[Mova](https://md.mova.elamur.ai/free/en/) · [this page in HTML](https://mova.elamur.ai/free/en/docs/papers/authors/juntao-yu/) [home](https://md.mova.elamur.ai/free/en/) / [docs](https://md.mova.elamur.ai/free/en/docs/) / [papers](https://md.mova.elamur.ai/free/en/docs/papers/) / [authors](https://md.mova.elamur.ai/free/en/docs/papers/authors/) / Juntao Yu # Juntao Yu 4 paper cards in Mova's library · 2020–2023 Juntao Yu wrote 4 of the papers Mova reads, in 2020–2023, most of them on [Coreference resolution](https://md.mova.elamur.ai/free/en/docs/papers/topics/coreference-resolution/), [Discourse analysis](https://md.mova.elamur.ai/free/en/docs/papers/topics/discourse-analysis/); often with [Massimo Poesio](https://md.mova.elamur.ai/free/en/docs/papers/authors/massimo-poesio/), [Carolyn Rosé](https://md.mova.elamur.ai/free/en/docs/papers/authors/carolyn-rose/), [Michael Strube](https://md.mova.elamur.ai/free/en/docs/papers/authors/michael-strube/). [OpenAlex](https://openalex.org/A5003328793) · [ORCID](https://orcid.org/0000-0001-7971-9154) · [**h-index 13**](https://openalex.org/authors/A5003328793) · [954 citations](https://openalex.org/authors/A5003328793) · [47 works](https://openalex.org/works?filter=author.id:A5003328793) — openalex, 2026-10-18 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=Juntao+Yu) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Juntao+Yu) · [dblp](https://dblp.org/search?q=Juntao+Yu) · [ACL Anthology](https://aclanthology.org/search/?q=Juntao+Yu) · [ORCID](https://orcid.org/orcid-search/search?searchQuery=Juntao+Yu) Topics: [Coreference resolution](https://md.mova.elamur.ai/free/en/docs/papers/topics/coreference-resolution/) 4 · [Discourse analysis](https://md.mova.elamur.ai/free/en/docs/papers/topics/discourse-analysis/) 2 ## Ideas Mova took (1) From the ideas ledger: an idea tried, kept or queued, or measured with no gain, and what it gave. - **measured, no gain** — Implement the discourse-deixis baseline as a sieve in coref/src/sieve.rs (the disabled demonstratives slot is the place): this/that (and it as subject of happened, was true, means) not followed by a noun → the preceding clause, as an event mention with a… *([The CODI-CRAC 2022 Shared Task on Anaphora, Bridging, and…](https://md.mova.elamur.ai/free/en/docs/papers/yu-2022-codi-crac-2022-shared-task/) · deixis sieve (event «it», bare this/that → previous clause, as an added clause mention): 17 of 141 right on GUM dev, −0.76/−0.09 CoNLL gold; in coref, off by…)* ## Papers 1. **[Scoring Coreference Chains with Split-Antecedent Anaphors](https://md.mova.elamur.ai/free/en/docs/papers/paun-2023-scoring-coreference-chains-split-antecedent/)** *(2023)* Standard coreference scorers (MUC, B3, CEAF, LEA, BLANC) assume that every anaphor refers to one entity, so they cannot score split-antecedent references such as "they" for "John" and "Mary" in "John met Mary. 2. **[The CODI-CRAC 2022 Shared Task on Anaphora, Bridging, and Discourse Deixis in Dialogue](https://md.mova.elamur.ai/free/en/docs/papers/yu-2022-codi-crac-2022-shared-task/)** *(2022)* The second edition of a shared task on anaphora in dialogue, with three tasks: identity anaphora (including split antecedents and singletons), bridging reference, and discourse deixis (a pronoun such as that or this referring to an event, fact or utterance). 3. **[The CODI-CRAC 2021 Shared Task on Anaphora, Bridging, and Discourse Deixis in Dialogue](https://md.mova.elamur.ai/free/en/docs/papers/khosla-2021-codi-crac-2021-shared-task/)** *(2021)* The shared task asks systems to find anaphoric relations in conversation, a genre that OntoNotes-style corpora barely cover. 4. **[Free the Plural: Unrestricted Split-Antecedent Anaphora Resolution](https://md.mova.elamur.ai/free/en/docs/papers/yu-2020-free-plural-unrestricted-split-antecedent/)** *(2020)* Most coreference systems give a mention one antecedent, so «John met Mary. They had a chat» cannot be resolved: they refers to two separately introduced entities. The paper builds the first model for this split-antecedent case in general, on ARRAU (news, dialogue, fiction, medical; 507 training anaphors), with gold… ## Co-authors (9) - [Massimo Poesio](https://md.mova.elamur.ai/free/en/docs/papers/authors/massimo-poesio/) ×4 - [Carolyn Rosé](https://md.mova.elamur.ai/free/en/docs/papers/authors/carolyn-rose/) ×2 - [Michael Strube](https://md.mova.elamur.ai/free/en/docs/papers/authors/michael-strube/) ×2 - [Nafise Sadat Moosavi](https://md.mova.elamur.ai/free/en/docs/papers/authors/nafise-sadat-moosavi/) ×2 - [Ramesh Manuvinakurike](https://md.mova.elamur.ai/free/en/docs/papers/authors/ramesh-manuvinakurike/) ×2 - [Silviu Paun](https://md.mova.elamur.ai/free/en/docs/papers/authors/silviu-paun/) ×2 - [Sopan Khosla](https://md.mova.elamur.ai/free/en/docs/papers/authors/sopan-khosla/) ×2 - [Vincent Ng](https://md.mova.elamur.ai/free/en/docs/papers/authors/vincent-ng/) ×2 - [Lori Levin](https://md.mova.elamur.ai/free/en/docs/papers/authors/lori-levin/) - [← previous Jun'ichi Tsujii](https://md.mova.elamur.ai/free/en/docs/papers/authors/jun-ichi-tsujii/) - [next → Junyi Jessy Li](https://md.mova.elamur.ai/free/en/docs/papers/authors/junyi-jessy-li/) - [↑ back to Authors](https://md.mova.elamur.ai/free/en/docs/papers/authors/)