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Aidan Swope

Aidan Swope has 2 papers in our library, in 2023–2024, most of them on Language models & pretraining, Reasoning, Information retrieval & search; often with Alex Gu, Anima Anandkumar, Jiaqi Zeng.

2 papers in our library · 2023–2024

OpenAlex · ORCID · h-index 3 · 6 works · 80 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 274 citations in our library · 1 more in our library without a page yet · ⭐ Paper Star rank #4111

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

 Affiliations

🏢HarmonicPalo Alto · United States2024–2026 · 2 paperscurrent

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 2 more institutions on single bylines are not listed.

 Concepts, shelves and topics

Of its works in our library: the number of works on each and its rating among them.

📚 Shelves 7 Arts and Humanities · 2 works Computer Science · 2 works Artificial Intelligence · 2 works Language and Linguistics · 2 works Computational Theory and Mathematics · 1 work Mathematics · 1 work Information Systems · 1 work

🧭 Topics 3 Information retrieval & search · 1 work Language models & pretraining · 1 work Reasoning · 1 work

 Works by year

2020s

20241 paper20231 paper

 Papers

The most cited first (OpenAlex and our library).

  1. LeanDojo: Theorem Proving with Retrieval-Augmented Language Models (2023 · 248 citations)
    Research on machine learning for formal theorem proving has been hard to reproduce and build on. Earlier LLM-based provers kept their code and training data private, and some needed thousands of GPU-days of compute. The authors respond with LeanDojo, an open toolkit for the Lean proof assistant. It uses Lean 3 by…
  2. HelpSteer: Multi-attribute Helpfulness Dataset for SteerLM (2024 · 69 citations)
    Open helpfulness preference datasets usually give only an overall rating or a pairwise ranking. They do not say why one answer is better, so trained models can pick up shallow cues, such as preferring longer replies whether or not they are useful. The NVIDIA team built HelpSteer to address this. It is a…

All works

3 works of theirs in our library, the most cited first; 2 with a page here, the others link their original until we summarise them.

  1. LeanDojo: Theorem Proving with Retrieval-Augmented Language ModelsKaiyu Yang, Aidan M. Swope, Alex Gu, et al.Conference on Neural Information Processing… · 248 citations
  2. HelpSteer: Multi-attribute Helpfulness Dataset for SteerLMZhilin Wang, Yi Dong, Jiaqi Zeng, et al.Conference of the North American Chapter of the… · 69 citations
  3. Aristotle: IMO-level Automated Theorem Proving (original ↗)Tudor Achim et al.2025 · arXiv:2510.01346 · 28 citations · no summary yet

 Co-authors here

8 co-authors with a page, the most papers together first.

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

 Cited by

Papers of our library cite their works 274 times (of the 141,840 papers whose bibliographies we read); 17 citing papers with a page here →.

Updated

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