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4,299,418 works, Canadian by any of four routes.

Every filter state is a URL; the URL is the query; the query is citable via /q/⟨hash⟩. The page, the API and the export parse the same parameters.

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The current cohort, streamed from the database: every work column, the machine labels, the provisional scores, and the per-row validation status. Exports are capped at 100,000 rows. Mints a permanent /q/ link for this exact query. The same filters always produce the same link, whoever asks.

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Generative Adversarial Networks and Image Synthesis
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Direct Codex and Gemma labels are unvalidated and sparse. Distilled predictions cover the full frame and are also unvalidated. Choose the evidence source explicitly; absence of a direct label is never a negative label.

affaffiliation
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The four routes compose: require the funder route and exclude affiliation to get the funder-only stratum no affiliation-based frame ever sees.

668 results · 1 filter active ·
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20002025
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Machine labels · sparse coverage
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An unlabeled work is unknown, not a negative. Label coverage is reported on every query.
668 works in the cohort · of 4,299,418page 7 of 14

Labels cover 1 of 668 works in this cohort. The rest are unlabeled, which is not a negative label: the label table is sparse today and grows as labeling rounds land.

Distilled predictions cover 668 of 668 works in this cohort. Predictions are machine_predicted_unvalidated. The Gemma side is a direct model label for every work (title-only); the Codex side is a distilled, calibrated classifier. Candidate is the union; consensus is the intersection.

affunlabeled
Deep Probabilistic Canonical Correlation Analysis
Mahdi Karami, Dale Schuurmans
2021· article· en· Proceedings of the AAAI Conference on Artificial Intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
6
citations
affno abstractunlabeled
Controlling BigGAN Image Generation with a Segmentation Network
Aman Jaiswal, Harpreet Singh Sodhi, Mohamed Muzamil H, Rajveen Singh Chandhok, Sageev Oore, Chandramouli Shama Sastry
2021· book-chapter· en· Lecture notes in computer science· Computer Science
machine prediction:candidate · noneconsensus · none
5
citations
affunlabeled
Markpainting: Adversarial Machine Learning meets Inpainting
David Khachaturov, Ilia Shumailov, Yiren Zhao, Nicolas Papernot, Ross Anderson
2021· article· en· International Conference on Machine Learning· Computer Science
machine prediction:candidate · noneconsensus · none
5
citations
fundno affunlabeled
Dual Adversarial Inference for Text-to-Image Synthesis
Qicheng Lao, Mohammad Havaei, Ahmad Pesaranghader, Francis Dutil, Lisa Di Jorio, Thomas Fevens
2019· preprint· en· arXiv (Cornell University)· Computer Science
machine prediction:candidate · noneconsensus · none
5
citations
affunlabeled
Deep Video Inpainting
Dahun Kim, Sanghyun Woo, Joon‐Young Lee, In So Kweon
2019· preprint· en· Computer Science
machine prediction:candidate · noneconsensus · none
5
citations
fundno affunlabeled
Discrete Restricted Boltzmann Machines
Guido Montúfar, Jason Morton
2013· article· en· arXiv (Cornell University)· Computer Science
machine prediction:candidate · noneconsensus · none
4
citations
affno abstractunlabeled
VARGAN: variance enforcing network enhanced GAN
Sanaz Mohammadjafari, Mücahit Çevik, Ayşe Bener
2022· article· en· Applied Intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
4
citations
affunlabeled
Generalized Adversarially Learned Inference
Yatin Dandi, Homanga Bharadhwaj, Abhishek Kumar, Piyush Rai
2021· article· en· Proceedings of the AAAI Conference on Artificial Intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
4
citations
affunlabeled
Energy-Based Processes for Exchangeable Data
Sherry Yang, Bo Dai, Hanjun Dai, Dale Schuurmans
2020· article· en· International Conference on Machine Learning· Computer Science
machine prediction:candidate · noneconsensus · none
3
citations
afffundunlabeled
Stochastic Image-to-Video Synthesis using cINNs
Michael Dorkenwald, Timo Milbich, Andreas Blattmann, Robin Rombach, Konstantinos G. Derpanis, Björn Ommer
2021· preprint· en· Computer Science
machine prediction:candidate · noneconsensus · none
3
citations
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