---
title: "Mingyang Song · Broad Institute — author profile and papers"
description: "Mingyang Song, Broad Institute: 4 papers on Elamur Research (2025–2026), h-index 83 — affiliations, topics, co-authors and who cites them…"
canonical: "https://research.elamur.ai/free/en/authors/mingyang-song/"
---
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# Mingyang Song

Mingyang Song has 4 papers in our library, in 2025–2026, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/), [Machine translation](https://md.research.elamur.ai/free/en/topics/machine-translation/), [Evaluation & benchmarks](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/); often with [Mao Zheng](https://md.research.elamur.ai/free/en/authors/mao-zheng/), [Xuan Luo](https://md.research.elamur.ai/free/en/authors/xuan-luo/), [Zheng Li](https://md.research.elamur.ai/free/en/authors/zheng-li/).

4 papers in our library · 2025–2026

[OpenAlex](https://openalex.org/A5017604004) · [ORCID](https://orcid.org/0000-0002-1324-0316) · [Wikidata](https://www.wikidata.org/wiki/Q61307934) · [**h-index 83**](https://openalex.org/authors/A5017604004) · [957 works](https://openalex.org/works?filter=author.id:A5017604004) · [28,348 citations](https://openalex.org/works?filter=author.id:A5017604004&sort=cited_by_count:desc) OpenAlex, 2026-10-14

[📄 4 works in our library](https://md.research.elamur.ai/free/en/authors/mingyang-song/#papers) · [🔗 Cited 56 times in our library](https://md.research.elamur.ai/free/en/authors/mingyang-song/cited-by/) · [⭐ Paper Stars ranking: #7637](https://md.research.elamur.ai/free/en/paper-stars/page/77/#star-7637)

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

## Affiliations

[🎓**Harvard University** Cambridge · United States 2013–2026 · 474 papers*current*](https://md.research.elamur.ai/free/en/universities/harvard-university/) · [🏥**Massachusetts General Hospital** Boston · United States 2013–2026 · 393 papers*current*](https://md.research.elamur.ai/free/en/hospitals/massachusetts-general-hospital/) · [🏥**Brigham and Women's Hospital** Boston · United States 2013–2026 · 13 papers*current*](https://md.research.elamur.ai/free/en/hospitals/brigham-and-women-s-hospital/) · [🔬**Broad Institute** Cambridge · United States 2015–2026 · 12 papers*current*](https://md.research.elamur.ai/free/en/labs/broad-institute/) · [🔬**Dana-Farber Cancer Institute** Boston · United States 2013–2026 · 8 papers*current*](https://ror.org/02jzgtq86) · [🏥**Dana-Farber/Harvard Cancer Center** Boston · United States 2015–2026 · 4 papers*current*](https://ror.org/03pvyf116) · [🏥**Dana-Farber Brigham Cancer Center** Boston · United States 2026 · 1 paper*current*](https://ror.org/05rgrbr06) · [🎓**Fudan University** Shanghai · China 2026 · 1 paper*current*](https://md.research.elamur.ai/free/en/universities/fudan-university/) · [🎓**China Medical University** Shenyang · China 2019–2021 · 6 papers](https://ror.org/032d4f246) · [🎓**Liaoning University of Traditional Chinese Medicine** Shenyang · China 2021–2023 · 5 papers](https://ror.org/030e3n504)

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 34 more institutions 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/) · [Computer Vision and Pattern Recognition · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) · [Information Systems · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/information-systems/)

🧭 Topics 3 Research subjects and languages the work is about.[Language models & pretraining · 3 works](https://md.research.elamur.ai/free/en/topics/language-models/) · [Machine translation · 2 works](https://md.research.elamur.ai/free/en/topics/machine-translation/) · [Evaluation & benchmarks · 1 work](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/)

## Works by year

### 2020s

[**2026** 1 paper](https://md.research.elamur.ai/free/en/authors/mingyang-song/year/2026/) · [**2025** 3 papers](https://md.research.elamur.ai/free/en/authors/mingyang-song/year/2025/)

## Papers

The most cited first (OpenAlex and our library).

1. **[Counting-Stars: A Multi-evidence, Position-aware, and Scalable Benchmark for Evaluating Long-Context Large Language Models](https://md.research.elamur.ai/free/en/papers/song-2025-counting-stars-multi-evidence-position/)** *(2025 · 20 citations)* Popular long-context tests such as needle-in-a-haystack ask a model to find one inserted sentence. Recent LLMs score almost perfectly on them, so these tests no longer separate strong models from weak ones. The authors propose Counting-Stars, a benchmark that measures how well a model gathers many scattered pieces of…
2. **[Hunyuan-MT Technical Report](https://md.research.elamur.ai/free/en/papers/zheng-2025-hunyuan-mt-technical-report/)** *(2025 · 17 citations)* Open-source LLM translators still trail proprietary systems, and translation between Mandarin and China's minority languages gets little attention.
3. **[SSR-Zero: Simple Self-Rewarding Reinforcement Learning for Machine Translation](https://md.research.elamur.ai/free/en/papers/yang-2026-ssr-zero-simple-self-rewarding/)** *(2026 · 10 citations)* Most strong LLM-based machine translation (MT) systems depend on costly external supervision, such as human-made reference translations or trained reward models, and this limits how far they can scale.
4. **[Can Many-Shot In-Context Learning Help LLMs as Evaluators? A Preliminary Empirical Study](https://md.research.elamur.ai/free/en/papers/song-2025-can-many-shot-context-learning/)** *(2025 · 9 citations)* LLM judges are increasingly used to grade other models, but their scores can be unstable and skewed by hidden biases.

## Co-authors here

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

- [Mao Zheng](https://md.research.elamur.ai/free/en/authors/mao-zheng/) ×4
- [Xuan Luo](https://md.research.elamur.ai/free/en/authors/xuan-luo/) ×2
- [Zheng Li](https://md.research.elamur.ai/free/en/authors/zheng-li/) ×2
- [Di Wang](https://md.research.elamur.ai/free/en/authors/di-wang/)

## Venues

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

- [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/) ×2: [COLING 2025](https://md.research.elamur.ai/free/en/venues/coling/2025/) ×2
- [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/): [Findings of the Association for Computational Linguistics 2026](https://md.research.elamur.ai/free/en/venues/findings/2026/)

## Cited by

Papers of our library cite their works 56 times (of the 149,439 papers whose bibliographies we read); [18 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/mingyang-song/cited-by/).

Updated 30 October 2026
