Final CFP: 1st Workshop on Controllable Generative Modeling in Language and Vision (CtrlGen 2021)
Excited by generation, control, and disentanglement, in either language or vision? Then check out our controllable generation workshop (CtrlGen) which takes place virtually at NeurIPS 2021 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 both paper and demo submissions related to controllable generation (read further for details).
Workshop Website: https://ctrlgenworkshop.github.io/
Contact: ctrlgenworkshop [at] gmail.com
Important Dates:
-Paper Submission Deadline: *September 30, 2021*
-Paper Acceptance Notification: October 22, 2021
-Paper Camera-Ready Deadline: November 1, 2021
-Demo Submission Deadline: *October 29, 2021*
-Demo Acceptance Notification: November 19, 2021
-Workshop Date: December 13, 2021
Note that the above deadlines are all 11:59pm AOE.
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 controllability.
-Novel loss functions, decoding methods, and prompt design methods for controllability.
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 learning, etc.
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 and go through double-blind review. 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.
Submission link: https://cmt3.research.microsoft.com/CtrlGen2021/Submission/Index
Full Call for Demonstrations: https://ctrlgenworkshop.github.io/demos.html
Submission deadline: October 29, 2021. Demos of all forms: research-related, demos of products, interesting and creative projects, etc. Looking for creative, well-presented, and attention-grabbing demos. Examples include:
-Creative AI such as controllable poetry, music, image, and video generation models.
-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 self-driving vehicles.
-Controllability in the form of deepfake and fake news, specifically methods to combat them.
-And much, much more…
Demonstration 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 in a single .zip file (containing the recording). Accepted demonstrations will be presented during our workshop and hosted on our workshop website. Submission link: https://cmt3.research.microsoft.com/CtrlGen2021/Submission/Index
Organizers:
-Steven Feng (CMU)
-Anusha Balakrishnan (Microsoft Semantic Machines)
-Drew Hudson (Stanford)
-Tatsunori Hashimoto (Stanford)
-Dongyeop Kang (UMN)
-Varun Gangal (CMU)
-Joel Tetreault (Dataminr)
Contact: ctrlgenworkshop [at] gmail.com