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

[NeurIPS'24 Spotlight] Observational Scaling Laws

A toolkit for scaling law research ⚖

Dimensionless learning

PluRel: Synthetic Data unlocks Scaling Laws for Relational Foundation Models

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

[ICLR 2025] Official implementation of "Towards Neural Scaling Laws for Time Series Foundation Models"

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)

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。

[NeurIPS 2023] Multi-fidelity hyperparameter optimization with deep power laws that achieves state-of-the-art results across diverse benchmarks.

[ICML 2023] "Data Efficient Neural Scaling Law via Model Reusing" by Peihao Wang, Rameswar Panda, Zhangyang Wang

Awesome-RL-Reasoning

No description provided.

A method for calculating scaling laws for LLMs from publicly available models

code for Scaling Laws for Language Transfer Learning

A curated collection of NLP and LLM resources. Covers essential papers and blogs on Transformers, Reinforcement Learning (RLHF, DPO, GRPO), Mechanistic Interpretability, Scaling Laws, and MLSys.

[ACL2025 Oral] Cuckoo: A Series of IE Free Riders Using LLM's Resources to Scale up Themselves.

Optimization and Scaling of Medium-Frequency Transformers

[ICLR 2026 Oral] Optimal Sparsity of Mixture-of-Experts Language Models for Reasoning Tasks

Code for CoNLL BabyLM workshop Mini Minds: Exploring Bebeshka and Zlata Baby Models

Long Context, Less Focus: A Scaling Gap in LLMs Revealed through Privacy and Personalization

🌹[ICML 2024] Selecting Large Language Model to Fine-tune via Rectified Scaling Law

Code for ICML 2025 How Do Large Language Monkeys Get Their Power (Laws)?

A high-performance Python library for simulating Diffusion-Limited Aggregation (DLA) with Numba JIT acceleration, parallel rendering, and automated fractal dimension analysis of dendritic growth patterns.

🔬 Implementation of agent coordination architectures and scaling principles from 'Towards a Science of Scaling Agent Systems' (arXiv:2512.08296). Research-backed multi-agent framework with benchmarks and validation.