---
title: "Shengjie Zhao · Tongji University — author profile and papers"
description: "Shengjie Zhao, Tongji University: 2 papers on Elamur Research (2026), h-index 2 — affiliations, topics, co-authors and who cites them in our library."
canonical: "https://research.elamur.ai/free/en/authors/shengjie-zhao/"
---
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# Shengjie Zhao

Shengjie Zhao has 2 papers in our library, in 2026, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/), [Reasoning](https://md.research.elamur.ai/free/en/topics/reasoning/), [Bias, fairness & safety](https://md.research.elamur.ai/free/en/topics/bias-fairness-safety/); often with [Wei Wang](https://md.research.elamur.ai/free/en/authors/wei-wang/), [Yu Wang](https://md.research.elamur.ai/free/en/authors/yu-wang/).

2 papers in our library · 2026

[OpenAlex](https://openalex.org/A5125716308) · [ORCID](https://orcid.org/0000-0002-4301-394X) · [Wikidata](https://www.wikidata.org/wiki/Q130825817) · [**h-index 2**](https://openalex.org/authors/A5125716308) · [24 works](https://openalex.org/works?filter=author.id:A5125716308) · [12 citations](https://openalex.org/works?filter=author.id:A5125716308&sort=cited_by_count:desc) OpenAlex, 2026-10-14

[📄 2 works in our library](https://md.research.elamur.ai/free/en/authors/shengjie-zhao/#papers) · [⭐ Paper Stars ranking: #13903](https://md.research.elamur.ai/free/en/paper-stars/page/140/#star-13903)

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

## Affiliations

[🎓**Tongji University** Shanghai · China 2025–2026 · 22 papers*current*](https://md.research.elamur.ai/free/en/universities/tongji-university/)

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 4 The field of science this work belongs to (OpenAlex fields).[Artificial Intelligence · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [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/) · [Language and Linguistics · 2 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/)

🧭 Topics 3 Research subjects and languages the work is about.[Bias, fairness & safety · 1 work](https://md.research.elamur.ai/free/en/topics/bias-fairness-safety/) · [Language models & pretraining · 1 work](https://md.research.elamur.ai/free/en/topics/language-models/) · [Reasoning · 1 work](https://md.research.elamur.ai/free/en/topics/reasoning/)

## Works by year

### 2020s

[**2026** 2 papers](https://md.research.elamur.ai/free/en/authors/shengjie-zhao/year/2026/)

## Papers

The most cited first (OpenAlex and our library).

1. **[AdapThink: Adaptive Thinking Preferences for Reasoning Language Models](https://md.research.elamur.ai/free/en/papers/xu-2026-adapthink-adaptive-thinking-preferences-reasoning/)** *(2026)* RL-trained reasoning LLMs waste tokens on easy problems through redundant self-checking. On hard problems they often abandon promising lines of reasoning too early. AdapThink is a post-training framework that replaces fixed length budgets with preferences derived from each group of sampled responses.
2. **[syuhhh@EEUCA 2026: A Three-Stage Progressive Training Framework for Fine-Grained Toxicity Detection in Online Gaming Communities](https://md.research.elamur.ai/free/en/papers/shi-2026-syuhhh-eeuca-2026-three-stage/)** *(2026)* The paper describes the winning entry in the GameTox shared task at the 9th EEUCA workshop. The task asks systems to assign one of six toxic-intent labels to in-game chat messages from World of Tanks. These messages are very short and full of slang, and the toxic classes are heavily outnumbered by non-toxic ones.

## Co-authors here

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

- [Wei Wang](https://md.research.elamur.ai/free/en/authors/wei-wang/)
- [Yu Wang](https://md.research.elamur.ai/free/en/authors/yu-wang/)

## Venues

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

- [Workshop on Event Extraction and Understanding: Challenges and Applications](https://md.research.elamur.ai/free/en/venues/eeuca/): [Workshop on Event Extraction and Understanding: Challenges and Applications 2026](https://md.research.elamur.ai/free/en/venues/eeuca/2026/)
- [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
