Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing: Tutorial Abstracts
Crowdsourcing Beyond Annotation: Case Studies in Benchmark Data Collection (2021.emnlp-tutorials)
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| Challenge: | Developing a theory of crowdsourcing for practical language problems remains an open challenge . |
| Approach: | This tutorial exposes NLP researchers to data collection crowdsourcing methods and principles through case studies. |
| Outcome: | This tutorial exposes NLP researchers to various data collection crowdsourcing methods and practices through case studies. |
Financial Opinion Mining (2021.emnlp-tutorials)
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| Challenge: | This tutorial will provide an overview of financial opinion mining and provide research directions. |
| Approach: | This tutorial will introduce financial opinion mining and examine possible research directions. |
| Outcome: | This tutorial aims to provide an overview of financial opinion mining and figure out research directions. |
Knowledge-Enriched Natural Language Generation (2021.emnlp-tutorials)
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| Challenge: | Knowledge-enriched text generation poses unique challenges in modeling and learning . a roadmap will outline the state-of-the-art methods to tackle these challenges . |
| Approach: | They propose a roadmap to tackle the challenges of knowledge-enriched text generation . they will dive deep into various technical components to illustrate how to represent knowledge . |
| Outcome: | This tutorial outlines the state-of-the-art methods to tackle the problem . it aims to show how to represent knowledge, feed knowledge into a generation model, evaluate results . |
Multi-Domain Multilingual Question Answering (2021.emnlp-tutorials)
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| Challenge: | Question answering (QA) is one of the most challenging tasks in natural language processing. |
| Approach: | a tutorial examines the state-of-the-art approaches to multi-domain and multilingual QA . they introduce standard benchmarks and discuss out-of the-box training with open-domain QA systems . |
| Outcome: | This tutorial aims to bridge the gap between open-domain and multilingual QA. |
Robustness and Adversarial Examples in Natural Language Processing (2021.emnlp-tutorials)
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| Challenge: | This tutorial aims to raise awareness of practical concerns about NLP robustness . it aims at addressing the weaknesses of NLP systems when faced with adversarial inputs and data with a distribution shift . |
| Approach: | This tutorial aims to bring awareness of practical concerns about NLP robustness . it reviews recent studies on analyzing the weakness of NLP systems when facing adversarial inputs . |
| Outcome: | This tutorial aims to bring awareness of practical concerns about NLP robustness . it will examine the weaknesses of NLP systems when faced with adversarial inputs and data with a distribution shift . |
Syntax in End-to-End Natural Language Processing (2021.emnlp-tutorials)
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| Challenge: | tutorial focuses on syntactic parsing and syntax in end-to-end natural language processing (NLP) tasks. |
| Approach: | tutorial will introduce syntactic parsing and the role of syntax in end-to-end natural language processing (NLP) tasks. |
| Outcome: | This tutorial will introduce the background and the latest progress of syntactic parsing and SRL/NMT. |