--- title: "Ruihong Huang — papers and cards" description: "Ruihong Huang: 2 paper cards in the Research library (2013–2025), with what each paper is about, the ideas Mova took from it, and the co-authors." canonical: "https://research.elamur.ai/free/en/authors/ruihong-huang/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/ruihong-huang/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Ruihong Huang # Ruihong Huang 2 paper cards in the Research library · 2013–2025 Ruihong Huang wrote 2 of the papers Mova reads, in 2013–2025, most of them on [Speech act theory](https://md.research.elamur.ai/free/en/topics/speech-act-theory/); often with Ashequl Qadir, Ayesha Qamar, [Ellen Riloff](https://md.research.elamur.ai/free/en/authors/ellen-riloff/). [OpenAlex](https://openalex.org/A5101688217) · [ORCID](https://orcid.org/0000-0002-4572-4243) · [**h-index 9**](https://openalex.org/authors/A5101688217) · [217 citations](https://openalex.org/authors/A5101688217) · [30 works](https://openalex.org/works?filter=author.id:A5101688217) — openalex-snapshot, 2026-10-14 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=Ruihong+Huang) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Ruihong+Huang) · [dblp](https://dblp.org/search?q=Ruihong+Huang) · [ACL Anthology](https://aclanthology.org/search/?q=Ruihong+Huang) · [ORCID](https://orcid.org/orcid-search/search?searchQuery=Ruihong+Huang) Topics: [Speech act theory](https://md.research.elamur.ai/free/en/topics/speech-act-theory/) 1 ## Papers 1. **[Do LLMs Understand Dialogues? A Case Study on Dialogue Acts](https://md.research.elamur.ai/free/en/papers/qamar-2025-do-llms-understand-dialogues-case/)** *(2025)* On fine-grained dialogue act classification (MRDA meetings, 50 classes; Switchboard, 43) prompted LLMs do far worse than small fine-tuned models: LLaMA-3.1-70B few-shot reaches 19 macro-F1 / 31% accuracy on MRDA against 40 / 66% for a RoBERTa model with speaker-turn modelling, and GPT-4 with audio only 28 / 42%. 2. **[Sarcasm as Contrast between a Positive Sentiment and Negative Situation](https://md.research.elamur.ai/free/en/papers/prag-2013-riloff-sarcasm-as-contrast-between-positive/)** *(2013)* The paper looks at one common form of sarcasm on Twitter: a positive sentiment verb or predicate placed just before a stereotypically negative situation. ## Co-authors (7) - Ashequl Qadir - Ayesha Qamar - [Ellen Riloff](https://md.research.elamur.ai/free/en/authors/ellen-riloff/) - Jonathan Tong - Lalindra De Silva - [Nathan Gilbert](https://md.research.elamur.ai/free/en/authors/nathan-gilbert/) - Prafulla Surve ## More papers in the library (6) Pages of the Research library: our summary, the ideas, references and who cites each. - [Hierarchical Fusion for Online Multimodal Dialog Act Classification](https://md.research.elamur.ai/free/en/papers/miah-2023-hierarchical-fusion-online-multimodal-dialog/) — Md Messal Monem Miah, Adarsh Pyarelal, Ruihong Huang · 2023 - [A Regularization Approach for Incorporating Event Knowledge and Coreference Relations into Neural Discourse Parsing](https://md.research.elamur.ai/free/en/papers/dai-2019-regularization-approach-incorporating-event-knowledge/) — Zeyu Dai, Ruihong Huang · 2019 - [Identifying the Most Dominant Event in a News Article by Mining Event Coreference Relations](https://md.research.elamur.ai/free/en/papers/choubey-2018-identifying-most-dominant-event-news/) — Prafulla Kumar Choubey, Kaushik Raju, Ruihong Huang · 2018 - [Improving Event Coreference Resolution by Modeling Correlations between Event Coreference Chains and Document Topic Structures](https://md.research.elamur.ai/free/en/papers/choubey-2018-improving-event-coreference-resolution-modeling/) — Prafulla Kumar Choubey, Ruihong Huang · 2018 - [Improving Implicit Discourse Relation Classification by Modeling Inter-dependencies of Discourse Units in a Paragraph](https://md.research.elamur.ai/free/en/papers/dai-2018-improving-implicit-discourse-relation-classification/) — Zeyu Dai, Ruihong Huang · 2018 - [Event Coreference Resolution by Iteratively Unfolding Inter-dependencies among Events](https://md.research.elamur.ai/free/en/papers/choubey-2017-event-coreference-resolution-iteratively-unfolding/) — Prafulla Kumar Choubey, Ruihong Huang · 2017