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Notes on optimization techniques

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Less Experts, Faster Decoding: Cost-Aware Speculative Decoding for Mixture-of-Experts
Source note · Jul 14, 2026 · large language models, speculative decoding
Researchers propose a new method called EcoSpec for optimizing the performance of Large Language Models (LLMs) using Sparse Mixture-of-Experts (MoE). This method aims to improve decoding speed by considering the cost…
CausalMix: Data Mixture as Causal Inference for Language Model Training
Source note · Jul 1, 2026 · language model training, causal inference
The paper presents CausalMix, a method that addresses the limitation of existing data mixing methods in Large Language Model (LLM) training by casting it as a causal inference problem. By using causal modeling to…

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Notes on optimization techniques

Less Experts, Faster Decoding: Cost-Aware Speculative Decoding for Mixture-of-Experts

CausalMix: Data Mixture as Causal Inference for Language Model Training