Papers by Delip Rao

3 papers
NSF-SciFy: Mining the NSF Awards Database for Scientific Claims (2026.acl-long)

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Challenge: NSF-SciFy contains 2.8 million claims from 400,000 abstracts spanning all science and mathematics disciplines.
Approach: They propose to use a dataset to extract scientific claims from National Science Foundation award abstracts and to use it to refine language models.
Outcome: The proposed method improves non-technical abstract generation, claim extraction, and investigation proposal extraction tasks while maintaining high precision and lower recall.
Probabilistic Soundness Guarantees in LLM Reasoning Chains (2025.emnlp-main)

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Challenge: Existing methods for detecting propagated errors in reasoning chains are inadequate . author et al. (2017) show that initial errors propagate and undermine reliability of final conclusion .
Approach: They propose a framework that evaluates each reasoning step based solely on previously-verified premises and provides certified statistical guarantees of its soundness.
Outcome: ARES achieves state-of-the-art performance across four benchmarks and demonstrates superior robustness on very long synthetic reasoning chains.
Learning Interpretable Style Embeddings via Prompting LLMs (2023.findings-emnlp)

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Challenge: Prior work has treated the style of a text as separable from the content.
Approach: They use prompting to perform stylometry on a large number of texts to generate a synthetic stylometric dataset.
Outcome: The proposed model trains human-interpretable representations on a large stylometric dataset and a linguistic model for style representation learning.

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