---
title: "Shengnan An — author profile and papers — Elamur Research"
description: "Shengnan An: 2 papers on Elamur Research (2023–2024), h-index 5 — affiliations, topics, co-authors and who cites them in our library."
canonical: "https://research.elamur.ai/free/en/authors/shengnan-an/"
---
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# Shengnan An

Shengnan An has 2 papers in our library, in 2023–2024, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/); often with [Jian-Guang Lou](https://md.research.elamur.ai/free/en/authors/jian-guang-lou/), [Nanning Zheng](https://md.research.elamur.ai/free/en/authors/nanning-zheng/), [Zeqi Lin](https://md.research.elamur.ai/free/en/authors/zeqi-lin/).

2 papers in our library · 2023–2024

[OpenAlex](https://openalex.org/A5027673336) · [ORCID](https://orcid.org/0009-0003-4989-4607) · [Wikidata](https://www.wikidata.org/wiki/Q130844950) · [**h-index 5**](https://openalex.org/authors/A5027673336) · [11 works](https://openalex.org/works?filter=author.id:A5027673336) · [104 citations](https://openalex.org/works?filter=author.id:A5027673336&sort=cited_by_count:desc) OpenAlex, 2026-10-14

[📄 2 works in our library](https://md.research.elamur.ai/free/en/authors/shengnan-an/#papers) · [🔗 Cited 105 times in our library](https://md.research.elamur.ai/free/en/authors/shengnan-an/cited-by/) · [⭐ Paper Stars ranking: #6953](https://md.research.elamur.ai/free/en/paper-stars/page/70/#star-6953)

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=Shengnan+An) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Shengnan+An) · [dblp](https://dblp.org/search?q=Shengnan+An) · [ACL Anthology](https://aclanthology.org/search/?q=Shengnan+An)

## Affiliations

[🎓**Xi'an Jiaotong University** Xi'an · China 2022–2024 · 4 papers](https://md.research.elamur.ai/free/en/universities/xi-an-jiaotong-university/) · [🏢**Microsoft** Redmond · United States 2023–2024 · 2 papers](https://md.research.elamur.ai/free/en/companies/microsoft/)

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

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

## Works by year

### 2020s

[**2024** 1 paper](https://md.research.elamur.ai/free/en/authors/shengnan-an/year/2024/) · [**2023** 1 paper](https://md.research.elamur.ai/free/en/authors/shengnan-an/year/2023/)

## Papers

The most cited first (OpenAlex and our library).

1. **[Make Your LLM Fully Utilize the Context](https://md.research.elamur.ai/free/en/papers/an-2024-make-llm-fully-utilize-context/)** *(2024 · 97 citations)* Long-context LLMs can accept tens of thousands of tokens, yet they often miss facts located in the middle of the input.
2. **[Learning From Mistakes Makes LLM Better Reasoner](https://md.research.elamur.ai/free/en/papers/an-2023-learning-mistakes-makes-llm-better/)** *(2023 · 64 citations)* Open-source LLMs such as LLaMA-2 still lag behind proprietary systems on multi-step math reasoning. They are usually improved by fine-tuning on question–rationale pairs (CoT data). This paper proposes LEMA (LEarning from MistAkes), which borrows the way students learn from their own errors. Several LLaMA and GPT…

## Co-authors here

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

- [Jian-Guang Lou](https://md.research.elamur.ai/free/en/authors/jian-guang-lou/) ×2
- [Nanning Zheng](https://md.research.elamur.ai/free/en/authors/nanning-zheng/) ×2
- [Zeqi Lin](https://md.research.elamur.ai/free/en/authors/zeqi-lin/) ×2
- [Zexiong Ma](https://md.research.elamur.ai/free/en/authors/zexiong-ma/) ×2
- [Weizhu Chen](https://md.research.elamur.ai/free/en/authors/weizhu-chen/)

## Venues

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

- [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/): [NeurIPS 2024](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/2024/)

## Cited by

Papers of our library cite their works 105 times (of the 149,439 papers whose bibliographies we read); [39 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/shengnan-an/cited-by/).

Updated 2 November 2026
