Papers by Ruofei Bai

2 papers
RoadMapper: A Multi-Agent System for Roadmap Generation of Solving Complex Research Problems (2026.findings-acl)

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Challenge: Existing tools to generate structured content for research tasks are limited in their ability to generate high-quality roadmaps.
Approach: They propose a benchmark to evaluate the ability of large language models (LLMs) to generate high-quality roadmaps for solving complex research problems.
Outcome: The proposed system can improve LLMs’ ability for roadmap generation while saving 84% of the time required by human experts.
Enhancing Self-Attention with Knowledge-Assisted Attention Maps (2022.naacl-main)

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Challenge: Existing works of knowledge infusion depend on multi-task learning frameworks, which are inefficient and require large-scale retraining when new knowledge is considered.
Approach: They propose a method which integrates knowledge-generated attention maps into the self-attention mechanism and integrates it into the model.
Outcome: The proposed model outperforms existing methods on academic datasets and industry-scale ad relevance applications.

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