Learning from Failures in Multi-Attempt Reinforcement Learning Paper • 2503.04808 • Published 9 days ago • 16
Learning from Failures in Multi-Attempt Reinforcement Learning Paper • 2503.04808 • Published 9 days ago • 16
Generating Symbolic World Models via Test-time Scaling of Large Language Models Paper • 2502.04728 • Published Feb 7 • 19
OpenCoder: The Open Cookbook for Top-Tier Code Large Language Models Paper • 2411.04905 • Published Nov 7, 2024 • 116
PositionID: LLMs can Control Lengths, Copy and Paste with Explicit Positional Awareness Paper • 2410.07035 • Published Oct 9, 2024 • 17
A Closer Look into Mixture-of-Experts in Large Language Models Paper • 2406.18219 • Published Jun 26, 2024 • 16
A Closer Look into Mixture-of-Experts in Large Language Models Paper • 2406.18219 • Published Jun 26, 2024 • 16
Unlocking Continual Learning Abilities in Language Models Paper • 2406.17245 • Published Jun 25, 2024 • 30
Unlocking Continual Learning Abilities in Language Models Paper • 2406.17245 • Published Jun 25, 2024 • 30
Efficient Continual Pre-training by Mitigating the Stability Gap Paper • 2406.14833 • Published Jun 21, 2024 • 20
Efficient Continual Pre-training by Mitigating the Stability Gap Paper • 2406.14833 • Published Jun 21, 2024 • 20
PIN: A Knowledge-Intensive Dataset for Paired and Interleaved Multimodal Documents Paper • 2406.13923 • Published Jun 20, 2024 • 23
LoGAH: Predicting 774-Million-Parameter Transformers using Graph HyperNetworks with 1/100 Parameters Paper • 2405.16287 • Published May 25, 2024 • 11
LoGAH: Predicting 774-Million-Parameter Transformers using Graph HyperNetworks with 1/100 Parameters Paper • 2405.16287 • Published May 25, 2024 • 11