awesome-language-model-analysis
A curated list of papers focusing on the theoretical analysis of large language models.
GraphCanon updated Sep 20, 2026 · GitHub synced Sep 20, 2026
55views this month
Decision brief
Curated List of Theoretical Papers on Large Language Models
Good fit when
- When you seek an in-depth theoretical understanding and formal/mathematical proofs related to the learning behavior and generalization ability of transformer-based large language models.
- If you are interested in research involving formal proofs, provable guarantees, bounds, expressivity results, convergence analysis specifically for transformer-based models.
Avoid when
- Avoid relying on this list if purely empirical or observational studies are more relevant to your needs as they are excluded from the repository.
- You should not use this resource if a comprehensive coverage of mechanistic engineering, probing, and interpretability is required, as these topics are currently less covered.
- Requirements:
- Some knowledge in theoretical computer science or mathematics is advised to fully comprehend the papers listed.; Python proficiency might be beneficial for implementing models based on theoretical findings.
Observed Jul 11, 2026 · Source: enrich:decision_facts
Verify the decision
Maintenance and security
Full trust report- Maintenance
- Steady (39d since push)
- As of Sep 6, 2026
- Provenance
- Not a fork · Personal account
- As of Sep 6, 2026
- Security (OSV)
- 5 low (5 low)
- As of Jul 11, 2026
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
pip install awesome-language-model-analysisSimilar tools
Same-category neighbours. No typed graph edges are catalogued for this tool yet.
Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
This repository contains a collection of 664 papers that focus on the theoretical and empirical analysis of transformer-based language models, emphasizing their properties such as learning behavior and generalization ability through formal/mathematical proofs, provable guarantees, bounds, expressivity results, convergence analysis. The list excludes purely empirical studies.
Capability facts
- Languages
- python
Source: github.language · Sep 6, 2026
Categories
Tags
README
Awesome Language Model Analysis This paper list focuses on the theoretical 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 form...
For agents
This page has a .md twin and JSON over the API.