AdditiveLLM2-OA: Open Access Journal Articles for LLM Domain Adaptation

Open Access journal articles up to February 2026 used for domain-adaptive pretraining and instruction tuning of the AdditiveLLM2 model. The dataset includes text and images, and is split by source journal. It was created by ppak10 and last updated on March 25, 2026.

Use Cases

• Domain-adaptive pretraining of language models based on journal article text.
• Instruction tuning for specialized LLMs based on the described article content.
• Analyzing vocabulary overlap and phrase frequency across different scientific journals.
• Training multimodal models using the described combination of text and image data.

Strengths

• Includes articles up to February 2026, suggesting recent content.
• Contains both text and image modalities for multimodal applications.
• Provides analysis of vocabulary overlap across four source journals.

Limitations

• Row count, column definitions, and file formats are unknown, limiting suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• License information is unknown, which may restrict usage.

Provenance

Source

Open Access journal articles aggregated from four source journals.

Collection Method

Used for domain adapting pretraining and instruction tuning; likely gathered via web scraping or API.

Time Range

Articles up to February 2026.

Freshness

Last updated 2026-03-25 13:38:07

Geography

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