Papers by Hao Henry Wang

2 papers
ChartM3: A Multi-Stage Code-Driven Pipeline for Constructing Multi-Dimensional and Multi-Step Visual Reasoning Data in Chart Comprehension (2025.findings-emnlp)

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Challenge: Currently, research on complex chart understanding tasks is limited . a pipeline for visual reasoning datasets addresses these limitations .
Approach: They propose a code-driven pipeline for generating visual reasoning datasets . pipeline integrates retrieval-augmented generation to retrieve professional chart templates .
Outcome: The proposed pipeline enhances chart diversity and data quality through model-based evaluation.
RASD: Retrieval-Augmented Speculative Decoding (2025.findings-acl)

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Challenge: Existing methods for generating draft tokens rely on lightweight draft models or additional model structures to generate tokens and retrieve context from databases.
Approach: They propose to use a pruning method to enhance model-based speculative decoding by combining the best-fit model with the best retrieval tree.
Outcome: The proposed method achieves state-of-the-art inference acceleration across tasks such as DocQA, Summary, Code, and In-Domain QA.

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