{"id":12373,"date":"2024-01-04T21:21:40","date_gmt":"2024-01-04T21:21:40","guid":{"rendered":"https:\/\/dsrc.haifa.ac.il\/?page_id=12373"},"modified":"2024-01-04T22:00:28","modified_gmt":"2024-01-04T22:00:28","slug":"colloquium-democratising-natural-language-processing-overcoming-language-and-domain-barriers-in-low-resource-environments-11-1-2024","status":"publish","type":"page","link":"https:\/\/dsrc.haifa.ac.il\/?page_id=12373","title":{"rendered":"Colloquium – Democratising Natural Language Processing: Overcoming Language and Domain Barriers in Low-Resource Environments, 11.1.2024"},"content":{"rendered":"\t\t
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Democratising Natural Language Processing: Overcoming Language and Domain Barriers in Low-Resource Environments\n\n<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Dr. Yftah Ziser, University of Edinburgh <\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Natural language processing (NLP) has been revolutionised in recent years to the point where it is an inseparable part of our daily lives. The transition to transformer-based models allows us to train models on vast amounts of text efficiently, proving that scale plays a crucial role in improving performance. Unfortunately, many people worldwide are marginalised from getting access to high-quality NLP models, as the language they speak and the domains they are interested in count for only a tiny fraction of current state-of-the-art models’ training sets.<\/p>

This talk will address the challenges, approaches, and opportunities for democratising NLP across different languages and domains by developing methods to improve NLP in low-resource scenarios. I will start by discussing how we can ease distribution mismatches to improve performance using representation learning. However, as NLP models become increasingly present in our lives, improving other crucial aspects beyond their performance, such as their fairness, factuality, and our ability to understand their underlying mechanisms, is essential. Therefore, I will also discuss using spectral methods to remove information from neural networks to reduce undesired attributes, such as bias, to increase fairness where sensitive data is scarce. Finally, I will explore future directions for making these models accessible toa broader audience by improving the aspects mentioned above in low-resource scenarios.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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Dr. Yftah Ziser <\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Yftah Ziser is a Postdoctoral Researcher at the School of Informatics at Edinburgh University, hosted by Shay Cohen. He focuses on Deep-Learning methods for dealing with the resource bottleneck, which seriously challenges the worldwide accessibility of NLP technology. His research develops methods to improve low-resource models’ performance, fairness, and factuality while developing analysis methods for deepening our understanding of them. He co-organized the Domain Adaptation for NLP Workshop at EACL 2021.<\/p>

Before joining the University of Edinburgh, Yftah worked as a research scientist at Amazon Alexa. Yftah obtained his PhD from the Technion, where he was advised by Roi Reichart.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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Dr. Yftah Ziser<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Yftah Ziser is a Postdoctoral Researcher at the School of Informatics at Edinburgh University, hosted by Shay Cohen. He focuses on Deep-Learning methods for dealing with the resource bottleneck, which seriously challenges the worldwide accessibility of NLP technology. His research develops methods to improve low-resource models’ performance, fairness, and factuality while developing analysis methods for deepening our understanding of them. He co-organized the Domain Adaptation for NLP Workshop at EACL 2021.<\/p>

Before joining the University of Edinburgh, Yftah worked as a research scientist at Amazon Alexa. Yftah obtained his PhD from the Technion, where he was advised by Roi Reichart.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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A Social computing platform for Biodiversity monitoring\n\n<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Weaam Shaheen & Lior Koren <\/a><\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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In this talk, we aim to explore the utilization of human computation and machine learning techniques to expedite and enhance the tedious tasks faced by ecologists in monitoring biodiversity. By working towards the integration of human and machine intelligence, our intermediate goal is to create a crowd-computing platform accessible for citizen scientists, allowing them to augment or even substitute the efforts of a single expert, thereby expediting the process considerably.<\/span><\/p>

Should our system prove successful, it will enable ecologists to harness algorithms and crowdsourced assistance to produce accurate and prompt assessments of nature’s status. Such data will be crucial for conservation organizations and authorities in formulating effective measures. Additionally, this approach is expected to strengthen the connection between citizen scientists and nature, while raising awareness about the importance of wildlife sustainability.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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Democratising Natural Language Processing: Overcoming Language and Domain Barriers in Low-Resource Environments Dr. Yftah Ziser, University of Edinburgh Natural language processing (NLP) has been revolutionised in recent years to the point where it is an inseparable part of our daily lives. The transition to transformer-based models allows us to train models on vast amounts of […]<\/p>\n","protected":false},"author":93,"featured_media":0,"parent":531,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"elementor_header_footer","meta":{"_acf_changed":false,"_eb_attr":"","_templately_pack_id":"","_templately_imported_at":"","_templately_source":"","_templately_import_session_id":"","footnotes":""},"class_list":["post-12373","page","type-page","status-publish","hentry","entry"],"acf":[],"aioseo_notices":[],"aioseo_head":"\n\t\t\n\t\n\t\n\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t