--- title: "Yuxuan Jiang — author profile and papers · Reasoning" description: "Yuxuan Jiang, University of Maryland, Baltimore County: 5 papers on Elamur Research (2025–2026), h-index 2 — affiliations, topics…" canonical: "https://research.elamur.ai/free/en/authors/yuxuan-jiang/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/yuxuan-jiang/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Yuxuan Jiang # Yuxuan Jiang Yuxuan Jiang has 5 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/), [Question answering](https://md.research.elamur.ai/free/en/topics/question-answering/); often with [Francis Ferraro](https://md.research.elamur.ai/free/en/authors/francis-ferraro/), [Angel X. Chang](https://md.research.elamur.ai/free/en/authors/angel-x-chang/), [Chaofan Tao](https://md.research.elamur.ai/free/en/authors/chaofan-tao/). 5 papers in our library · 2025–2026 [OpenAlex](https://openalex.org/A5139760986) · [**h-index 2**](https://openalex.org/authors/A5139760986) · [4 works](https://openalex.org/works?filter=author.id:A5139760986) · [4 citations](https://openalex.org/works?filter=author.id:A5139760986&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 5 works in our library](https://md.research.elamur.ai/free/en/authors/yuxuan-jiang/#papers) · [🔗 Cited 39 times in our library](https://md.research.elamur.ai/free/en/authors/yuxuan-jiang/cited-by/) · [⭐ Paper Stars ranking: #9183](https://md.research.elamur.ai/free/en/paper-stars/page/92/#star-9183) 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=Yuxuan+Jiang) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Yuxuan+Jiang) · [dblp](https://dblp.org/search?q=Yuxuan+Jiang) · [ACL Anthology](https://aclanthology.org/search/?q=Yuxuan+Jiang) ## Affiliations [🎓**University of Maryland, Baltimore County** Baltimore · United States 2026 · 2 papers*current*](https://md.research.elamur.ai/free/en/universities/university-of-maryland-baltimore-county/) 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 7 The field of science this work belongs to (OpenAlex fields).[Computer Science · 5 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Arts and Humanities · 4 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Artificial Intelligence · 5 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Language and Linguistics · 4 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) · [Computer Vision and Pattern Recognition · 4 works](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) · [Experimental and Cognitive Psychology · 1 work](https://md.research.elamur.ai/free/en/shelves/psychology/experimental-and-cognitive-psychology/) · [Psychology · 1 work](https://md.research.elamur.ai/free/en/shelves/psychology/) 🧭 Topics 6 Research subjects and languages the work is about.[Reasoning · 3 works](https://md.research.elamur.ai/free/en/topics/reasoning/) · [Efficient models & compression · 1 work](https://md.research.elamur.ai/free/en/topics/efficient-models/) · [Language models & pretraining · 1 work](https://md.research.elamur.ai/free/en/topics/language-models/) · [Question answering · 1 work](https://md.research.elamur.ai/free/en/topics/question-answering/) · [Sentiment & emotion · 1 work](https://md.research.elamur.ai/free/en/topics/sentiment-emotion/) · [Vision & language · 1 work](https://md.research.elamur.ai/free/en/topics/multimodal/) ## Works by year ### 2020s [**2026** 4 papers](https://md.research.elamur.ai/free/en/authors/yuxuan-jiang/year/2026/) · [**2025** 1 paper](https://md.research.elamur.ai/free/en/authors/yuxuan-jiang/year/2025/) ## Papers The most cited first (OpenAlex and our library). 1. **[DRP: Distilled Reasoning Pruning with Skill-aware Step Decomposition for Efficient Large Reasoning Models](https://md.research.elamur.ai/free/en/papers/jiang-2025-drp-distilled-reasoning-pruning-skill/)** *(2025 · 21 citations)* Large Reasoning Models tend to "overthink": they produce very long chains of thought full of redundant checks and backtracking, which wastes compute. 2. **[Find Your Optimal Teacher: Personalized Data Synthesis via Router-Guided Multi-Teacher Distillation](https://md.research.elamur.ai/free/en/papers/zhang-2026-find-your-optimal-teacher-personalized/)** *(2026 · 13 citations)* Small LLMs are usually distilled by fine-tuning them on outputs from the most powerful available teacher. Prior work shows this can backfire: very strong teachers may produce answers that are too complex or too far from what the student can absorb. Earlier remedies (Mix, CAR) still make every candidate teacher answer… 3. **[Beyond Math: Stories as a Testbed for Memorization-Constrained Reasoning in LLMs](https://md.research.elamur.ai/free/en/papers/jiang-2026-beyond-math-stories-as-testbed/)** *(2026 · 10 citations)* Research on memorization in LLMs has mostly focused on math and logic, where recalling previously seen problems is treated as a pure shortcut. 4. **[From Recognition to Reasoning: Benchmarking and Enhancing MLLMs on Real-World Receipt Document Understanding](https://md.research.elamur.ai/free/en/papers/wang-2026-recognition-reasoning-benchmarking-enhancing-mllms/)** *(2026)* The paper addresses Visual Information Extraction (VIE) from receipts and invoices. Existing benchmarks are small, synthetic, or limited to narrow domains, and they mostly test literal text extraction. The authors introduce ReceiptBench, a human-annotated collection of 10,656 real-world financial documents, including… 5. **[QA-MoE: Towards a Continuous Reliability Spectrum with Quality-Aware Mixture of Experts for Robust Multimodal Sentiment Analysis](https://md.research.elamur.ai/free/en/papers/zhu-2026-qa-moe-continuous-reliability-spectrum/)** *(2026)* Real-world multimodal sentiment analysis (MSA) systems receive text, audio and video that may be noisy, partially lost, or both at once. ## Co-authors here 12 of 17 co-authors with a page, the most papers together first. - [Francis Ferraro](https://md.research.elamur.ai/free/en/authors/francis-ferraro/) ×2 - [Angel X. Chang](https://md.research.elamur.ai/free/en/authors/angel-x-chang/) - [Chaofan Tao](https://md.research.elamur.ai/free/en/authors/chaofan-tao/) - [Chenming Shang](https://md.research.elamur.ai/free/en/authors/chenming-shang/) - [Dawei Li](https://md.research.elamur.ai/free/en/authors/dawei-li/) - [Hayden Kwok-Hay So](https://md.research.elamur.ai/free/en/authors/hayden-kwok-hay-so/) - [Hengyuan Zhang](https://md.research.elamur.ai/free/en/authors/hengyuan-zhang/) - [Jing Xiong](https://md.research.elamur.ai/free/en/authors/jing-xiong/) - [Jun Chen](https://md.research.elamur.ai/free/en/authors/jun-chen/) - [Leilei Gan](https://md.research.elamur.ai/free/en/authors/leilei-gan/) - [Ngai Wong](https://md.research.elamur.ai/free/en/authors/ngai-wong/) - [Ruobing Xie](https://md.research.elamur.ai/free/en/authors/ruobing-xie/) ## 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 - [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/): [EACL 2026](https://md.research.elamur.ai/free/en/venues/eacl/2026/) ## Cited by Papers of our library cite their works 39 times (of the 149,439 papers whose bibliographies we read); [13 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/yuxuan-jiang/cited-by/). Updated 2 November 2026