# Llm training

`kaal:entity:llm-training`

**Status.** derived

This node is assembled mechanically from the 2 claims that carry the concept tag `llm-training`. It is a roster of what the corpus says under this term. It is **not** an adjudicated definition: no single statement here has been ruled canonical, and no first-appearance call has been made. Read the claims and judge for yourself.

## Every claim under this term

2 claims across 1 works, 2024 to 2024.

**2024**

- [4755632-002](https://wulfkaal.github.io/claims/4755632-002) [failure/argued] *(failure mode)* -- Transformer neural network architecture removes the scale constraint on training data but not the quality constraint, so data quality continues to be a major unsolved issue for large language models even where internet scale corpora are available.
  > data quality continues to be a huge issue for LLMs
  Wulf A. Kaal, AI Learning - Decentralized Governance to Optimize Human Output Datasets for AI Learning (2024). SSRN: https://ssrn.com/abstract=4755632
- [4755632-003](https://wulfkaal.github.io/claims/4755632-003) [failure/argued] *(failure mode)* -- The move by AI developers toward smaller training datasets raises the risk of overfitting, especially with complex models, which forces LLM developers to rely on regularization to counteract overfitting of the model to the training data.
  > However, with small datasets in LLMs, the risk of overfitting also rises, especially with complex models. Therefore, LLM developers have to turn to regularization in an effort to address overfitting of the model with the training data.
  Wulf A. Kaal, AI Learning - Decentralized Governance to Optimize Human Output Datasets for AI Learning (2024). SSRN: https://ssrn.com/abstract=4755632

## Verify

Every claim above resolves to a record carrying a verbatim source quote, the sha256 of the source PDF, and a preformatted citation. Nothing here asks to be taken on trust.

    curl -s https://wulfkaal.github.io/entities/llm-training.md | sha256sum

**Canonical form.** This markdown file is the canonical hashed representation of this entity node. Its sha256 is the content hash.