---
title: "Rulin Shao · Princeton University — author profile and papers"
description: "Rulin Shao, Princeton University: 4 papers on Elamur Research (2024–2025), h-index 9 — affiliations, topics, co-authors and who cites them…"
canonical: "https://research.elamur.ai/free/en/authors/rulin-shao/"
---
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# Rulin Shao

Rulin Shao has 4 papers in our library, in 2024–2025, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/), [Information retrieval & search](https://md.research.elamur.ai/free/en/topics/information-retrieval/); often with [Akari Asai](https://md.research.elamur.ai/free/en/authors/akari-asai/), [Rui Xin](https://md.research.elamur.ai/free/en/authors/rui-xin/), [Sewon Min](https://md.research.elamur.ai/free/en/authors/sewon-min/).

4 papers in our library · 2024–2025

[OpenAlex](https://openalex.org/A5047742348) · [ORCID](https://orcid.org/0000-0002-8228-2106) · [Wikidata](https://www.wikidata.org/wiki/Q104555738) · [**h-index 9**](https://openalex.org/authors/A5047742348) · [47 works](https://openalex.org/works?filter=author.id:A5047742348) · [276 citations](https://openalex.org/works?filter=author.id:A5047742348&sort=cited_by_count:desc) OpenAlex, 2026-10-14

[📄 4 works in our library](https://md.research.elamur.ai/free/en/authors/rulin-shao/#papers) · [🔗 Cited 590 times in our library](https://md.research.elamur.ai/free/en/authors/rulin-shao/cited-by/) · [10 more in our library without a page yet](#also) · [⭐ Paper Stars ranking: #6591](https://md.research.elamur.ai/free/en/paper-stars/page/66/#star-6591)

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

Elsewhere: [Google Scholar](https://scholar.google.com/citations?view_op=search_authors&mauthors=Rulin+Shao) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Rulin+Shao) · [dblp](https://dblp.org/search?q=Rulin+Shao) · [ACL Anthology](https://aclanthology.org/search/?q=Rulin+Shao)

## Affiliations

[🎓**University of Washington** Seattle · United States 2023–2026 · 22 papers*current*](https://md.research.elamur.ai/free/en/universities/university-of-washington/) · [🎓**Carnegie Mellon University** Pittsburgh · United States 2021–2026 · 7 papers*current*](https://md.research.elamur.ai/free/en/universities/carnegie-mellon-university/) · [🔬**Allen Institute for Artificial Intelligence** Seattle · United States 2025–2026 · 2 papers*current*](https://md.research.elamur.ai/free/en/labs/allen-institute-for-artificial-intelligence/) · [🎓**Stanford University** Stanford · United States 2025–2026 · 2 papers*current*](https://md.research.elamur.ai/free/en/universities/stanford-university/) · [🎓**Princeton University** Princeton · United States 2026 · 1 paper*current*](https://md.research.elamur.ai/free/en/universities/princeton-university/) · [🎓**University of California San Diego** San Diego · United States 2026 · 1 paper*current*](https://md.research.elamur.ai/free/en/universities/university-of-california-san-diego/) · [🎓**Xi'an Jiaotong University** Xi'an · China 2019–2020 · 2 papers](https://md.research.elamur.ai/free/en/universities/xi-an-jiaotong-university/)

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 1 more institution on single bylines are not listed.

## Fields, topics and concepts

Of its works in our library, with the number of works on each.

📚 Shelves 6 The field of science this work belongs to (OpenAlex fields).[Arts and Humanities · 4 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Computer Science · 4 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Artificial Intelligence · 4 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Language and Linguistics · 4 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) · [Information Systems · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/information-systems/) · [Computer Vision and Pattern Recognition · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/)

🧭 Topics 2 Research subjects and languages the work is about.[Information retrieval & search · 1 work](https://md.research.elamur.ai/free/en/topics/information-retrieval/) · [Language models & pretraining · 1 work](https://md.research.elamur.ai/free/en/topics/language-models/)

## Works by year

### 2020s

[**2025** 2 papers](https://md.research.elamur.ai/free/en/authors/rulin-shao/year/2025/) · [**2024** 2 papers](https://md.research.elamur.ai/free/en/authors/rulin-shao/year/2024/)

## Papers

The most cited first (OpenAlex and our library).

1. **[OpenScholar: Synthesizing Scientific Literature with Retrieval-augmented LMs](https://md.research.elamur.ai/free/en/papers/asai-2024-openscholar-synthesizing-scientific-literature/)** *(2024 · 62 citations)* Large language models often fail researchers who need to digest scientific literature. They invent references, rely on outdated pre-training knowledge, and seldom show the sources behind their claims. OpenScholar addresses this with a fully open retrieval-augmented system built on OpenScholar-DataStore (OSDS), an…
2. **[Spurious Rewards: Rethinking Training Signals in RLVR](https://md.research.elamur.ai/free/en/papers/shao-2025-spurious-rewards-rethinking-training-signals/)** *(2025 · 53 citations)* Reinforcement learning with verifiable rewards (RLVR) is credited with improving math reasoning in language models, but it is unclear what in the training signal actually causes the gains.
3. **[Language models scale reliably with over-training and on downstream tasks](https://md.research.elamur.ai/free/en/papers/gadre-2024-language-models-scale-reliably-over/)** *(2024 · 46 citations)* Scaling laws let teams forecast large language model behaviour from cheap small runs. Most published laws, however, assume Chinchilla-style compute-optimal training and predict only next-token loss. In practice, smaller models are often over-trained on far more tokens to cut inference cost, and they are compared on…
4. **[DR Tulu: Reinforcement Learning with Evolving Rubrics for Deep Research](https://md.research.elamur.ai/free/en/papers/shao-2025-dr-tulu-reinforcement-learning-evolving/)** *(2025 · 28 citations)* Open deep research (DR) agents are usually trained with reinforcement learning on short questions whose answers can be checked automatically. That kind of reward does not transfer to open-ended, long-form reports, where quality is loosely defined and checking claims requires current external evidence.

## All works

14 works of theirs in our library, the most cited first; 4 with a page here, the others link their original until we summarise them.

1. [**OpenScholar: Synthesizing Scientific Literature with Retrieval-augmented LMs arXiv:2411.14199**Akari Asai, Jacqueline He, Rulin Shao, et al.*2024 · 62 citations*](https://md.research.elamur.ai/free/en/papers/asai-2024-openscholar-synthesizing-scientific-literature/)
2. [**Spurious Rewards: Rethinking Training Signals in RLVR arXiv:2506.10947**Rulin Shao, Shuyue Stella Li, Rui Xin, et al.*2025 · 53 citations*](https://md.research.elamur.ai/free/en/papers/shao-2025-spurious-rewards-rethinking-training-signals/)
3. [**Language models scale reliably with over-training and on downstream tasks arXiv:2403.08540**Samir Yitzhak Gadre, Georgios Smyrnis, Vaishaal Shankar, et al.*2024 · 46 citations*](https://md.research.elamur.ai/free/en/papers/gadre-2024-language-models-scale-reliably-over/)
4. **[Synthesizing scientific literature with retrieval-augmented language models ↗](https://doi.org/10.1038/s41586-025-10072-4) Nature · no summary yet**Akari Asai et al.*2026 · 42 citations*
5. **[ReasonIR: Training Retrievers for Reasoning Tasks ↗](https://arxiv.org/abs/2504.20595) arXiv (Cornell University) · no summary yet**Rulin Shao et al.*2025 · 41 citations*
6. **[DISTFLASHATTN: Distributed Memory-efficient Attention for Long-context LLMs Training ↗](https://arxiv.org/abs/2310.03294) arXiv:2310.03294 · no summary yet**Dacheng Li et al.*2023 · 36 citations*
7. **[Scaling Retrieval-Based Language Models with a Trillion-Token Datastore ↗](https://doi.org/10.52202/079017-2896) neural information processing systems · no summary yet**Rulin Shao et al.*2024 · 30 citations*
8. [**DR Tulu: Reinforcement Learning with Evolving Rubrics for Deep Research arXiv:2511.19399**Rulin Shao, Akari Asai, Shannon Zejiang Shen, et al.*2025 · 28 citations*](https://md.research.elamur.ai/free/en/papers/shao-2025-dr-tulu-reinforcement-learning-evolving/)
9. **[Cross-modal Attention Congruence Regularization for Vision-Language Relation Alignment ↗](https://aclanthology.org/2023.acl-long.298/) Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yet**Rohan Pandey et al.*2023 · 11 citations*
10. **[Improving Factuality with Explicit Working Memory ↗](https://aclanthology.org/2025.acl-long.548/) Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yet**Mingda Chen et al.*2025 · 4 citations*
11. **[JobBench: Aligning Agent Work With Human Will ↗](https://arxiv.org/abs/2605.26329) arXiv (Cornell University) · no summary yet**Yuetai Li et al.*2026 · 1 citation*
12. **[ScholarCatalyst: A Benchmark for Retrieving Papers That Inspire New Research ↗](https://arxiv.org/abs/2610.02202) arXiv (Cornell University) · no summary yet**Sohyeon Kim et al.*2026*
13. **[Context Language Models ↗](https://arxiv.org/abs/2609.37725) arXiv (Cornell University) · no summary yet**Rulin Shao et al.*2026*
14. **[Efficient Test-Time Adaptation through Human-AI Interaction ↗](https://arxiv.org/abs/2609.04141) arXiv (Cornell University) · no summary yet**Zora Zhiruo Wang et al.*2026*

## Co-authors here

12 of 32 co-authors with a page, the most papers together first.

- [Akari Asai](https://md.research.elamur.ai/free/en/authors/akari-asai/) ×2
- [Rui Xin](https://md.research.elamur.ai/free/en/authors/rui-xin/) ×2
- [Sewon Min](https://md.research.elamur.ai/free/en/authors/sewon-min/) ×2
- [Alex Fang](https://md.research.elamur.ai/free/en/authors/alex-fang/)
- [Amanpreet Singh](https://md.research.elamur.ai/free/en/authors/amanpreet-singh/)
- [David Sontag](https://md.research.elamur.ai/free/en/authors/david-sontag/)
- [David Wadden](https://md.research.elamur.ai/free/en/authors/david-wadden/)
- [Georgios Smyrnis](https://md.research.elamur.ai/free/en/authors/georgios-smyrnis/)
- [Hamish Ivison](https://md.research.elamur.ai/free/en/authors/hamish-ivison/)
- [Hannaneh Hajishirzi](https://md.research.elamur.ai/free/en/authors/hannaneh-hajishirzi/)
- [Jean Mercat](https://md.research.elamur.ai/free/en/authors/jean-mercat/)
- [Jeffrey Li](https://md.research.elamur.ai/free/en/authors/jeffrey-li/)

## Venues

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

- Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) ×2
- [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)
- Nature
- neural information processing systems

## Cited by

Papers of our library cite their works 590 times (of the 149,439 papers whose bibliographies we read); [147 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/rulin-shao/cited-by/).

Updated 2 November 2026