awesome-language-model-analysis

github.com/furyton/awesome-language-model-analysis ↗

This paper list focuses on the theoretical and empirical analysis of language models, especially large language models (LLMs). The papers in this list investigate the learning behavior, generalization ability, and other properties of language models through theoretical analysis, empirical analysis, or a combination of both.

100

GitHub Stars

589

Curated Resources

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Add the Context Awesome MCP server to Claude, Cursor, or any MCP client, then ask:

"Show me learning / generalization / reasoning / weak to strong generalization resources from awesome-language-model-analysis"

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What's inside

Miscellanea

Phenomena of Interest

[paper link]Learning / Generalization / Reasoning / Weak to Strong Generalization
[paper link]Learning / Generalization / Reasoning / Weak to Strong Generalization
[paper link]Learning / Generalization / Reasoning / Weak to Strong Generalization
[paper link]Training Dynamics / Landscape / Optimization / Fine-tuning / etc.
[paper link]Scaling Laws / Emergent Abilities / Grokking / etc.
[paper link]Training Dynamics / Landscape / Optimization / Fine-tuning / etc.

Mechanistic Engineering / Probing / Interpretability

Representational Capacity

[paper link]What Can Transformer Do? / Properties of Transformer
[paper link]What Can Transformer Do? / Properties of Transformer
[paper link]What Can Transformer Not Do? / Limitation of Transformer
[paper link]What Can Transformer Not Do? / Limitation of Transformer
[paper link]What Can Transformer Not Do? / Limitation of Transformer
[paper link]What Can Transformer Not Do? / Limitation of Transformer

Architectural Effectivity

[paper link]Tokenization / Embedding

Showing a sample of 589 resources. View the full list on GitHub →