We welcome full paper submissions (around 8 pages, excluding references or supplementary resources). The paper submissions has to be in pdf structure and make use of the AAAI official templates. All submissions must be nameless and conform to AAAI specifications for double-blind critique.
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We invite papers that concentrate on various facets of mitigating misinformation created by LLMs. Subjects of curiosity include (but are usually not restricted to):
Expressivity of tensor representations such as exponential lower bounds of matrix ranks and circuit dimensions and sample complexity of figured out representations;
In addition, provide a notebook for having notes, concerns you ought to talk to and an open up attitude willing to study and network.
Both of those paper and poster submissions will be peer-reviewed. Papers could be accepted for presentation as a chat along with a poster or only as being a poster.
The internet pages involve references and any appendices. Extra steerage within the submissions is in the Workshop Web-site. The review procedure will likely be one blind.
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Lastly, the workshop will welcome papers that describe the discharge of privateness-preserving benchmarks and info sets which might be utilized by the community to unravel elementary challenges of curiosity, including in equipment Understanding and optimization for wellbeing techniques and concrete networks, to mention but a couple of illustrations.
This can be a url into the workshop Internet site. We are going to polish it and populate it with all specifics shortly:
All submissions will bear a double-blind peer critique course of action. Each and every paper are going to be reviewed by at the least two associates of the program committee determined by its originality, relevance to your workshop, technical soundness, and clarity of presentation.
Innovations in complex engineering units for instance production and supplies synthesis increasingly find artificial intelligence/machine Discovering (AI/ML) remedies to enhance their design and style, growth, and output processes. Having said that, Even with increasing curiosity from different subfields, AI/ML techniques are nevertheless to satisfy their complete promise in acquiring these advancements. Important obstructions include not enough substantial-high-quality knowledge, issue in embedding complicated scientific and engineering information in Studying, and here the need for top-dimensional style Room exploration beneath constrained budgets.
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We also welcome contributions that use current benchmarks to display basic safety or AI systems or locate unsafe behaviors.