--- title: "Ruixiang Tang — author profile and papers — Elamur Research" description: "Ruixiang Tang, Rutgers, The State University of New Jersey: 4 papers on Elamur Research (2023–2026), h-index 12 — affiliations, topics…" canonical: "https://research.elamur.ai/free/en/authors/ruixiang-tang/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/ruixiang-tang/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Ruixiang Tang # Ruixiang Tang Ruixiang Tang has 4 papers in our library, in 2023–2026, 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/), [Vision & language](https://md.research.elamur.ai/free/en/topics/multimodal/); often with [Xia Hu](https://md.research.elamur.ai/free/en/authors/xia-hu/), [Andrew Wen](https://md.research.elamur.ai/free/en/authors/andrew-wen/), [Bing Yin](https://md.research.elamur.ai/free/en/authors/bing-yin/). 4 papers in our library · 2023–2026 [OpenAlex](https://openalex.org/A5101660251) · [ORCID](https://orcid.org/0000-0001-6476-2336) · [Wikidata](https://www.wikidata.org/wiki/Q130839439) · [**h-index 12**](https://openalex.org/authors/A5101660251) · [54 works](https://openalex.org/works?filter=author.id:A5101660251) · [1,425 citations](https://openalex.org/works?filter=author.id:A5101660251&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 4 works in our library](https://md.research.elamur.ai/free/en/authors/ruixiang-tang/#papers) · [🔗 Cited 242 times in our library](https://md.research.elamur.ai/free/en/authors/ruixiang-tang/cited-by/) · [5 more in our library without a page yet](#also) · [⭐ Paper Stars ranking: #2680](https://md.research.elamur.ai/free/en/paper-stars/page/27/#star-2680) 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=Ruixiang+Tang) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Ruixiang+Tang) · [dblp](https://dblp.org/search?q=Ruixiang+Tang) · [ACL Anthology](https://aclanthology.org/search/?q=Ruixiang+Tang) ## Affiliations [🎓**Rutgers, The State University of New Jersey** New Brunswick · United States 2024–2026 · 12 papersEmployment since 2024 · Assistant Professor, Computer Science*current*](https://md.research.elamur.ai/free/en/universities/rutgers-the-state-university-of-new-jersey/) · [🎓**Rochester Institute of Technology** Rochester · United States 2026 · 1 paper*current*](https://md.research.elamur.ai/free/en/universities/rochester-institute-of-technology/) · [🎓**Rice University** Houston · United States 2020–2024 · 24 papersEducation 2021–2024 · PhD, Computer Science](https://md.research.elamur.ai/free/en/universities/rice-university/) · [🎓**Texas A&M University** College Station · United States 2019–2024 · 7 papersEducation 2019–2021 · Computer Science and Engineering](https://md.research.elamur.ai/free/en/universities/texas-a-m-university/) · [🎓**Tsinghua University** Beijing · China 2019–2020 · 3 papers](https://md.research.elamur.ai/free/en/universities/tsinghua-university/) · [🎓**Duke University** Durham · United States 2019 · 2 papers](https://md.research.elamur.ai/free/en/universities/duke-university/) From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 3 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 · 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/) · [Artificial Intelligence · 4 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 · 3 works](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) 🧭 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/) · [Vision & language · 1 work](https://md.research.elamur.ai/free/en/topics/multimodal/) ## Works by year ### 2020s [**2026** 1 paper](https://md.research.elamur.ai/free/en/authors/ruixiang-tang/year/2026/) · [**2025** 2 papers](https://md.research.elamur.ai/free/en/authors/ruixiang-tang/year/2025/) · [**2023** 1 paper](https://md.research.elamur.ai/free/en/authors/ruixiang-tang/year/2023/) ## Papers The most cited first (OpenAlex and our library). 1. **[Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and Beyond](https://md.research.elamur.ai/free/en/papers/yang-2023-harnessing-power-llms-practice-survey/)** *(2023 · 814 citations)* This survey is a practitioner-oriented guide to deciding when large language models are the right tool for downstream NLP work, and when they are not. The authors do not train anything new. Instead, they organise existing knowledge along three axes: models, data and tasks. 2. **[Disentangling Memory and Reasoning Ability in Large Language Models](https://md.research.elamur.ai/free/en/papers/jin-2025-disentangling-memory-reasoning-ability-large/)** *(2025 · 45 citations)* Large language models typically answer knowledge-heavy questions with one undivided chain of thought. This makes it hard to tell whether a wrong answer comes from missing facts or from faulty logic, and the blending is associated with knowledge being lost mid-chain and with hallucination. 3. **[TACO: Enhancing Multimodal In-context Learning via Task Mapping-Guided Sequence Configuration](https://md.research.elamur.ai/free/en/papers/li-2025-taco-enhancing-multimodal-context-learning/)** *(2025 · 22 citations)* Large vision–language models (LVLMs) can learn tasks from interleaved image–text demonstrations, but their in-context learning (ICL) is fragile. Small changes to the chosen demonstrations (ICDs) can noticeably shift outputs, and existing selection methods rely on hand-crafted relevance metrics. 4. **[FaithLM: Towards Faithful Explanations for Large Language Models](https://md.research.elamur.ai/free/en/papers/chuang-2026-faithlm-faithful-explanations-large-language/)** *(2026 · 9 citations)* LLMs often explain their answers in natural language, but these explanations frequently do not reflect what actually drove the prediction. Classic fidelity tests, which delete important tokens, also fit poorly with free-text rationales whose content is semantic rather than token-level. ## All works 9 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. **[Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and Beyond](https://md.research.elamur.ai/free/en/papers/yang-2023-harnessing-power-llms-practice-survey/) [ACM Transactions on Knowledge Discovery from Data](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-knowledge-discovery-from-data/)**Jingfeng Yang, Hongye Jin, Ruixiang Tang, et al.*2023 · 814 citations* 2. **[Disentangling Memory and Reasoning Ability in Large Language Models](https://md.research.elamur.ai/free/en/papers/jin-2025-disentangling-memory-reasoning-ability-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mingyu Jin, Weidi Luo, Sitao Cheng, et al.*2025 · 45 citations* 3. **[TACO: Enhancing Multimodal In-context Learning via Task Mapping-Guided Sequence Configuration](https://md.research.elamur.ai/free/en/papers/li-2025-taco-enhancing-multimodal-context-learning/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yanshu Li, Jianjiang Yang, Tian Yun, et al.*2025 · 22 citations* 4. **[FaithLM: Towards Faithful Explanations for Large Language Models](https://md.research.elamur.ai/free/en/papers/chuang-2026-faithlm-faithful-explanations-large-language/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Yu-Neng Chuang, Guanchu Wang, Chia-Yuan Chang, et al.*2026 · 9 citations* 5. **[Counting Circuits: Mechanistic Interpretability of Visual Reasoning in Large Vision-Language Models ↗](https://arxiv.org/abs/2603.18523) arXiv (Cornell University) · no summary yet**Liwei Che et al.*2026 · 2 citations* 6. **[Learning from Primitive: Probing Visual Reasoning of LVLMs via Counting ↗](https://doi.org/10.1007/978-3-032-37023-5_37) Lecture notes in computer science · no summary yet**Liwei Che et al.*2026* 7. **[Why MLLMs Struggle to Count: Overcoming Individuation and Aggregation Bottlenecks with ConvStack ↗](https://arxiv.org/abs/2609.37096) arXiv (Cornell University) · no summary yet**Liwei Che et al.*2026* 8. **[Reasoning over Precedents Alongside Statutes: Case-Augmented Deliberative Alignment for LLM Safety ↗](https://aclanthology.org/2026.acl-long.30/) Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yet**Can Jin et al.*2026* 9. **[A Decoupled Multi-Agent Framework for Complex Text Style Transfer ↗](https://aclanthology.org/2025.findings-emnlp.1166/) Findings of the Association for Computational Linguistics: EMNLP 2025 · no summary yet**Lingxi Zhang et al.*2025* ## Co-authors here 12 of 23 co-authors with a page, the most papers together first. - [Xia Hu](https://md.research.elamur.ai/free/en/authors/xia-hu/) ×2 - [Andrew Wen](https://md.research.elamur.ai/free/en/authors/andrew-wen/) - [Bing Yin](https://md.research.elamur.ai/free/en/authors/bing-yin/) - [Chia-Yuan Chang](https://md.research.elamur.ai/free/en/authors/chia-yuan-chang/) - [Fan Yang](https://md.research.elamur.ai/free/en/authors/fan-yang/) - [Guanchu Wang](https://md.research.elamur.ai/free/en/authors/guanchu-wang/) - [Haoming Jiang](https://md.research.elamur.ai/free/en/authors/haoming-jiang/) - [Hongye Jin](https://md.research.elamur.ai/free/en/authors/hongye-jin/) - [Jinfa Huang](https://md.research.elamur.ai/free/en/authors/jinfa-huang/) - [Jingfeng Yang](https://md.research.elamur.ai/free/en/authors/jingfeng-yang/) - [Mengnan Du](https://md.research.elamur.ai/free/en/authors/mengnan-du/) - [Mingyu Jin](https://md.research.elamur.ai/free/en/authors/mingyu-jin/) ## 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 2025](https://md.research.elamur.ai/free/en/venues/acl/2025/) - [ACM Transactions on Knowledge Discovery from Data](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-knowledge-discovery-from-data/): [ACM Transactions on Knowledge Discovery from Data 2023](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-knowledge-discovery-from-data/2023/) - [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/) - [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: EMNLP 2025 - Lecture notes in computer science ## Cited by Papers of our library cite their works 242 times (of the 149,439 papers whose bibliographies we read); [39 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/ruixiang-tang/cited-by/). Updated 30 October 2026