---
title: "Sirui Han — author profile and papers — Elamur Research"
description: "Sirui Han, Hong Kong University of Science and Technology: 10 papers on Elamur Research (2025–2026), h-index 5 — affiliations, topics…"
canonical: "https://research.elamur.ai/free/en/authors/sirui-han/"
---
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# Sirui Han

Sirui Han has 10 papers in our library, in 2025–2026, 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/), [Evaluation & benchmarks](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/); often with [Yike Guo](https://md.research.elamur.ai/free/en/authors/yike-guo/), [Jiaming Ji](https://md.research.elamur.ai/free/en/authors/jiaming-ji/), [Haoran Li](https://md.research.elamur.ai/free/en/authors/haoran-li/).

10 papers in our library · 2025–2026

[OpenAlex](https://openalex.org/A5021255269) · [ORCID](https://orcid.org/0000-0001-7303-0671) · [**h-index 5**](https://openalex.org/authors/A5021255269) · [24 works](https://openalex.org/works?filter=author.id:A5021255269) · [51 citations](https://openalex.org/works?filter=author.id:A5021255269&sort=cited_by_count:desc) OpenAlex, 2026-10-14

[📄 10 works in our library](https://md.research.elamur.ai/free/en/authors/sirui-han/#papers) · [🔗 Cited 125 times in our library](https://md.research.elamur.ai/free/en/authors/sirui-han/cited-by/) · [4 more in our library without a page yet](#also) · [⭐ Paper Stars ranking: #6108](https://md.research.elamur.ai/free/en/paper-stars/page/62/#star-6108)

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

## Affiliations

[🎓**Hong Kong University of Science and Technology** Hong Kong · China 2023–2026 · 123 papersEmployment · Assistant Professor*current*](https://md.research.elamur.ai/free/en/universities/hong-kong-university-of-science-and-technology/) · [🎓**Chinese University of Hong Kong** Hong Kong · China 2016–2026 · 3 papers](https://md.research.elamur.ai/free/en/universities/chinese-university-of-hong-kong/) · [🎓**Hong Kong Polytechnic University** Hong Kong · China 2021–2023 · 3 papers](https://md.research.elamur.ai/free/en/universities/hong-kong-polytechnic-university/)

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 1 more institution on single bylines are not listed.

## Fields, topics and concepts

Of its works in our library, with the number of works on each.

📚 Shelves 13 The field of science this work belongs to (OpenAlex fields).[Computer Science · 10 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Artificial Intelligence · 8 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Arts and Humanities · 6 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Language and Linguistics · 6 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) · [Social Sciences · 4 works](https://md.research.elamur.ai/free/en/shelves/social-sciences/) · [Safety Research · 2 works](https://md.research.elamur.ai/free/en/shelves/social-sciences/safety-research/) · [Computer Vision and Pattern Recognition · 5 works](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) · [Sociology and Political Science · 2 works](https://md.research.elamur.ai/free/en/shelves/social-sciences/sociology-and-political-science/) · [Law · 1 work](https://md.research.elamur.ai/free/en/shelves/social-sciences/law/) · [Political Science and International Relations · 1 work](https://md.research.elamur.ai/free/en/shelves/social-sciences/political-science-and-international-relations/) · [Decision Sciences · 1 work](https://md.research.elamur.ai/free/en/shelves/decision-sciences/) · [Information Systems · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/information-systems/) · [Information Systems and Management · 1 work](https://md.research.elamur.ai/free/en/shelves/decision-sciences/information-systems-and-management/)

🧭 Topics 7 Research subjects and languages the work is about.[Legal AI · 3 works](https://md.research.elamur.ai/free/en/topics/legal-ai/) · [Reasoning · 5 works](https://md.research.elamur.ai/free/en/topics/reasoning/) · [Bias, fairness & safety · 3 works](https://md.research.elamur.ai/free/en/topics/bias-fairness-safety/) · [Language models & pretraining · 3 works](https://md.research.elamur.ai/free/en/topics/language-models/) · [Evaluation & benchmarks · 3 works](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/) · [Vision & language · 3 works](https://md.research.elamur.ai/free/en/topics/multimodal/) · [Efficient models & compression · 1 work](https://md.research.elamur.ai/free/en/topics/efficient-models/)

## Works by year

### 2020s

[**2026** 5 papers](https://md.research.elamur.ai/free/en/authors/sirui-han/year/2026/) · [**2025** 5 papers](https://md.research.elamur.ai/free/en/authors/sirui-han/year/2025/)

## Papers

The most cited first (OpenAlex and our library).

1. **[PKU-SafeRLHF: Towards Multi-Level Safety Alignment for LLMs with Human Preference](https://md.research.elamur.ai/free/en/papers/ji-2025-pku-saferlhf-multi-level-safety/)** *(2025 · 83 citations)* Safety alignment of large language models depends on preference data and fine-grained harm labels, which are expensive to collect at scale.
2. **[FinMME: Benchmark Dataset for Financial Multi-Modal Reasoning Evaluation](https://md.research.elamur.ai/free/en/papers/luo-2025-finmme-benchmark-dataset-financial-multi/)** *(2025 · 19 citations)* FinMME addresses the lack of specialised benchmarks for testing multimodal large language models (MLLMs) on financial material, where charts are data-dense and interpretation requires expert knowledge.
3. **[PrivaCI-Bench: Evaluating Privacy with Contextual Integrity and Legal Compliance](https://md.research.elamur.ai/free/en/papers/li-2025-privaci-bench-evaluating-privacy-contextual/)** *(2025 · 17 citations)* Most privacy benchmarks for LLMs reduce privacy to spotting personally identifiable information. That ignores whether a particular data flow is appropriate in its setting. PrivaCI-Bench addresses this gap using Contextual Integrity (CI) theory. CI describes each flow by five parameters: sender, recipient, subject…
4. **[LegalReasoner: Step-wised Verification-Correction for Legal Judgment Reasoning](https://md.research.elamur.ai/free/en/papers/shi-2025-legalreasoner-step-wised-verification-correction/)** *(2025 · 16 citations)* Legal judgment prediction (LJP) asks a model to produce a court-like ruling from a plaintiff's claim and the case facts.
5. **[Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/hu-2025-context-reasoner-incentivizing-reasoning-capability/)** *(2025 · 7 citations)* LLMs deployed as tool-using agents raise safety and privacy risks. Typical defenses detect sensitive patterns instead of reasoning about the situation, and they rarely reflect actual legal standards. The authors reframe safety and privacy as compliance questions grounded in Contextual Integrity (CI) theory. Under CI…
6. **[Bit-by-Bit: Progressive QAT Strategy with Outlier Channel Splitting for Stable Low-Bit LLMs](https://md.research.elamur.ai/free/en/papers/xu-2026-bit-bit-progressive-qat-strategy/)** *(2026 · 3 citations)* Quantization-aware training (QAT) of LLMs at extreme precisions, such as 2-bit weights and activations, often breaks down.
7. **[Learning While Staying Curious: Entropy-Preserving Supervised Fine-Tuning via Adaptive Self-Distillation for Large Reasoning Models](https://md.research.elamur.ai/free/en/papers/wang-2026-learning-while-staying-curious-entropy/)** *(2026 · 3 citations)* Large reasoning models are usually post-trained by supervised fine-tuning followed by reinforcement learning (SFT-then-RL).
8. **[Perception, Understanding and Reasoning: A Multimodal Benchmark for Video Fake News Detection](https://md.research.elamur.ai/free/en/papers/yakun-2026-perception-understanding-reasoning-multimodal-benchmark/)** *(2026 · 3 citations)* Most benchmarks for video fake news detection (VFND) score only the final real/fake label. They cannot show whether a multimodal large language model (MLLM) actually saw the right evidence, understood the story, or reasoned soundly. The authors address this with POVFNDB, a process-oriented benchmark. It is built on…
9. **[SafeMT: Multi-turn Safety for Multimodal Language Models](https://md.research.elamur.ai/free/en/papers/zhu-2026-safemt-multi-turn-safety-multimodal/)** *(2026 · 3 citations)* SafeMT targets a gap in the safety evaluation of multimodal large language models (MLLMs). Existing benchmarks mostly test single image-plus-prompt inputs, but real users talk to these models over many turns, and harmful intent can be spread across a conversation. The authors combined red-team queries from earlier…
10. **[InsightEval: An Expert-Curated Benchmark for Assessing Insight Discovery in LLM-Driven Data Agents](https://md.research.elamur.ai/free/en/papers/zhu-2026-insighteval-expert-curated-benchmark-assessing/)** *(2026 · 2 citations)* LLM-based data agents are increasingly used to extract insights from tables, but few benchmarks measure this ability well.

## All works

14 works of theirs in our library, the most cited first; 10 with a page here, the others link their original until we summarise them.

1. **[PKU-SafeRLHF: Towards Multi-Level Safety Alignment for LLMs with Human Preference](https://md.research.elamur.ai/free/en/papers/ji-2025-pku-saferlhf-multi-level-safety/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiaming Ji, Donghai Hong, Borong Zhang, et al.*2025 · 83 citations*
2. **[FinMME: Benchmark Dataset for Financial Multi-Modal Reasoning Evaluation](https://md.research.elamur.ai/free/en/papers/luo-2025-finmme-benchmark-dataset-financial-multi/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Junyu Luo, Zhizhuo Kou, Liming Yang, et al.*2025 · 19 citations*
3. **[PrivaCI-Bench: Evaluating Privacy with Contextual Integrity and Legal Compliance](https://md.research.elamur.ai/free/en/papers/li-2025-privaci-bench-evaluating-privacy-contextual/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Haoran Li, Wenbin Hu, Huihao Jing, et al.*2025 · 17 citations*
4. **[LegalReasoner: Step-wised Verification-Correction for Legal Judgment Reasoning](https://md.research.elamur.ai/free/en/papers/shi-2025-legalreasoner-step-wised-verification-correction/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Weijie Shi, Han Zhu, Jiaming Ji, et al.*2025 · 16 citations*
5. **[Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/hu-2025-context-reasoner-incentivizing-reasoning-capability/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Wenbin Hu, Haoran Li, Huihao Jing, et al.*2025 · 7 citations*
6. **[LRAS: Advanced Legal Reasoning with Agentic Search ↗](https://arxiv.org/abs/2601.07296) arXiv:2601.07296 · no summary yet**Yujin Zhou; Chuxue Cao; Jinluan Yang; Lijun Wu; Conghui He; Sirui Han;, Yike Guo*2026 · 4 citations*
7. **[Bit-by-Bit: Progressive QAT Strategy with Outlier Channel Splitting for Stable Low-Bit LLMs](https://md.research.elamur.ai/free/en/papers/xu-2026-bit-bit-progressive-qat-strategy/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Binxing Xu, Hao Gu, Lujun Li, et al.*2026 · 3 citations*
8. **[Learning While Staying Curious: Entropy-Preserving Supervised Fine-Tuning via Adaptive Self-Distillation for Large Reasoning Models](https://md.research.elamur.ai/free/en/papers/wang-2026-learning-while-staying-curious-entropy/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hao Wang, Hao Gu, Hongming Piao, et al.*2026 · 3 citations*
9. **[Perception, Understanding and Reasoning: A Multimodal Benchmark for Video Fake News Detection](https://md.research.elamur.ai/free/en/papers/yakun-2026-perception-understanding-reasoning-multimodal-benchmark/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Cui Yakun, Peng Qi, Fushuo Huo, et al.*2026 · 3 citations*
10. **[SafeMT: Multi-turn Safety for Multimodal Language Models](https://md.research.elamur.ai/free/en/papers/zhu-2026-safemt-multi-turn-safety-multimodal/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Han Zhu, Juntao Dai, Jiaming Ji, et al.*2026 · 3 citations*
11. **[InsightEval: An Expert-Curated Benchmark for Assessing Insight Discovery in LLM-Driven Data Agents](https://md.research.elamur.ai/free/en/papers/zhu-2026-insighteval-expert-curated-benchmark-assessing/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhenghao Zhu, Yuanfeng Song, Xing Chen, et al.*2026 · 2 citations*
12. **[How well can large language model agents simulate complex legal dispute resolution? ↗](https://doi.org/10.1007/s10506-026-09518-5) Artificial Intelligence and Law (Springer) · no summary yet**Yujin Zhou et al.*2026 · 1 citation*
13. **[ContextLens: Modeling Imperfect Privacy and Safety Context for Legal Compliance ↗](https://aclanthology.org/2026.acl-long.294/) Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yet**Haoran Li et al.*2026*
14. **[LexAgentHallu: A Hierarchical Benchmark for Profiling Hallucinations in Legal Agents ↗](https://arxiv.org/abs/2609.09754) arXiv:2609.09754 · EMNLP 2026 Main · no summary yet**Yujin Zhou et al.*2026*

## Co-authors here

12 of 47 co-authors with a page, the most papers together first.

- [Yike Guo](https://md.research.elamur.ai/free/en/authors/yike-guo/) ×6
- [Jiaming Ji](https://md.research.elamur.ai/free/en/authors/jiaming-ji/) ×4
- [Haoran Li](https://md.research.elamur.ai/free/en/authors/haoran-li/) ×3
- [Boyuan Chen](https://md.research.elamur.ai/free/en/authors/boyuan-chen/) ×2
- [Chengzhong Liu](https://md.research.elamur.ai/free/en/authors/chengzhong-liu/) ×2
- [Cui Yakun](https://md.research.elamur.ai/free/en/authors/cui-yakun/) ×2
- [Han Zhu](https://md.research.elamur.ai/free/en/authors/han-zhu/) ×2
- [Hao Gu](https://md.research.elamur.ai/free/en/authors/hao-gu/) ×2
- [Hao Wang](https://md.research.elamur.ai/free/en/authors/hao-wang/) ×2
- [Huihao Jing](https://md.research.elamur.ai/free/en/authors/huihao-jing/) ×2
- [Juntao Dai](https://md.research.elamur.ai/free/en/authors/juntao-dai/) ×2
- [Peizhao Hu](https://md.research.elamur.ai/free/en/authors/peizhao-hu/) ×2

## 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/) ×9: [ACL 2026](https://md.research.elamur.ai/free/en/venues/acl/2026/) ×4, [ACL 2025](https://md.research.elamur.ai/free/en/venues/acl/2025/) ×4
- [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/)
- Artificial Intelligence and Law (Springer)

## Cited by

Papers of our library cite their works 125 times (of the 149,439 papers whose bibliographies we read); [29 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/sirui-han/cited-by/).

Updated 31 October 2026