--- title: "Vincent Ng — papers, page 2 — Elamur Research" description: "Vincent Ng: 44 papers on Elamur Research (2002–2026), h-index 46 — affiliations, topics, co-authors and who cites them in our library." canonical: "https://research.elamur.ai/free/en/authors/vincent-ng/page/2/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/vincent-ng/page/2/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Vincent Ng](https://md.research.elamur.ai/free/en/authors/vincent-ng/) / page 2 # Vincent Ng · page 2 44 papers in our library · 2002–2026 · page 2 of 2 [The profile, affiliations and co-authors →](https://md.research.elamur.ai/free/en/authors/vincent-ng/) ## Papers The most cited first (OpenAlex and our library). [← prev](https://md.research.elamur.ai/free/en/authors/vincent-ng/) [1](https://md.research.elamur.ai/free/en/authors/vincent-ng/) **2** 26. **[Joint Inference for Event Coreference Resolution](https://md.research.elamur.ai/free/en/papers/lu-2016-joint-inference-event-coreference-resolution/)** *(2016 · 46 citations)* Resolving which event mentions in a document describe the same real-world event is difficult. Event coreference sits near the end of the information extraction pipeline, so it inherits errors from earlier steps such as trigger detection, argument extraction and entity coreference. The authors argue that modelling… 27. **[Chinese Zero Pronoun Resolution: A Joint Unsupervised Discourse-Aware Model Rivaling State-of-the-Art Resolvers](https://md.research.elamur.ai/free/en/papers/chen-2015-chinese-zero-pronoun-resolution-joint/)** *(2015 · 39 citations)* Chinese often leaves an argument unexpressed: a zero pronoun (ZP) is a silent slot that may refer back to an earlier mention. 28. **[SinoCoreferencer: An End-to-End Chinese Event Coreference Resolver](https://md.research.elamur.ai/free/en/papers/chen-2014-sinocoreferencer-end-end-chinese-event/)** *(2014 · 32 citations)* Event coreference resolution groups event mentions in a text that describe the same real-world happening. It sits at the very end of an information extraction pipeline, and almost all prior systems target English. The authors present SinoCoreferencer, an end-to-end resolver for Chinese that follows the ACE task… 29. **[Constrained Multi-Task Learning for Event Coreference Resolution](https://md.research.elamur.ai/free/en/papers/lu-2021-constrained-multi-task-learning-event/)** *(2021 · 28 citations)* Event coreference resolution asks whether two event mentions in a document describe the same real-world event. 30. **[Learning the Information Status of Noun Phrases in Spoken Dialogues](https://md.research.elamur.ai/free/en/papers/rahman-2011-learning-information-status-noun-phrases/)** *(2011 · 26 citations)* The paper tackles automatic information-status classification: deciding whether a noun phrase in a conversation is old (already mentioned or tied to the dialogue participants), mediated (inferable from earlier material or generally known), or new to the hearer. 31. **[Conundrums in Entity Coreference Resolution: Making Sense of the State of the Art](https://md.research.elamur.ai/free/en/papers/lu-2020-conundrums-entity-coreference-resolution-making/)** *(2020 · 25 citations)* Neural entity coreference resolvers have achieved large score gains with fairly simple architectures: a mention-ranking model over contextualized embeddings with learned span representations. 32. **[Bridging Resolution: A Survey of the State of the Art](https://md.research.elamur.ai/free/en/papers/kobayashi-2020-bridging-resolution-survey-state-art/)** *(2020 · 24 citations)* Bridging resolution connects an anaphor to an antecedent that is related to it but does not refer to the same entity. 33. **[Conundrums in Event Coreference Resolution: Making Sense of the State of the Art](https://md.research.elamur.ai/free/en/papers/lu-2021-conundrums-event-coreference-resolution-making/)** *(2021 · 23 citations)* Span-based neural models have recently set new records in event coreference resolution (CR), but it is unclear where their gains come from. 34. **[Chinese Event Coreference Resolution: An Unsupervised Probabilistic Model Rivaling Supervised Resolvers](https://md.research.elamur.ai/free/en/papers/chen-2015-chinese-event-coreference-resolution-unsupervised/)** *(2015 · 20 citations)* Resolving which event mentions in a document describe the same real-world happening is hard. It is even harder for Chinese, which has received little research attention and lacks large lexical resources comparable to WordNet or FrameNet, which have helped English systems. Chen and Ng address within-document Chinese… 35. **[Chinese Zero Pronoun Resolution: An Unsupervised Probabilistic Model Rivaling Supervised Resolvers](https://md.research.elamur.ai/free/en/papers/chen-2014-chinese-zero-pronoun-resolution-unsupervised/)** *(2014 · 17 citations)* The paper addresses anaphoric zero pronoun (AZP) resolution in Chinese, which means linking an omitted subject to an earlier noun phrase. 36. **[Linguistically Aware Coreference Evaluation Metrics](https://md.research.elamur.ai/free/en/papers/chen-2013-linguistically-aware-coreference-evaluation-metrics/)** *(2013 · 16 citations)* Standard coreference scorers (MUC, B3, CEAF) treat mentions as interchangeable items, so any clustering task could be scored with them. 37. **[Bridging Resolution: Making Sense of the State of the Art](https://md.research.elamur.ai/free/en/papers/kobayashi-2021-bridging-resolution-making-sense-state/)** *(2021 · 15 citations)* Bridging resolution means linking an anaphor to a related but non-identical antecedent, as in "the games" linked to "baseball." Yu and Poesio's (2020) neural multi-task learning (MTL) model, trained jointly on coreference and bridging, is the current state of the art. 38. **[The CODI-CRAC 2022 Shared Task on Anaphora, Bridging, and Discourse Deixis in Dialogue](https://md.research.elamur.ai/free/en/papers/yu-2022-codi-crac-2022-shared-task/)** *(2022 · 14 citations)* 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). 39. **[Chinese Event Coreference Resolution: Understanding the State of the Art](https://md.research.elamur.ai/free/en/papers/chen-2013-chinese-event-coreference-resolution-understanding/)** *(2013 · 13 citations)* The paper asks why event coreference, the task of linking mentions of the same real-world event, remains hard, using Chinese as a test case. 40. **[The CODI-CRAC 2021 Shared Task on Anaphora, Bridging, and Discourse Deixis Resolution in Dialogue: A Cross-Team Analysis](https://md.research.elamur.ai/free/en/papers/li-2021-codi-crac-2021-shared-task/)** *(2021 · 7 citations)* CODI-CRAC 2021 was the first shared task devoted entirely to anaphora resolution in dialogue. It had three tracks: entity coreference, bridging, and discourse deixis. The last two are rarely studied, especially for conversational data. This paper compares the participating systems across teams, combining statistics… 41. **[PairSpanBERT: An Enhanced Language Model for Bridging Resolution](https://md.research.elamur.ai/free/en/papers/kobayashi-2023-pairspanbert-enhanced-language-model-bridging/)** *(2023 · 6 citations)* Bridging resolution means finding anaphors that relate to an earlier entity through a non-identity link, such as part-whole or attribute, and connecting them to that antecedent. 42. **[Universal Anaphora: The First Three Years](https://md.research.elamur.ai/free/en/papers/poesio-2024-universal-anaphora-first-three-years/)** *(2024 · 4 citations)* Coreference work in NLP has long revolved around OntoNotes. That corpus centres on identity coreference in a limited set of genres and leaves out singletons, expletives and many harder phenomena. Universal Anaphora (UA) began in 2020 and is modelled on Universal Dependencies. It aims to coordinate research on… 43. **[End-to-End Neural Bridging Resolution](https://md.research.elamur.ai/free/en/papers/kobayashi-2022-end-end-neural-bridging-resolution/)** *(2022 · 3 citations)* Bridging resolution means finding anaphoric noun phrases tied to an earlier mention by a non-identity relation (for example, "ruling-party members" depends on "Japan") and linking each to that antecedent. 44. **[RBR: RAG-Based Open-Domain Question Answering Using a Ranking Approach to Document Retrieval](https://md.research.elamur.ai/free/en/papers/naravajhula-2026-rbr-rag-based-open-domain/)** *(2026)* Open-domain question answering (ODQA) systems based on Retrieval-Augmented Generation (RAG) combine two parts. [← prev](https://md.research.elamur.ai/free/en/authors/vincent-ng/) [1](https://md.research.elamur.ai/free/en/authors/vincent-ng/) **2**