 • Published Aug 27, 2024 • 1
Running 5 5 OpenThoughts Benchmark Explorer 📊 Explore model performance through benchmark correlations
Scaling Laws for Robust Comparison of Open Foundation Language-Vision Models and Datasets Paper • 2506.04598 • Published Jun 5 • 6
Running 5 5 OpenThoughts Benchmark Explorer 📊 Explore model performance through benchmark correlations
Alice in Wonderland: Simple Tasks Showing Complete Reasoning Breakdown in State-Of-the-Art Large Language Models Paper • 2406.02061 • Published Jun 4, 2024 • 2
DataComp-LM: In search of the next generation of training sets for language models Paper • 2406.11794 • Published Jun 17, 2024 • 54
Scaling Laws for Robust Comparison of Open Foundation Language-Vision Models and Datasets Paper • 2506.04598 • Published Jun 5 • 6