Running 2.57k 2.57k The Ultra-Scale Playbook 🌌 The ultimate guide to training LLM on large GPU Clusters
CoRAG: Collaborative Retrieval-Augmented Generation Paper • 2504.01883 • Published Apr 2 • 10 • 2
SAEs Can Improve Unlearning: Dynamic Sparse Autoencoder Guardrails for Precision Unlearning in LLMs Paper • 2504.08192 • Published Apr 11 • 4
SAEs $\textit{Can}$ Improve Unlearning: Dynamic Sparse Autoencoder Guardrails for Precision Unlearning in LLMs Paper • 2504.08192 • Published Apr 11 • 4 • 2
Decoding Dark Matter: Specialized Sparse Autoencoders for Interpreting Rare Concepts in Foundation Models Paper • 2411.00743 • Published Nov 1, 2024 • 7
Decoding Dark Matter: Specialized Sparse Autoencoders for Interpreting Rare Concepts in Foundation Models Paper • 2411.00743 • Published Nov 1, 2024 • 7
Decoding Dark Matter: Specialized Sparse Autoencoders for Interpreting Rare Concepts in Foundation Models Paper • 2411.00743 • Published Nov 1, 2024 • 7 • 2
Grass: Compute Efficient Low-Memory LLM Training with Structured Sparse Gradients Paper • 2406.17660 • Published Jun 25, 2024 • 5
Grass: Compute Efficient Low-Memory LLM Training with Structured Sparse Gradients Paper • 2406.17660 • Published Jun 25, 2024 • 5
Grass: Compute Efficient Low-Memory LLM Training with Structured Sparse Gradients Paper • 2406.17660 • Published Jun 25, 2024 • 5 • 3
An In-depth Look at Gemini's Language Abilities Paper • 2312.11444 • Published Dec 18, 2023 • 1