Papers with direct mapping

3 papers
Using Intermediate Representations to Solve Math Word Problems (P18-1)

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Challenge: Existing approaches to solving math word problems do not include higher-order operations that cannot be explicitly represented in equations.
Approach: They propose an iterative labeling framework that generates intermediate forms and executes them to obtain the final answers.
Outcome: The proposed model outperforms existing models in solving math word problems.
Rethinking-based Code Summarization with Chain of Comments (2025.coling-main)

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Challenge: Existing methods focus on learning a direct mapping from pure code to summaries, overlooking the heterogeneity gap between code and summary.
Approach: They propose a framework that uses chain of comments as auxiliary intermediate information to bridge the gap between code and summaries.
Outcome: The proposed framework outperforms baseline models and multiple code Large Language Models by a large margin.
Beyond Query Memorization: Large Language Model Routing with Query Decomposition and Historical Matching (2026.acl-long)

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Challenge: Existing routing methods rely on direct mapping from queries to models based on surface-level features, leading to poor generalizability on out-of-distribution data.
Approach: They propose a new routing framework that recasts the routing task as a matching process of sifting similar queries from historical logs.
Outcome: The proposed framework improves matching accuracy while lowering inference costs . it decouples linguistic surface forms from task-intrinsic requirements .

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