---
title: "Haibin Chen · Alibaba Group — author profile and papers"
description: "Haibin Chen, Alibaba Group: 4 papers on Elamur Research (2026), h-index 0 — affiliations, topics, co-authors and who cites them in our library."
canonical: "https://research.elamur.ai/free/en/authors/haibin-chen/"
---
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# Haibin Chen

Haibin Chen has 4 papers in our library, in 2026, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/); often with [Bo Zheng](https://md.research.elamur.ai/free/en/authors/bo-zheng/), [Langming Liu](https://md.research.elamur.ai/free/en/authors/langming-liu/), [Shilei Liu](https://md.research.elamur.ai/free/en/authors/shilei-liu/).

4 papers in our library · 2026

[OpenAlex](https://openalex.org/A5139785102) · [**h-index 0**](https://openalex.org/authors/A5139785102) · [4 works](https://openalex.org/works?filter=author.id:A5139785102) · [0 citations](https://openalex.org/works?filter=author.id:A5139785102&sort=cited_by_count:desc) OpenAlex, 2026-10-14

[📄 4 works in our library](https://md.research.elamur.ai/free/en/authors/haibin-chen/#papers) · [⭐ Paper Stars ranking: #13275](https://md.research.elamur.ai/free/en/paper-stars/page/133/#star-13275)

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

## Affiliations

[🏢**Alibaba Group** San Mateo · United States 2026 · 4 papers*current*](https://md.research.elamur.ai/free/en/companies/alibaba-group-united-states/) · [🏢**Alibaba Group** Hangzhou · China 2026 · 4 papers*current*](https://md.research.elamur.ai/free/en/companies/alibaba-group/)

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine.

## 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).[Artificial Intelligence · 4 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [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/) · [Language and Linguistics · 4 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) · [Computer Vision and Pattern Recognition · 2 works](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 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

[**2026** 4 papers](https://md.research.elamur.ai/free/en/authors/haibin-chen/year/2026/)

## Papers

The most cited first (OpenAlex and our library).

1. **[CoMeT: Collaborative Memory Transformer for Efficient Long Context Modeling](https://md.research.elamur.ai/free/en/papers/zhao-2026-comet-collaborative-memory-transformer-efficient/)** *(2026)* Standard Transformers struggle with very long inputs because attention cost grows quadratically and the KV cache keeps expanding.
2. **[PretrainRL: Alleviating Factuality Hallucination of Large Language Models at the Beginning](https://md.research.elamur.ai/free/en/papers/liu-2026-pretrainrl-alleviating-factuality-hallucination-large/)** *(2026)* The paper addresses factual hallucinations in LLMs, meaning confident statements that can be checked and shown false.
3. **[Read As Human: Compressing Context via Parallelizable Close Reading and Skimming](https://md.research.elamur.ai/free/en/papers/tang-2026-read-as-human-compressing-context/)** *(2026)* Long prompts, such as those produced by retrieval-augmented generation, make LLM inference slow because attention cost grows quadratically.
4. **[SELECting over Tokens: Curating Pre-training Data at Scale via Token Classification](https://md.research.elamur.ai/free/en/papers/tong-2026-selecting-over-tokens-curating-pre/)** *(2026)* Web-scraped pre-training corpora contain a lot of boilerplate and noise. Standard cleaning pipelines use document-level heuristics that can only keep or drop whole pages. Generative token-level refiners such as ProX-C are finer-grained but slow at scale and may hallucinate edits. The authors propose SelecT, which…

## Co-authors here

12 of 18 co-authors with a page, the most papers together first.

- [Bo Zheng](https://md.research.elamur.ai/free/en/authors/bo-zheng/) ×4
- [Langming Liu](https://md.research.elamur.ai/free/en/authors/langming-liu/) ×4
- [Shilei Liu](https://md.research.elamur.ai/free/en/authors/shilei-liu/) ×4
- [Wenbo Su](https://md.research.elamur.ai/free/en/authors/wenbo-su/) ×4
- [Yujin Yuan](https://md.research.elamur.ai/free/en/authors/yujin-yuan/) ×4
- [Weidong Zhang](https://md.research.elamur.ai/free/en/authors/weidong-zhang/) ×3
- [Jiwei Tang](https://md.research.elamur.ai/free/en/authors/jiwei-tang/) ×2
- [Kangtao Lv](https://md.research.elamur.ai/free/en/authors/kangtao-lv/) ×2
- [Runsong Zhao](https://md.research.elamur.ai/free/en/authors/runsong-zhao/) ×2
- [Xin Tong](https://md.research.elamur.ai/free/en/authors/xin-tong/) ×2
- [Hai-Tao Zheng](https://md.research.elamur.ai/free/en/authors/hai-tao-zheng/)
- [Jiaang Li](https://md.research.elamur.ai/free/en/authors/jiaang-li/)

## Venues

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

- [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/) ×3: [ACL 2026](https://md.research.elamur.ai/free/en/venues/acl/2026/) ×3
- [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/)

Updated 2 November 2026
