---
title: "Jinpeng Hu — author profile and papers — Elamur Research"
description: "Jinpeng Hu, Hefei University of Technology: 4 papers on Elamur Research (2025–2026), h-index 6 — affiliations, topics, co-authors and who…"
canonical: "https://research.elamur.ai/free/en/authors/jinpeng-hu/"
---
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# Jinpeng Hu

Jinpeng Hu 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/), [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 [Zhuo Li](https://md.research.elamur.ai/free/en/authors/zhuo-li/), [Anningzhe Gao](https://md.research.elamur.ai/free/en/authors/anningzhe-gao/), [Xiang Wan](https://md.research.elamur.ai/free/en/authors/xiang-wan/).

4 papers in our library · 2025–2026

[OpenAlex](https://openalex.org/A5139852755) · [ORCID](https://orcid.org/0000-0003-4090-7494) · [**h-index 6**](https://openalex.org/authors/A5139852755) · [16 works](https://openalex.org/works?filter=author.id:A5139852755) · [245 citations](https://openalex.org/works?filter=author.id:A5139852755&sort=cited_by_count:desc) OpenAlex, 2026-10-14

[📄 4 works in our library](https://md.research.elamur.ai/free/en/authors/jinpeng-hu/#papers) · [🔗 Cited 18 times in our library](https://md.research.elamur.ai/free/en/authors/jinpeng-hu/cited-by/) · [1 more in our library without a page yet](#also) · [⭐ Paper Stars ranking: #8786](https://md.research.elamur.ai/free/en/paper-stars/page/88/#star-8786)

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

## Affiliations

[🎓**Hefei University of Technology** Hefei · China 2024–2026 · 12 papersEmployment*current*](https://md.research.elamur.ai/free/en/universities/hefei-university-of-technology/) · [🎓**Chinese University of Hong Kong, Shenzhen** Shenzhen · China 2019–2023 · 4 papersEducation 2019–2023 · PhD](https://md.research.elamur.ai/free/en/universities/chinese-university-of-hong-kong-shenzhen/) · [🎓**Shenzhen Research Institute of Big Data** Shenzhen · China 2022–2023 · 4 papers](https://md.research.elamur.ai/free/en/universities/shenzhen-research-institute-of-big-data/) · [🎓**Harbin Institute of Technology** Harbin · China 2013–2019Education 2013–2017 · BachelorEducation 2017–2019 · Master](https://md.research.elamur.ai/free/en/universities/harbin-institute-of-technology/)

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 8 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/) · [Health Informatics · 2 works](https://md.research.elamur.ai/free/en/shelves/medicine/health-informatics/) · [Medicine · 2 works](https://md.research.elamur.ai/free/en/shelves/medicine/) · [Safety Research · 1 work](https://md.research.elamur.ai/free/en/shelves/social-sciences/safety-research/) · [Social Sciences · 1 work](https://md.research.elamur.ai/free/en/shelves/social-sciences/)

🧭 Topics 3 Research subjects and languages the work is about.[Language models & pretraining · 4 works](https://md.research.elamur.ai/free/en/topics/language-models/) · [Reasoning · 1 work](https://md.research.elamur.ai/free/en/topics/reasoning/) · [Bias, fairness & safety · 1 work](https://md.research.elamur.ai/free/en/topics/bias-fairness-safety/)

## Works by year

### 2020s

[**2026** 2 papers](https://md.research.elamur.ai/free/en/authors/jinpeng-hu/year/2026/) · [**2025** 2 papers](https://md.research.elamur.ai/free/en/authors/jinpeng-hu/year/2025/)

## Papers

The most cited first (OpenAlex and our library).

1. **[Self-Instructed Derived Prompt Generation Meets In-Context Learning: Unlocking New Potential of Black-Box LLMs](https://md.research.elamur.ai/free/en/papers/li-2025-self-instructed-derived-prompt-generation/)** *(2025 · 9 citations)* Rewriting prompts is a common way to get better answers from LLMs that cannot be fine-tuned, such as GPT4.
2. **[Psyche-R1: Towards Reliable Psychological LLMs through Unified Empathy, Expertise, and Reasoning](https://md.research.elamur.ai/free/en/papers/dai-2026-psyche-r1-reliable-psychological-llms/)** *(2026 · 8 citations)* Psyche-R1 is a Chinese psychological LLM that combines three abilities usually built separately: empathetic counselling, psychology domain knowledge, and explicit reasoning.
3. **[Add-One-In: Incremental Sample Selection for Large Language Models via a Choice-Based Greedy Paradigm](https://md.research.elamur.ai/free/en/papers/li-2025-add-one-incremental-sample-selection/)** *(2025 · 5 citations)* Picking a compact, high-value subset of instruction data can cut supervised fine-tuning (SFT) costs for LLMs.
4. **[PsychEthicsBench: Evaluating Large Language Models Against Australian Mental Health Ethics](https://md.research.elamur.ai/free/en/papers/shen-2026-psychethicsbench-evaluating-large-language-models/)** *(2026 · 2 citations)* Most safety evaluations of LLMs judge a model by whether it refuses harmful requests. In mental health this is a weak measure. A curt refusal can seem cold, discourage someone from seeking help, or still contain ethically problematic content. Existing medical-ethics benchmarks also tend to assume one shared standard…

## All works

5 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. **[Self-Instructed Derived Prompt Generation Meets In-Context Learning: Unlocking New Potential of Black-Box LLMs](https://md.research.elamur.ai/free/en/papers/li-2025-self-instructed-derived-prompt-generation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhuo Li, Yuhao Du, Jinpeng Hu, et al.*2025 · 9 citations*
2. **[Psyche-R1: Towards Reliable Psychological LLMs through Unified Empathy, Expertise, and Reasoning](https://md.research.elamur.ai/free/en/papers/dai-2026-psyche-r1-reliable-psychological-llms/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chongyuan Dai, Jinpeng Hu, Hongchang Shi, et al.*2026 · 8 citations*
3. **[Add-One-In: Incremental Sample Selection for Large Language Models via a Choice-Based Greedy Paradigm](https://md.research.elamur.ai/free/en/papers/li-2025-add-one-incremental-sample-selection/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhuo Li, Yuhao Du, Xiaoqi Jiao, et al.*2025 · 5 citations*
4. **[PsychEthicsBench: Evaluating Large Language Models Against Australian Mental Health Ethics](https://md.research.elamur.ai/free/en/papers/shen-2026-psychethicsbench-evaluating-large-language-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yaling Shen, Stephanie Fong, Yiwen Jiang, et al.*2026 · 2 citations*
5. **[WebUncertainty: Dual-Level Uncertainty Driven Planning and Reasoning For Autonomous Web Agent ↗](https://aclanthology.org/2026.findings-acl.637/) Findings of the Association for Computational Linguistics: ACL 2026 · no summary yet**Lingfeng Zhang et al.*2026*

## Co-authors here

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

- [Zhuo Li](https://md.research.elamur.ai/free/en/authors/zhuo-li/) ×3
- [Anningzhe Gao](https://md.research.elamur.ai/free/en/authors/anningzhe-gao/) ×2
- [Xiang Wan](https://md.research.elamur.ai/free/en/authors/xiang-wan/) ×2
- [Yuhao Du](https://md.research.elamur.ai/free/en/authors/yuhao-du/) ×2
- [Feilong Tang](https://md.research.elamur.ai/free/en/authors/feilong-tang/)
- [Meng Wang](https://md.research.elamur.ai/free/en/authors/meng-wang/)
- [Steven Y. Guo](https://md.research.elamur.ai/free/en/authors/steven-y-guo/)
- [Xiangyu Zhao](https://md.research.elamur.ai/free/en/authors/xiangyu-zhao/)
- [Xiaoqi Jiao](https://md.research.elamur.ai/free/en/authors/xiaoqi-jiao/)
- [Xun Yang](https://md.research.elamur.ai/free/en/authors/xun-yang/)
- [Zimu Wang](https://md.research.elamur.ai/free/en/authors/zimu-wang/)
- [Zongyuan Ge](https://md.research.elamur.ai/free/en/authors/zongyuan-ge/)

## 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/) ×2: [ACL 2026](https://md.research.elamur.ai/free/en/venues/acl/2026/), [ACL 2025](https://md.research.elamur.ai/free/en/venues/acl/2025/)
- [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/): [EMNLP 2025](https://md.research.elamur.ai/free/en/venues/emnlp/2025/)
- [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/)
- Findings of the Association for Computational Linguistics: ACL 2026

## Cited by

Papers of our library cite their works 18 times (of the 149,439 papers whose bibliographies we read); [6 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/jinpeng-hu/cited-by/).

Updated 1 November 2026
