--- title: "Ming Xiang · University of Chicago — author profile and papers" description: "Ming Xiang, University of Chicago: 2 papers on Elamur Research (2022), h-index 2 — affiliations, topics, co-authors and who cites them in…" canonical: "https://research.elamur.ai/free/en/authors/ming-xiang/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/ming-xiang/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Ming Xiang # Ming Xiang Ming Xiang has 2 papers in our library, in 2022, most of them on [Reasoning](https://md.research.elamur.ai/free/en/topics/reasoning/); often with [Christopher Kennedy](https://md.research.elamur.ai/free/en/authors/christopher-kennedy/), [Wei Liu](https://md.research.elamur.ai/free/en/authors/wei-liu/). 2 papers in our library · 2022 [OpenAlex](https://openalex.org/A5034975534) · [**h-index 2**](https://openalex.org/authors/A5034975534) · [9 works](https://openalex.org/works?filter=author.id:A5034975534) · [11 citations](https://openalex.org/works?filter=author.id:A5034975534&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 2 works in our library](https://md.research.elamur.ai/free/en/authors/ming-xiang/#papers) · 🔗 Cited 4 times in our library · [⭐ Paper Stars ranking: #5882](https://md.research.elamur.ai/free/en/paper-stars/page/59/#star-5882) 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=Ming+Xiang) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Ming+Xiang) · [dblp](https://dblp.org/search?q=Ming+Xiang) · [ACL Anthology](https://aclanthology.org/search/?q=Ming+Xiang) ## Affiliations [🎓**University of Chicago** Chicago · United States 2019–2026 · 8 papers*current*](https://md.research.elamur.ai/free/en/universities/university-of-chicago/) From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. ## 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).[Arts and Humanities · 2 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [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/) · [Language and Linguistics · 2 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) · [Computer Vision and Pattern Recognition · 1 work](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 1 Research subjects and languages the work is about.[Reasoning · 2 works](https://md.research.elamur.ai/free/en/topics/reasoning/) ## Works by year ### 2020s [**2022** 2 papers Ming Xiang's papers of 2022](https://md.research.elamur.ai/free/en/authors/ming-xiang/year/2022/) ## Papers The most cited first (OpenAlex and our library). 1. **[Simple but Challenging: Natural Language Inference Models Fail on Simple Sentences](https://md.research.elamur.ai/free/en/papers/luo-2022-simple-but-challenging-natural-language/)** *(2022 · 7 citations)* Transformer models fine-tuned on SNLI and MNLI reach high accuracy, but it is unclear whether they actually reason about sentence meaning or exploit dataset artifacts. 2. **[Pragmatic reasoning and semantic convention: A case study on gradable adjectives](https://md.research.elamur.ai/free/en/papers/xiang-2022-pragmatic-reasoning-semantic-convention-case/)** *(2022 · 4 citations)* The paper asks how listeners handle unmodified gradable adjectives ("long", "empty", "bent"), whose cutoff point is set by context and often uncertain. ## Co-authors here 2 co-authors with a page, the most papers together first. - [Christopher Kennedy](https://md.research.elamur.ai/free/en/authors/christopher-kennedy/) - [Wei Liu](https://md.research.elamur.ai/free/en/authors/wei-liu/) ## 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/): [Findings of the Association for Computational Linguistics 2022](https://md.research.elamur.ai/free/en/venues/findings/2022/) - [Semantics and Pragmatics](https://md.research.elamur.ai/free/en/venues/semantics-and-pragmatics/): [Semantics and Pragmatics 2022](https://md.research.elamur.ai/free/en/venues/semantics-and-pragmatics/2022/) ## Cited by Papers of our library cite their works 4 times (of the 141,840 papers whose bibliographies we read). Updated 24 October 2026