scaling law

Pitfalls of Scale: Investigating the Inverse Task of Redefinition in Large Language Models ACL 2025 PolyPythias: Stability and Outliers across Fifty Language Model Pre-Training Runs ICLR 2025 RegMix: Data Mixture as Regression for Language Model Pre-training ICLR 2025 Revisiting Scaling Laws for Language Models: The Role of Data Quality and Training Strategies ACL 2025 Scalable Vision Language Model Training via High Quality Data Curation ACL 2025 Scaling Capability in Token Space: An Analysis of Large Vision Language Model JMLR 2025 Scaling Data-Constrained Language Models JMLR 2025 Scaling Inference-Efficient Language Models ICML 2025 Scaling Laws and Efficient Inference for Ternary Language Models ACL 2025 Scaling Laws Are Unreliable for Downstream Tasks: A Reality Check EMNLP 2025 Scaling Laws for Adversarial Attacks on Language Model Activations and Tokens ICLR 2025 Scaling Laws for Differentially Private Language Models ICML 2025 Scaling Laws for Downstream Task Performance in Machine Translation ICLR 2025 Scaling Laws for Forgetting during Finetuning with Pretraining Data Injection ICML 2025 Scaling Laws for Multilingual Language Models ACL 2025 Scaling Laws for Native Multimodal Models ICCV 2025 Scaling Laws for Precision ICLR 2025 Scaling Laws for Pre-training Agents and World Models ICML 2025 Scaling Laws for Synthetic Speech for Model Training Interspeech 2025 Scaling Laws for Task-Optimized Models of the Primate Visual Ventral Stream ICML 2025 Scaling Laws for Upcycling Mixture-of-Experts Language Models ICML 2025 Scaling LLMs’ Social Reasoning: Sprinkle Cognitive “Aha Moment” into Fundamental Long-thought Logical Capabilities ACL 2025 Scaling Optimal LR Across Token Horizons ICLR 2025 Scaling up Masked Diffusion Models on Text ICLR 2025 Scaling Wearable Foundation Models ICLR 2025