When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method Paper • 2402.17193 • Published Feb 27 • 23
Beyond A*: Better Planning with Transformers via Search Dynamics Bootstrapping Paper • 2402.14083 • Published Feb 21 • 47
In deep reinforcement learning, a pruned network is a good network Paper • 2402.12479 • Published Feb 19 • 17
GLoRe: When, Where, and How to Improve LLM Reasoning via Global and Local Refinements Paper • 2402.10963 • Published Feb 13 • 9
RLVF: Learning from Verbal Feedback without Overgeneralization Paper • 2402.10893 • Published Feb 16 • 10
DataDreamer: A Tool for Synthetic Data Generation and Reproducible LLM Workflows Paper • 2402.10379 • Published Feb 16 • 29
Self-Discover: Large Language Models Self-Compose Reasoning Structures Paper • 2402.03620 • Published Feb 6 • 109
Rephrasing the Web: A Recipe for Compute and Data-Efficient Language Modeling Paper • 2401.16380 • Published Jan 29 • 47
SliceGPT: Compress Large Language Models by Deleting Rows and Columns Paper • 2401.15024 • Published Jan 26 • 68
Deconstructing Denoising Diffusion Models for Self-Supervised Learning Paper • 2401.14404 • Published Jan 25 • 16
MM-LLMs: Recent Advances in MultiModal Large Language Models Paper • 2401.13601 • Published Jan 24 • 44
Spotting LLMs With Binoculars: Zero-Shot Detection of Machine-Generated Text Paper • 2401.12070 • Published Jan 22 • 42
Mamba: Linear-Time Sequence Modeling with Selective State Spaces Paper • 2312.00752 • Published Dec 1, 2023 • 138