TranNhiem Vietnamese Document-Image Reasoning with Chain-of-Thought

Vietnamese document-image understanding with explicit reasoning chains for multi-turn question-answering. The dataset is based on scanned or rendered Vietnamese document pages such as textbooks, articles, and worksheets. It was curated by Trần Nhiệm and the reasoning and answers were synthesized by the Qwen3.5-397B-A17B model over the Viet-Doc-VQA-II document collection.

Use Cases

• Train visual question answering models based on Vietnamese document images mentioned in the description.
• Benchmark chain-of-thought reasoning capabilities based on the step-by-step answer chains.
• Develop educational AI assistants based on the textbook and worksheet content.
• Fine-tune large language models for Vietnamese document comprehension based on the multi-turn QA format.

Strengths

• Includes explicit step-by-step chain-of-thought reasoning for each answer.
• Focuses on Vietnamese document understanding, a less common language in multimodal datasets.
• Based on a specific document collection (Viet-Doc-VQA-II) for grounding.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Last updated 2026-07-17 06:24:26; freshness should be verified.

Provenance

Source

huggingface

Collection Method

Synthesized by Qwen3.5-397B-A17B model over the Viet-Doc-VQA-II document collection.

Freshness

Last updated 2026-07-17 06:24:26.