Papers with rule-based algorithms
Generating OpenAPI Specifications from Online API Documentation with Large Language Models (2025.acl-industry)
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Koren Lazar, Matan Vetzler, Kiran Kate, Jason Tsay, David Boaz, Himanshu Gupta, Avraham Shinnar, Rohith D Vallam, David Amid, Esther Goldbraich, Jim Laredo, Ateret Anaby Tavor
| Challenge: | API specifications are often presented as unstructured HTML pages, requiring external users to manually convert it into a structured format. |
| Approach: | They propose a framework that transforms long API documentation pages into consistent, machine-readable API specifications. |
| Outcome: | The proposed framework generalizes well across hundreds of APIs and produces valid OpenAPI specifications that encapsulate most of the information from the original documentation. |
PDFdigest: an Adaptable Layout-Aware PDF-to-XML Textual Content Extractor for Scientific Articles (L18-1)
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| Challenge: | Existing tools to extract structured textual content from PDFs are essential to enable scientific text mining. |
| Approach: | They propose a PDF-to-XML textual content extraction tool that extracts structured textual contents from scientific articles in PDF format. |
| Outcome: | The proposed tool extracts structured textual content from scientific articles in PDF format while preserving both the textual contents and layout details of the input PDF document. |
Constrained Language Models for Interactive Poem Generation (2022.lrec-1)
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Andrei Popescu-Belis, Àlex Atrio, Valentin Minder, Aris Xanthos, Gabriel Luthier, Simon Mattei, Antonio Rodriguez
| Challenge: | Neural language models cannot learn constraints from data, which is scarce for a well-resourced language such as French. |
| Approach: | They propose a system that combines neural language models with constraints that can be set by users on form, topic, emotion, and rhyming scheme. |
| Outcome: | The proposed system generates poems and stanzas using LMs and rule-based algorithms . it has been demonstrated at public events and log analysis shows that users found it engaging . |
GAMEBoT: Transparent Assessment of LLM Reasoning in Games (2025.acl-long)
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| Challenge: | Existing efforts to create benchmarks that move beyond superficial pattern recognition to delve into the profound reasoning skills required for problemsolving face challenges such as insufficient interpretability, performance saturation or data contamination. |
| Approach: | They propose a gaming arena designed for rigorous assessment of LLM reasoning capabilities. |
| Outcome: | The proposed framework decomposes complex reasoning into predefined modular subproblems and generates ground truth for these subproblem types. |