---
title: "Han Wang — author profile and papers — Elamur Research"
description: "Han Wang, University of North Carolina at Chapel Hill: 6 papers on Elamur Research (2018–2026), h-index 30 — affiliations, topics…"
canonical: "https://research.elamur.ai/free/en/authors/han-wang/"
---
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# Han Wang

Han Wang has 6 papers in our library, in 2018–2026, most of them on [Reasoning](https://md.research.elamur.ai/free/en/topics/reasoning/), [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/), [Speech & spoken language](https://md.research.elamur.ai/free/en/topics/speech/); often with [Changhao Pan](https://md.research.elamur.ai/free/en/authors/changhao-pan/), [Chenyuhao Wen](https://md.research.elamur.ai/free/en/authors/chenyuhao-wen/), [Haiyang Yu](https://md.research.elamur.ai/free/en/authors/haiyang-yu/).

6 papers in our library · 2018–2026

[OpenAlex](https://openalex.org/A5100452675) · [ORCID](https://orcid.org/0000-0002-1320-0947) · [**h-index 30**](https://openalex.org/authors/A5100452675) · [187 works](https://openalex.org/works?filter=author.id:A5100452675) · [3,225 citations](https://openalex.org/works?filter=author.id:A5100452675&sort=cited_by_count:desc) OpenAlex, 2026-10-14

[📄 6 works in our library](https://md.research.elamur.ai/free/en/authors/han-wang/#papers) · [🔗 Cited 67 times in our library](https://md.research.elamur.ai/free/en/authors/han-wang/cited-by/) · [⭐ Paper Stars ranking: #7015](https://md.research.elamur.ai/free/en/paper-stars/page/71/#star-7015)

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

## Affiliations

[🎓**Guangxi University** Nanning · China 2018–2026 · 41 papers*current*](https://md.research.elamur.ai/free/en/universities/guangxi-university/) · [🎓**University of North Carolina at Chapel Hill** Chapel Hill · United States 2018–2026 · 34 papers*current*](https://md.research.elamur.ai/free/en/universities/university-of-north-carolina-at-chapel-hill/) · [🎓**Hangzhou City University** Hangzhou 2023–2026 · 6 papers*current*](https://ror.org/01wck0s05) · [🎓**University of Jyväskylä** Jyväskylä · Finland 2024–2026 · 3 papers*current*](https://md.research.elamur.ai/free/en/universities/university-of-jyvaskyla/) · [🎓**Central South University** Changsha · China 2025–2026 · 2 papers*current*](https://md.research.elamur.ai/free/en/universities/central-south-university/) · [🎓**Changchun University of Chinese Medicine** Changchun · China 2020–2026 · 2 papers*current*](https://ror.org/035cyhw15) · [🎓**North China University of Science and Technology** Tangshan · China 2023–2026 · 2 papers*current*](https://ror.org/04z4wmb81) · [🎓**Northeast Agricultural University** Harbin · China 2017–2026 · 2 papers*current*](https://ror.org/0515nd386) · [🎓**Northeast Normal University** Changchun · China 2011–2026 · 2 papers*current*](https://md.research.elamur.ai/free/en/universities/northeast-normal-university/) · [🎓**University of Malaya** Kuala Lumpur · Malaysia 2025–2026 · 2 papers*current*](https://md.research.elamur.ai/free/en/universities/university-of-malaya/)

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 69 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 5 The field of science this work belongs to (OpenAlex fields).[Arts and Humanities · 6 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Computer Science · 6 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Artificial Intelligence · 6 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Language and Linguistics · 6 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/)

🧭 Topics 7 Research subjects and languages the work is about.[Reasoning · 3 works](https://md.research.elamur.ai/free/en/topics/reasoning/) · [Language models & pretraining · 2 works](https://md.research.elamur.ai/free/en/topics/language-models/) · [Bias, fairness & safety · 1 work](https://md.research.elamur.ai/free/en/topics/bias-fairness-safety/) · [Efficient models & compression · 1 work](https://md.research.elamur.ai/free/en/topics/efficient-models/) · [English · 1 work](https://md.research.elamur.ai/free/en/topics/english/) · [Evaluation & benchmarks · 1 work](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/) · [Speech & spoken language · 1 work](https://md.research.elamur.ai/free/en/topics/speech/)

## Works by year

### 2020s

[**2026** 2 papers](https://md.research.elamur.ai/free/en/authors/han-wang/year/2026/) · [**2025** 2 papers](https://md.research.elamur.ai/free/en/authors/han-wang/year/2025/) · [**2024** 1 paper](https://md.research.elamur.ai/free/en/authors/han-wang/year/2024/)

### 2010s

[**2018** 1 paper](https://md.research.elamur.ai/free/en/authors/han-wang/year/2018/)

## Papers

The most cited first (OpenAlex and our library).

1. **[Self-Distillation Bridges Distribution Gap in Language Model Fine-Tuning](https://md.research.elamur.ai/free/en/papers/yang-2024-self-distillation-bridges-distribution-gap/)** *(2024 · 63 citations)* When an instruction-tuned LLM is further fine-tuned for a narrow downstream task, it tends to lose general abilities such as instruction following, helpfulness and safety alignment.
2. **[Prolonged Reasoning Is Not All You Need: Certainty-Based Adaptive Routing for Efficient LLM/MLLM Reasoning](https://md.research.elamur.ai/free/en/papers/lu-2025-prolonged-reasoning-all-need-certainty/)** *(2025 · 11 citations)* Reasoning-tuned LLMs and MLLMs tend to produce long chain-of-thought output for every query. This costs many tokens and can even hurt accuracy on easy, fact-based questions. A pilot with Qwen2.5-0.5B on text-rich VQA and KIE data showed that direct answers were both more accurate and far cheaper than reasoning-based…
3. **[AlphaOne: Reasoning Models Thinking Slow and Fast at Test Time](https://md.research.elamur.ai/free/en/papers/zhang-2025-alphaone-reasoning-models-thinking-slow/)** *(2025 · 10 citations)* Models like OpenAI o1 and DeepSeek-R1, known as large reasoning models (LRMs), frequently overthink or underthink at inference time.
4. **[English Out-of-Vocabulary Lexical Evaluation Task](https://md.research.elamur.ai/free/en/papers/wang-2018-english-out-vocabulary-lexical-evaluation/)** *(2018 · 3 citations)* The paper proposes a benchmark for words a model has never seen: out-of-vocabulary (OOV) items that occur only in test material, so their meaning must come from surrounding text.
5. **[Comprehensive Benchmarking of Long-Form Speech Generation in Diverse Scenarios](https://md.research.elamur.ai/free/en/papers/pan-2026-comprehensive-benchmarking-long-form-speech/)** *(2026)* Long-form text-to-speech has shifted from single sentences to paragraphs and multi-speaker dialogue, but evaluation has not kept pace.
6. **[Stabilizing Efficient Reasoning with Step-Level Advantage Selection](https://md.research.elamur.ai/free/en/papers/wang-2026-stabilizing-efficient-reasoning-step-level/)** *(2026)* Methods that make LLM reasoning shorter usually add length penalties or pruning. They also tend to post-train in a much smaller context window than the base model used. The authors separate these two factors. They post-train DeepScaleR-1.5B-Preview with plain GRPO in a 4K window, using only a correctness reward. This…

## Co-authors here

12 of 23 co-authors with a page, the most papers together first.

- [Changhao Pan](https://md.research.elamur.ai/free/en/authors/changhao-pan/)
- [Chenyuhao Wen](https://md.research.elamur.ai/free/en/authors/chenyuhao-wen/)
- [Haiyang Yu](https://md.research.elamur.ai/free/en/authors/haiyang-yu/)
- [Hao Feng](https://md.research.elamur.ai/free/en/authors/hao-feng/)
- [Jialian Wu](https://md.research.elamur.ai/free/en/authors/jialian-wu/)
- [Jiang Liu](https://md.research.elamur.ai/free/en/authors/jiang-liu/)
- [Jinghui Lu](https://md.research.elamur.ai/free/en/authors/jinghui-lu/)
- [Jingqun Tang](https://md.research.elamur.ai/free/en/authors/jingqun-tang/)
- [Jitendra Malik](https://md.research.elamur.ai/free/en/authors/jitendra-malik/)
- [Mohit Bansal](https://md.research.elamur.ai/free/en/authors/mohit-bansal/)
- [Qian Liu](https://md.research.elamur.ai/free/en/authors/qian-liu/)
- [Rui Yang](https://md.research.elamur.ai/free/en/authors/rui-yang/)

## Venues

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

- [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/) ×2: [Findings of the Association for Computational Linguistics 2026](https://md.research.elamur.ai/free/en/venues/findings/2026/) ×2
- [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/): [ACL 2024](https://md.research.elamur.ai/free/en/venues/acl/2024/)
- [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/)

## Cited by

Papers of our library cite their works 67 times (of the 149,439 papers whose bibliographies we read); [14 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/han-wang/cited-by/).

Updated 1 November 2026
