Minimal reproduction of OneRec
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Updated
Mar 31, 2026 - Python
Minimal reproduction of OneRec
Scaling Data-Constrained Language Models
Reproducible scaling laws for contrastive language-image learning (https://arxiv.org/abs/2212.07143)
🔥🔥🔥 Latest Advances on Large Recommendation Models
🔥PhysInOne in Python (CVPR 2026)
A toolkit for scaling law research ⚖
[NeurIPS'24 Spotlight] Observational Scaling Laws
PluRel: Synthetic Data unlocks Scaling Laws for Relational Foundation Models
Dimensionless learning
Official code for the ICLR 2025 paper, "Scaling Offline Model-Based RL via Jointly-Optimized World-Action Model Pretraining"
qwen3-base family of models RL on gsm8k using verl, is there an RL power law on downstream tasks?
[ICLR26] AI-based scaling law discovery
MDM-Prime-v2: Binary Encoding and Index Shuffling Enable Compute-optimal Scaling of Diffusion Language Models
[ICLR 2025] Official implementation of "Towards Neural Scaling Laws for Time Series Foundation Models"
[NeurIPS 2023] Multi-fidelity hyperparameter optimization with deep power laws that achieves state-of-the-art results across diverse benchmarks.
The Silence of Intelligence — A comprehensive analysis of Anthropic CEO Dario Amodei's philosophy on Scaling Laws, AI safety, and the future of humanity. / Anthropic CEO ダリオ・アモディの思想を体系化したOSS書籍。スケーリング則の本質とAIの未来を解き明かす。
Code for reproducing the experiments on large-scale pre-training and transfer learning for the paper "Effect of large-scale pre-training on full and few-shot transfer learning for natural and medical images" (https://arxiv.org/abs/2106.00116)
[ICML 2023] "Data Efficient Neural Scaling Law via Model Reusing" by Peihao Wang, Rameswar Panda, Zhangyang Wang
Awesome-RL-Reasoning
NeurIPS 2026 - Multi-Network Training for Transfer Learning on Temporal Graphs
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