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Intent-aware Schema Generation and Refinement for Literature Review Tables

Padmakumar, Vishakh, Chang, Joseph Chee, Lo, Kyle, Downey, Doug, Naik, Aakanksha·2025·Findings of the Association for Computational Linguistics: EMNLP 2025
DOI 10.18653/v1/2025.findings-emnlp.1274
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Figure 1 We benchmark the abilities of LLMs to perform schema generation for literature review tables given a table intent or information need (§2) via prompting and fine-tuning (§3) as well as editing existing schema candidates (§4).
Figure 1 We benchmark the abilities of LLMs to perform schema generation for literature review tables given a table intent or information need (§2) via prompting and fine-tuning (§3) as well as editing existing schema candidates (§4).CC-BY · From the PDF
Figure 2 While Candidate 1 is a valid schema to compare the research papers, incorporating a table intent yields Candidate 2 , which better aligns with the user-written reference reflecting their actual information need. (§2)
Figure 2 While Candidate 1 is a valid schema to compare the research papers, incorporating a table intent yields Candidate 2 , which better aligns with the user-written reference reflecting their actual information need. (§2)CC-BY · From the PDF
Figure 3 Overview of editing techniques proposed to refine schemas in §4.
Figure 3 Overview of editing techniques proposed to refine schemas in §4.CC-BY · From the PDF
Image 4
CC-BY · From the PDF

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Authors
Padmakumar, V., Chang, J. C., Lo, K., Downey, D., & Naik, A.
Venue
Findings of the Association for Computational Linguistics: EMNLP 2025
Publisher
Association for Computational Linguistics
Published
2025
Pages
23450-23472
DOI
10.18653/v1/2025.findings-emnlp.1274
Cited by
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Padmakumar, V., Chang, J. C., Lo, K., Downey, D., & Naik, A. (2025). Intent-aware Schema Generation and Refinement for Literature Review Tables. Findings of the Association for Computational Linguistics: EMNLP 2025. https://doi.org/10.18653/v1/2025.findings-emnlp.1274