Excited by generation, control, and disentanglement, in either language or vision? Then check out our controllable generation workshop <https://ctrlgenworkshop.github.io/> (CtrlGen) which takes place virtually at NeurIPS 2021 <https://nips.cc/Conferences/2021/Dates> on December 13th! We feature an exciting lineup of speakers, a live QA and panel session, interactive activities, and networking opportunities. We are also inviting paper and demo submissions (read further for details).
*Workshop Website*: https://ctrlgenworkshop.github.io/ *Contact*: ctrlgenworkshop at gmail.com
*Important Dates (deadlines are 11:59pm AOE):*
- Paper Submission Deadline: *September 30, 2021*
- Demo Submission Deadline: *October 29, 2021*
- Workshop Date: *December 13, 2021*
*Submission portal:* https://cmt3.research.microsoft.com/CtrlGen2021/Submission/Index
*Full Call for Papers*: https://ctrlgenworkshop.github.io/CFP.html Paper submission deadline: *September 30, 2021*. Topics of interest include: *Methodology and Algorithms:*
- New methods and algorithms for controllability.
- Improvements of language and vision model architectures for
- Novel loss functions, decoding methods, and prompt design methods for
*Applications and Ethics:*
- Applications of controllability including creative AI, machine
co-creativity, entertainment, data augmentation (for text and vision),
ethics (e.g. bias and toxicity reduction), enhanced training for
self-driving vehicles, and improving conversational agents.
- Ethical issues and challenges related to controllable generation
including the risks and dangers of deepfake and fake news.
*Tasks (a few examples):*
- Semantic text exchange
- Syntactically-controlled paraphrase generation
- Persona-based text generation
- Style-sensitive generation or style transfer (for text and vision)
- Image synthesis and scene representation in both 2D and 3D
- Cross-modal tasks such as controllable image or video captioning and
generation from text
- New and previously unexplored controllable generation tasks!
*Evaluation and Benchmarks*
- New and improved evaluation methods and metrics for controllability
- Standard and unified metrics and benchmark tasks for controllability
*Cross-Domain and Other Areas*
- Work in interpretability, disentanglement, robustness, representation
*Position and Survey Papers*
- For example, exploring problems and lacunae in current controllability
formulations, neglected areas in controllability, and the unclear and
non-standardized definition of controllability
*Paper Submission Instructions:* Papers will be submitted using our CMT submission portal <https://cmt3.research.microsoft.com/CtrlGen2021/Submission/Index>. Submissions should be a single .pdf file that is fully anonymized, with up to 8 pages of content and unlimited references and appendices, following the NeurIPS style template. Supplementary material in the form of code and small data files can be submitted separately as a single .zip file. Accepted papers will be presented as posters and hosted on our workshop website. Note that the workshop is non-archival. While original submissions are preferred, we also welcome works currently under review, but discourage papers already accepted and published elsewhere, including at the NeurIPS main conference. *We especially encourage submissions from those with diverse backgrounds, such as minority or underrepresented groups and junior researchers.*
*Full Call for Demonstrations*: https://ctrlgenworkshop.github.io/demos.html Submission deadline: *October 29, 2021*. Demos of all forms are welcome: research-related, demos of products, interesting and creative projects, etc. We are looking for creative, well-presented, and attention-grabbing demos. Examples include:
- Creative AI such as controllable poetry, music, image, and video
- Style transfer for both text and vision.
- Interactive chatbots and assistants that involve controllability.
- Controllable language generation systems, e.g. using GPT-2 or GPT-3.
- Controllable multimodal systems such as image and video captioning or
generation from text.
- Controllable image and video/graphics enhancement systems.
- Systems for controlling scenes/environments and applications for
- Controllability in the form of deepfake and fake news, specifically
methods to combat them.
- And much, much more…
*Demo Submission Instructions:* Please record a brief (e.g. 3-5 minute) video showcasing and explaining your demo. Demonstrations will be submitted using our CMT submission portal <https://cmt3.research.microsoft.com/CtrlGen2021/Submission/Index> in a single .zip file (containing the recording). Accepted demonstrations will be presented during our workshop and hosted on our workshop website.
Organizers: Steven Feng <https://styfeng.github.io/> (CMU) Varun Gangal <https://vgtomahawk.github.io/> (CMU) Drew Hudson <https://cs.stanford.edu/people/dorarad/> (Stanford) Tatsunori Hashimoto <https://thashim.github.io/> (Stanford) Anusha Balakrishnan <https://www.microsoft.com/en-us/research/people/anbalak/> (Microsoft Semantic Machines) Dongyeop Kang <http://v/> (UMN) Joel Tetreault <https://www.cs.rochester.edu/~tetreaul/academic.html>
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