Singapore

EMNLP 2023

Better Handling Coreference Resolution in Aspect Level Sentiment Classification by Fine-Tuning Language Models | VIDEO

coreferenceresolution

absa

transformers

workshop paper

**Welcome to EMNLP 2023!**

On behalf of the EMNLP 2023 Organizing Committee, I extend a warm and heartfelt welcome to all of you to the 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP). It is with immense pleasure and excitement that we gather here in Singapore, a vibrant hub of innovation and technological advancement.

The conference program is packed with insightful presentations, thought-provoking workshops, and engaging networking opportunities. In addition to the technical sessions, we have also planned several social events that will provide you with the opportunity to connect with your colleagues.

The conference is held in person at the Resorts World Convention Centre in Singapore, and available on-line with the help of Underline.

For those in Singapore, I hope that you will find time to explore the exciting Sentosa Island, Gardens by the Bay, Singapore Botanic Gardens and the many other attractions unique to Singapore.

Of course, we are grateful to our sponsors and partners for their generous support of EMNLP 2023, whose contributions make it possible for us to host this world-class event.

Yuji Matsumoto (RIKEN AIP) 
EMNLP 2023 General Chair

To access the **EMNLP 2023** event page on Underline, you need to register for the Conference. 
Please follow **[this link](https://2023.emnlp.org/registration/)** for more details.

EMNLP 2023 took place in Singapore from Dec 6th to Dec 10th, 2023.

Investigating Failures to Generalize for Coreference Resolution Models

Integrated Annotation of Event Structure, Object States, and Entity Coreference

CAW-coref: Conjunction-Aware Word-level Coreference Resolution

The pragmatics of characters' mental perspectives in pronominal reference resolution

Scalar Anaphora: Annotating Degrees of Coreference in Text

Investigating Multilingual Coreference Resolution by Universal Annotations | VIDEO

Recent Computational Approaches to Coreference Resolution

Findings of the Second Shared Task on Multilingual Coreference Resolution | VIDEO

Multilingual coreference resolution: Adapt and Generate | VIDEO

Neural End-to-End Coreference Resolution using Morphological Information

https://d3smihljt9218e.cloudfront.net/transcript/59301/subtitle/ca561c7fac38881c18cd24c6f219cb75.vtt

English (automatic)

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Investigating Failures to Generalize for Coreference Resolution Models

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Next from EMNLP 2023

Investigating Failures to Generalize for Coreference Resolution Models

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