The Edge-of-Reach Problem in Offline Model-Based Reinforcement Learning Paper • 2402.12527 • Published Feb 19, 2024
The AI Scientist-v2: Workshop-Level Automated Scientific Discovery via Agentic Tree Search Paper • 2504.08066 • Published Apr 10 • 11
Building Instruction-Tuning Datasets from Human-Written Instructions with Open-Weight Large Language Models Paper • 2503.23714 • Published Mar 31
Balancing Speed and Stability: The Trade-offs of FP8 vs. BF16 Training in LLMs Paper • 2411.08719 • Published Nov 10, 2024
Why We Build Local Large Language Models: An Observational Analysis from 35 Japanese and Multilingual LLMs Paper • 2412.14471 • Published Dec 19, 2024
Wider or Deeper? Scaling LLM Inference-Time Compute with Adaptive Branching Tree Search Paper • 2503.04412 • Published Mar 6 • 1
Wider or Deeper? Scaling LLM Inference-Time Compute with Adaptive Branching Tree Search Paper • 2503.04412 • Published Mar 6 • 1
Drop-Upcycling: Training Sparse Mixture of Experts with Partial Re-initialization Paper • 2502.19261 • Published Feb 26 • 7
Drop-Upcycling: Training Sparse Mixture of Experts with Partial Re-initialization Paper • 2502.19261 • Published Feb 26 • 7
TAID: Temporally Adaptive Interpolated Distillation for Efficient Knowledge Transfer in Language Models Paper • 2501.16937 • Published Jan 28 • 6
TAID: Temporally Adaptive Interpolated Distillation for Efficient Knowledge Transfer in Language Models Paper • 2501.16937 • Published Jan 28 • 6
Release of Pre-Trained Models for the Japanese Language Paper • 2404.01657 • Published Apr 2, 2024 • 1
TAID: Temporally Adaptive Interpolated Distillation for Efficient Knowledge Transfer in Language Models Paper • 2501.16937 • Published Jan 28 • 6
Agent Skill Acquisition for Large Language Models via CycleQD Paper • 2410.14735 • Published Oct 16, 2024 • 2