Singapore

EMNLP 2023

PR-MCS: Perturbation Robust Metric for MultiLingual Image Captioning

perturbation robustness

image captioning metric

multilingual multimodal learning

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.

Crosslingual Transfer Learning for Low-Resource Languages Based on Multilingual Colexification Graphs

A Joint Matrix Factorization Analysis of Multilingual Representations

X-SNS: Cross-Lingual Transfer Prediction through Sub-Network Similarity

Multilingual Generation and Answering of Questions from Texts and Knowledge Graphs

A Multi-Modal Multilingual Benchmark for Document Image Classification

Towards Multilingual Interlinear Morphological Glossing

Unleashing the Multilingual Encoder Potential: Boosting Zero-Shot Performance via Probability Calibration

Interpreting Indirect Answers to Yes-No Questions in Multiple Languages

BERTwich: Extending BERT’s Capabilities to Model Dialectal and Noisy Text

One For All & All For One: Bypassing Hyperparameter Tuning with Model Averaging for Cross-Lingual Transfer

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Next from EMNLP 2023

Crosslingual Transfer Learning for Low-Resource Languages Based on Multilingual Colexification Graphs

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Next from EMNLP 2023

Crosslingual Transfer Learning for Low-Resource Languages Based on Multilingual Colexification Graphs

Downloads