NLP for Conversational AI
Co-located with ACL 2022
Over the past decades, mathematicians, linguists, and computer scientists have dedicated their efforts towards empowering human-machine communication in natural language. While in recent years the emergence of virtual personal assistants such as Siri, Alexa, Google Assistant, and Cortana has pushed the field forward, the development of such conversational agents remains difficult with numerous unanswered questions and challenges.
Following the success of the 3rd NLP for Conversational AI workshop at EMNLP, "The 4th NLP4ConvAI” will be a one-day workshop, co-located with ACL 2022 in Dublin. The goal of this workshop is to bring together researchers and practitioners to discuss impactful research problems in this area, share findings from real-world applications, and generate ideas for future research directions.
The workshop will include keynotes, posters, and panel sessions. In keynote talks, senior technical leaders from industry and academia will share insights on the latest developments in the field. We would like to encourage researchers and students to share their prospects and latest discoveries. There will also be a panel discussion with noted conversational AI leaders focused on the state of the field, future directions, and open problems across academia and industry.
Sound exciting? We are looking forward to seeing you!
2022/05/26: Best paper awards announced! Check it out here!
2022/05/01: Published the workshop program. Check it out here!
2022/03/28: The acceptance decision for direct submissions is now available in OpenReview. The decision entry for ARR submissions is
delayed due to some technical issue. We have contacted OpenReview and will fix it asap.now available in OpenReview (3/30).
2022/02/28: Extended the ARR commitment deadline (paper with review) to March 4th, 2022 (23:59 GMT-12).
2022/02/14: Final Call for Paper, with updated submission deadline (Feb 28th) for papers submitted directly to the workshop.
2022/01/10: Updated the CFP to also accept submissions through the ACL Rolling Review. Check the guideline and timeline here.
2021/12/30: First Call for Papers is out! Check it out here.
February 18th, 2022--> February 28th, 2022 (23:59 GMT-12)
Through ARR (with reviews):
February 2 8th, 2022--> March 4th, 2022 (23:59 GMT-12)
Notification of Paper Acceptance: March 28th, 2022
Camera-Ready Paper Due: April 8th, 2022
Workshop Date: May 27th, 2022
Keynote: Past, Present, Future of Conversational AI
Recent advances in deep learning based methods for language processing, especially using self-supervised learning methods resulted in new excitement towards building more sophisticated Conversational AI systems. While this is partially true for social chatbots or retrieval-based applications, it is commonplace to see dialogue processing as yet another task while assessing these new state of the art approaches. In this talk, I will argue that Conversational AI comes with an orthogonal methodology for machine learning to complement such methods interacting with the users using implicit and explicit signals. This is an exceptional opportunity for Conversational AI research moving forward and I will present couple representative efforts from Alexa AI.
Keynote: Directions of Dialog Research in the Era of Big Pre-training Models
Big pre-training models (such as BERT and GPT3) have demonstrated excellent performances on various NLP tasks. Instruction tuning and prompting have enabled these models to shine in low-resource settings. The natural question is “Will big models solve dialog tasks?” This talk will first go through big models’ impact on several sub-topics within dialog systems (e.g. social chatbots, task-oriented dialog systems, negotiation/persuasion dialog systems, continue learning in dialog systems, multilingual dialog systems, multimodal dialog systems, deployable dialog systems, etc) and then follow up with the speaker's own interpretations of the challenges remaining and possible future directions.
Keynote: HybriDialogue: Towards Information-Seeking Dialogue Reasoning Grounded on Tabular and Textual Data
A pressing challenge in current dialogue systems is to successfully converse with users on topics with information distributed across different modalities. Previous work in multi-turn dialogue systems has primarily focused on either text or table information. In more realistic scenarios, having a joint understanding of both is critical as knowledge is typically distributed over both unstructured and structured forms. In this talk, I will present a new dialogue dataset, HybriDialogue, which consists of crowdsourced natural conversations grounded on both Wikipedia text and tables. The conversations are created through the decomposition of complex multihop questions into simple, realistic multiturn dialogue interactions. We conduct several baseline experiments, including retrieval, system state tracking, and dialogue response generation. Our results show that there is still ample opportunity for improvement, demonstrating the importance of building stronger dialogue systems that can reason over the complex setting of information-seeking dialogue grounded on tables and text. I will also briefly mention a few related studies on dialogue research from the UCSB NLP Group.
Keynote: Scaling impact: the case for humanitarian NLP
Advances in core NLP capabilities have enabled an extensive variety of scenarios where conversational AI provides real value for companies and customers alike. Leveraging lessons learned from these successes to applying the technology in the humanitarian context requires an understanding of both the potential for impact and risk of misuse.
Maria-Georgia Zachari, Omilia
Keynote: Dialog Management for Conversational Task-Oriented Industry Solutions
This talk will focus on how the Omilia Cloud Platform® leverages the notion of Dialog Act in order to solve real-life use cases in task-oriented dialog systems for call centers. We will address the challenge of completing tasks efficiently, achieving high KPIs and integrating with a call center, while at the same time building and maintaining a flexible conversational NLU system.