--- title: "Shangbin Feng · Microsoft — author profile and papers" description: "Shangbin Feng, Microsoft: 2 papers on Elamur Research (2023–2024), h-index 18 — affiliations, topics, co-authors and who cites them in our…" canonical: "https://research.elamur.ai/free/en/authors/shangbin-feng/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/shangbin-feng/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Shangbin Feng # Shangbin Feng Shangbin Feng has 2 papers in our library, in 2023–2024, most of them on [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/), [Reasoning](https://md.research.elamur.ai/free/en/topics/reasoning/); often with [Yulia Tsvetkov](https://md.research.elamur.ai/free/en/authors/yulia-tsvetkov/), [Chan Young Park](https://md.research.elamur.ai/free/en/authors/chan-young-park/), [Pang Wei Koh](https://md.research.elamur.ai/free/en/authors/pang-wei-koh/). 2 papers in our library · 2023–2024 [OpenAlex](https://openalex.org/A5039166924) · [ORCID](https://orcid.org/0000-0002-4133-1987) · [Wikidata](https://www.wikidata.org/wiki/Q130890072) · [**h-index 18**](https://openalex.org/authors/A5039166924) · [79 works](https://openalex.org/works?filter=author.id:A5039166924) · [1,424 citations](https://openalex.org/works?filter=author.id:A5039166924&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 2 works in our library](https://md.research.elamur.ai/free/en/authors/shangbin-feng/#papers) · [🔗 Cited 428 times in our library](https://md.research.elamur.ai/free/en/authors/shangbin-feng/cited-by/) · [9 more in our library without a page yet](#also) · [⭐ Paper Stars ranking: #3846](https://md.research.elamur.ai/free/en/paper-stars/page/39/#star-3846) 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=Shangbin+Feng) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Shangbin+Feng) · [dblp](https://dblp.org/search?q=Shangbin+Feng) · [ACL Anthology](https://aclanthology.org/search/?q=Shangbin+Feng) ## Affiliations [🎓**University of Washington** Seattle · United States 2021–2026 · 52 papers*current*](https://md.research.elamur.ai/free/en/universities/university-of-washington/) · [🏢**Microsoft** Redmond · United States 2026 · 1 paper*current*](https://md.research.elamur.ai/free/en/companies/microsoft/) · [🎓**Xi'an Jiaotong University** Xi'an · China 2021–2023 · 13 papers](https://md.research.elamur.ai/free/en/universities/xi-an-jiaotong-university/) · [🔬**Allen Institute for Artificial Intelligence** Seattle · United States 2023–2024 · 3 papers](https://md.research.elamur.ai/free/en/labs/allen-institute-for-artificial-intelligence/) · [🎓**Tsinghua University** Beijing · China 2022–2023 · 3 papers](https://md.research.elamur.ai/free/en/universities/tsinghua-university/) · [🎓**University of Virginia** Charlottesville · United States 2022–2023 · 3 papers](https://md.research.elamur.ai/free/en/universities/university-of-virginia/) · [🎓**University of Technology Sydney** Sydney · Australia 2021–2022 · 3 papers](https://md.research.elamur.ai/free/en/universities/university-of-technology-sydney/) · [🎓**Carnegie Mellon University** Pittsburgh · United States 2023–2024 · 2 papers](https://md.research.elamur.ai/free/en/universities/carnegie-mellon-university/) · [🎓**University of California San Diego** San Diego · United States 2022 · 2 papers](https://md.research.elamur.ai/free/en/universities/university-of-california-san-diego/) From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 2 more institutions on single bylines are not listed. ## Concepts, shelves and topics Of its works in our library: the number of works on each and its rating among them. 📚 Shelves 7 The field of science this work belongs to (OpenAlex fields).[Computer Science · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Artificial Intelligence · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [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/) · [Medicine · 1 work](https://md.research.elamur.ai/free/en/shelves/medicine/) · [Computer Vision and Pattern Recognition · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) · [Health Informatics · 1 work](https://md.research.elamur.ai/free/en/shelves/medicine/health-informatics/) 🧭 Topics 4 Research subjects and languages the work is about.[Bias, fairness & safety · 1 work](https://md.research.elamur.ai/free/en/topics/bias-fairness-safety/) · [Language models & pretraining · 1 work](https://md.research.elamur.ai/free/en/topics/language-models/) · [Evaluation & benchmarks · 1 work](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/) · [Reasoning · 1 work](https://md.research.elamur.ai/free/en/topics/reasoning/) ## Works by year ### 2020s [**2024** 1 paper MediQ: Question-Asking LLMs and a Benchmark for Reliable Interactive Clinical Reasoning](https://md.research.elamur.ai/free/en/papers/li-2024-mediq-question-asking-llms-benchmark/) · [**2023** 1 paper From Pretraining Data to Language Models to Downstream Tasks: Tracking the Trails of Political Biases Leading to Unfair NLP Models](https://md.research.elamur.ai/free/en/papers/feng-2023-pretraining-data-language-models-downstream/) ## Papers The most cited first (OpenAlex and our library). 1. **[From Pretraining Data to Language Models to Downstream Tasks: Tracking the Trails of Political Biases Leading to Unfair NLP Models](https://md.research.elamur.ai/free/en/papers/feng-2023-pretraining-data-language-models-downstream/)** *(2023 · 306 citations)* Large language models absorb text from news, forums, books and encyclopedias, and much of that text carries political opinions. 2. **[MediQ: Question-Asking LLMs and a Benchmark for Reliable Interactive Clinical Reasoning](https://md.research.elamur.ai/free/en/papers/li-2024-mediq-question-asking-llms-benchmark/)** *(2024 · 70 citations)* Most medical QA benchmarks give the model the whole case at once. Real consultations are different: patients often leave out details, and a clinician has to ask follow-up questions before deciding. The authors argue that LLMs are tuned to answer no matter what, which makes them unreliable when the context is… ## All works 11 works of theirs in our library, the most cited first; 2 with a page here, the others link their original until we summarise them. 1. **[From Pretraining Data to Language Models to Downstream Tasks: Tracking the Trails of Political Biases Leading to Unfair NLP Models](https://md.research.elamur.ai/free/en/papers/feng-2023-pretraining-data-language-models-downstream/)**Shangbin Feng, Chan Young Park, Yuhan Liu, et al.*[Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/) · 306 citations* 2. **[Can Language Models Solve Graph Problems in Natural Language?](https://arxiv.org/abs/2305.10037) · original ↗ · no summary yet · arXiv:2305.10037**Heng Wang et al.*2023 · 120 citations* 3. **[MediQ: Question-Asking LLMs and a Benchmark for Reliable Interactive Clinical Reasoning](https://md.research.elamur.ai/free/en/papers/li-2024-mediq-question-asking-llms-benchmark/)**Shuyue Stella Li, Vidhisha Balachandran, Shangbin Feng, et al.*[Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/) · 70 citations* 4. **[Modular Pluralism: Pluralistic Alignment via Multi-LLM Collaboration](https://aclanthology.org/2024.emnlp-main.240/) · original ↗ · no summary yet · Proceedings of the 2024 Conference on Empirical Methods in Natural Language…**Shangbin Feng et al.*2024 · 63 citations* 5. **[Resolving Knowledge Conflicts in Large Language Models](https://arxiv.org/abs/2310.00935) · original ↗ · no summary yet · arXiv:2310.00935**Yike Wang et al.*2023 · 47 citations* 6. **[Knowledge Card: Filling LLMs' Knowledge Gaps with Plug-in Specialized Language Models](https://arxiv.org/abs/2305.09955) · original ↗ · no summary yet · arXiv:2305.09955**Shangbin Feng et al.*2023 · 32 citations* 7. **[Biased LLMs can Influence Political Decision-Making](https://aclanthology.org/2025.acl-long.328/) · original ↗ · no summary yet · Proceedings of the 63rd Annual Meeting of the Association for Computational…**Jillian Fisher et al.*2025 · 20 citations* 8. **[When One LLM Drools, Multi-LLM Collaboration Rules](https://aclanthology.org/2026.acl-long.775/) · original ↗ · no summary yet · Proceedings of the 64th Annual Meeting of the Association for Computational…**Shangbin Feng et al.*2026 · 9 citations* 9. **[Bidirectional LMs are Better Knowledge Memorizers? A Benchmark for Real-world Knowledge Injection](https://aclanthology.org/2026.acl-long.771/) · original ↗ · no summary yet · Proceedings of the 64th Annual Meeting of the Association for Computational…**Yuwei Zhang et al.*2026 · 2 citations* 10. **[Legislator Representation Learning with Social Context and Expert Knowledge](https://arxiv.org/abs/2108.03881) · original ↗ · no summary yet · arXiv:2108.03881**Shangbin Feng et al.*2021 · 2 citations* 11. **[Generalizable LLM Learning of Graph Synthetic Data with Post-training Alignment](https://aclanthology.org/2026.findings-acl.586/) · original ↗ · no summary yet · Findings of the Association for Computational Linguistics: ACL 2026**Yizhuo Zhang et al.*2026* ## Co-authors here 4 co-authors with a page, the most papers together first. - [Yulia Tsvetkov](https://md.research.elamur.ai/free/en/authors/yulia-tsvetkov/) ×2 - [Chan Young Park](https://md.research.elamur.ai/free/en/authors/chan-young-park/) - [Pang Wei Koh](https://md.research.elamur.ai/free/en/authors/pang-wei-koh/) - [Vidhisha Balachandran](https://md.research.elamur.ai/free/en/authors/vidhisha-balachandran/) ## 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/) ×4: [ACL 2023](https://md.research.elamur.ai/free/en/venues/acl/2023/) - [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/): [NeurIPS 2024](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/2024/) - Findings of the Association for Computational Linguistics… - Proceedings of the 2024 Conference on Empirical Methods in… ## Cited by Papers of our library cite their works 428 times (of the 141,840 papers whose bibliographies we read); [19 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/shangbin-feng/cited-by/). Updated 24 October 2026