NAACL2021 Workshop on Multimodal Artificial Intelligence (MAI-Workshop)

COVID-19 Disclaimer:

We hope everyone and their loved ones are staying safe during the COVID-19 pandemic. The workshop will be available as part of NAACL 2021 online broadcasting system. 

Scope

The NAACL 2021 Workshop on Multimodal Artificial Intelligence (MAI-Workshop) offers a unique opportunity for interdisciplinary researchers to study and model interactions between (but not limited to) modalities of language, vision, and acoustic. Advances in multimodal learning allows the field of NLP to take the leap towards better generalization to real-world (as opposed to limitation to textual applications), and better downstream performance in Conversational AI, Virtual Reality, Robotics, HCI, Healthcare, and Education.

We invite researchers from NLP, Computer Vision, Speech Processing, Robotics, HCI, and Affective Computing to submit their papers.

• • Neural Modeling of Multimodal Language
• • Multimodal Dialogue Modeling and Generation
• • Multimodal Sentiment Analysis and Emotion Recognition
• • Language, Vision and Speech
• • Multimodal Artificial Social Intelligence Modeling
• • Multimodal Commonsense Reasoning
• • Multimodal RL and Control (Human-robot communication and multimodal language for robots)
• • Multimodal Healthcare
• • Multimodal Educational Systems
• • Multimodal Affective Computing
• • Multimodal Fusion and Alignment
• • Multimodal Representation Learning
• • Multimodal Sequential Modeling
• • Multimodal Co-learning and Transfer Learning
• • Multimodal Active Learning
• • Multimodal and Multimedia Resources
• • Creative Applications of Multimodal Learning in E-commerce, Art, and other Impactful Areas.

Keynotes

Speaker: Kristen Grauman – University of Texas at Austin (USA)

Speaker: Anind Dey – University Washington (USA)

Speaker: Emily Mower Provost – University of Michigan (USA)

Speaker: Marcus Rohrbach – Facebook AI Research (USA)

Speaker: Xin (Eric) Wang – University of California Santa Cruz (USA)

Workshop Track

CLICK TO SUBMIT YOUR PAPER HERE

Archival Track: Workshop papers are either full (8 pages) or short (4 pages) papers with infinite references. The formatting instructions are identical to NAACL 2021 paper format. ACL guidelines suggest papers should be self-contained, with high presentation quality and properly compared to previous works. Publications related to all areas above are welcome to submit a paper. The submission should have at least two modalities present in their experiments (i.e. works should be related to multimodal learning). The workshop track encourages creative applications of multimodal learning, over new or understudied datasets.

All accepted papers will be presented during poster sessions at the workshop. Selected papers will also be invited as contributed talks. All the papers (full or short) will be indexed as part of the NAACL 2021 workshop proceedings. All submitted material should be considered novel at the time of submission. Further results and experiments on existing works is also acceptable for submission.

Submission template: https://2021.naacl.org/calls/papers/
 

Non-archival Track: The workshop also includes a non-archival track to allow submission of previously published papers and double submissions to other conferences or journals. Accepted non-archival papers will still be presented as posters or talks at the workshop. There are no formatting or page restrictions for non-archival submissions. The accepted papers to the non-archival track will be displayed on the workshop website, but will NOT be included in the NAACL 2021 Workshop proceedings or otherwise archived.

Important Dates

• Deadline for all submissions extended to March 25th. 

• March 25th: Deadline for all submissions

**All deadlines @11:59 pm anywhere on Earth – year 2020**

Schedule (PDT Timezone)

(ALL PDT TIMEZONE)

9:00 – 9:10 Introduction and Remarks
9:10 – 9:55 Invited Speaker #1 – Xin (Eric) Wang
9:55 – 10:10 QA #1
10:10 – 10:55 Invited Speaker #2 – Anind Dey
10:55 – 11:10 QA #2
11:10 – 11:55: Invited Speaker #3 – Emily Mower Provost
11:55 – 12:10: QA #3
12:10 – 12:30 Beak
12:30 – 1:15 Invited Speaker #4 – Marcus Rohrbach
1:15 – 1:30 QA #4
1:30 – 2:15 Invited Speaker #5 – Kristen Grauman
2:15 – 2:30 QA #5
2:30-4:00 Poster Session

Organizing Committee

	Amir Zadeh – Language Technologies Institute, Carnegie Mellon University
	Louis-Philippe Morency – Language Technologies Institute, Carnegie Mellon University
	Paul Pu Liang – Machine Learning Department, Carnegie Mellon University
	Jed Yang – Carnegie Mellon University
	Candace Ross – Massachusetts Institute of Technology
	Ruslan Salakhutdinov – Carnegie Mellon University
	Soujanya Poria – Singapore University of Technology and Design
	Erik Cambria – Nanyang Technological University
	Kelly Shi – Carnegie Mellon University