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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.

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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Advanced Neural Network Applications
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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.

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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.

1,336 results · 1 filter active ·
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20012025
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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.
1,336 works in the cohort · of 4,299,418page 2 of 27

Labels cover 0 of 1,336 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 1,336 of 1,336 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
Long Range Arena: A Benchmark for Efficient Transformers
Yi Tay, Mostafa Dehghani, Samira Abnar, Yikang Shen, Dara Bahri, Philip Pham +4 more
2020· preprint· en· arXiv (Cornell University)· Computer Science
machine prediction:candidate · noneconsensus · none
195
citations
affunlabeled
Lookahead Optimizer: k steps forward, 1 step back
Michael R. Zhang, James Lucas, Jimmy Ba, Geoffrey E. Hinton
2019· article· en· Neural Information Processing Systems· Computer Science
machine prediction:candidate · noneconsensus · none
176
citations
affaboutunlabeled
Winner-Take-All Autoencoders
Alireza Makhzani, Brendan J. Frey
2014· preprint· en· arXiv (Cornell University)· Computer Science
machine prediction:candidate · noneconsensus · none
174
citations
affunlabeled
Dual Vision Transformer
Ting Yao, Yehao Li, Yingwei Pan, Yu Wang, Xiao–Ping Zhang, Tao Mei
2023· article· en· IEEE Transactions on Pattern Analysis and Machine Intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
157
citations
affunlabeled
Neural Networks with Few Multiplications
Zhouhan Lin, Matthieu Courbariaux, Roland Memisevic, Yoshua Bengio
2015· preprint· en· arXiv (Cornell University)· Computer Science
machine prediction:candidate · noneconsensus · none
155
citations
affunlabeled
Fast Semantic Segmentation for Scene Perception
Xuetao Zhang, Zhenxue Chen, Q. M. Jonathan Wu, Lei Cai, Dan Lu
2018· article· en· IEEE Transactions on Industrial Informatics· Computer Science
machine prediction:candidate · noneconsensus · none
127
citations

How this was built: Screen · Findings · About