Singapore

EMNLP 2023

Leveraging Large Language Models for Enhanced Product Descriptions in eCommerce

product description enhancement

large language models

e-commerce

ICPR 2020 is the premier international conference on Pattern Recognition, gathering leading researchers from around the world to present their latest achievements in Pattern Analysis and Recognition, applied Artificial Intelligence and Machine Learning. The topic of the year is " Putting Artificial intelligence to work on Patterns". 
For the first time, ICPR has employed a two-round review process similar to journal submissions, with new papers allowed to be submitted in either the first or second round and papers submitted in the first round and not accepted allowed to be revised and re-submitted for second round review. 

In this edition of the **ICPR 2020** Conference, there are 1407 Oral/Poster presentations organized in five Tracks: 
- Artificial Intelligence, Machine Learning for Pattern Analysis; 
- Biometrics, Human Analysis and Behavior Understanding; Computer Vision, Robotics and Intelligent Systems; 
- Document and Media Analysis; and 
- Image and Signal Processing. 

The **ICPR 2020** Main Conference program also includes 7 Keynotes from prominent world-renowned scientists, 8 Tutorials, 28 Demos, 8 Challenges, 2 Panels, as well as an Industry/Sponsor Exhibition. In addition, 41 Workshops on a range of important current and emerging research topics complete the ICPR 2020 program. 


ICPR 2020

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.

Separating the Wheat from the Chaff with BREAD: An open-source benchmark and metrics to detect redundancy in text

MacLaSa: Multi-Aspect Controllable Text Generation via Efficient Sampling from Compact Latent Space

Can Large Language Models Fix Data Annotation Errors? An Empirical Study Using Debatepedia for Query-Focused Text Summarization

Uniform Complexity for Text Generation

Unraveling Downstream Gender Bias from Large Language Models: A Study on AI Educational Writing Assistance

A Comprehensive Evaluation of Tool-Assisted Generation Strategies

Harnessing the power of LLMs: Evaluating human-AI text co-creation through the lens of news headline generation

InfoDiffusion: Information Entropy Aware Diffusion Process for Non-Autoregressive Text Generation

Ask To The Point: Open-Domain Entity-Centric Question Generation

NLP Evaluation in trouble: On the Need to Measure LLM Data Contamination for each Benchmark

https://d3smihljt9218e.cloudfront.net/transcript/59357/subtitle/080cab6eeace80fc4c1d3c6e2492eda4.vtt

English (automatic)

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Separating the Wheat from the Chaff with BREAD: An open-source benchmark and metrics to detect redundancy in text

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Solution for Product-10k Challenge:Large-scale Product Recognition

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Next from EMNLP 2023

Separating the Wheat from the Chaff with BREAD: An open-source benchmark and metrics to detect redundancy in text

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Solution for Product-10k Challenge:Large-scale Product Recognition

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