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← Graph transformer networks allow multimodule document recognition…

14 connected korrents · 15 moments from 1 Jan 1998 to 18 Sept 2026. Nearly all of them are about neural networks.

Everything filed under computer vision computer vision Everything filed under pruning pruning Everything filed under LLMs LLMs Everything filed under transformers transformers Same subjectSame subjectSame subjectSame subjectSame subjectSame subjectSame subjectSame subjectSame subjectSame subjectSame subjectSame subjectSame subjectSame subject Read this korrent: Graph transformer networks allow multimodule document recognition systems to be trained globally with gradient methods to minimize overall performance. Graph transformer networks allowmultimodule document recognition systemsto be trained globally with gradientmethods to minimize overall performance. Last stated 29 years ago 1 Jan 1998 YB Yoshua Bengio — holds since 1998-01-01 — tap for who they are Same subject: Sequence transduction can use a simple architecture based solely on attention, without recurrence or convolutions. — tap to centre the map on it Sequence transduction can use asimple architecture based solely onattention, without recurrence orconvolutions. Last stated 9 years ago 12 Jun 2017 IP Illia Polosukhin — holds since 2017-06-12 — tap for who they are JU Jakob Uszkoreit — holds since 2017-06-12 — tap for who they are NP Niki Parmar — holds since 2017-06-12 — tap for who they are AV Ashish Vaswani — holds since 2017-06-12 — tap for who they are NS Noam Shazeer — holds since 2017-06-12 — tap for who they are AG Aidan N. Gomez — holds since 2017-06-12 — tap for who they are +2 2 more Same subject: A transduction model can rely entirely on self-attention for input and output representations without sequence-aligned RNNs or convolution. — tap to centre the map on it A transduction model can relyentirely on self-attention for inputand output representations withoutsequence-aligned RNNs orconvolution. Last stated 9 years ago 12 Jun 2017 IP Illia Polosukhin — holds since 2017-06-12 — tap for who they are JU Jakob Uszkoreit — holds since 2017-06-12 — tap for who they are NP Niki Parmar — holds since 2017-06-12 — tap for who they are AV Ashish Vaswani — holds since 2017-06-12 — tap for who they are NS Noam Shazeer — holds since 2017-06-12 — tap for who they are AG Aidan N. Gomez — holds since 2017-06-12 — tap for who they are +2 2 more Same subject: Work on large language models is not progress toward artificial general intelligence, because the models do not understand what they read. — tap to centre the map on it Work on large language models is notprogress toward artificial generalintelligence, because the models donot understand what they read. Last stated a year ago 30 Jul 2025 AG Alexey Guzey — holds since 2024-08-09 — tap for who they are AG Alexey Guzey — no longer holds since 2025-07-30 — tap for who they are Same subject: With suitable architecture, gradient-based learning can form decision surfaces that classify high-dimensional patterns such as handwritten characters with minimal preprocessing. — tap to centre the map on it With suitable architecture,gradient-based learning can formdecision surfaces that classifyhigh-dimensional patterns such ashandwritten characters with minimalpreprocessing. Last stated 29 years ago 1 Jan 1998 YB Yoshua Bengio — holds since 1998-01-01 — tap for who they are Same subject: Residual networks are easier to optimize than plain ones and keep gaining accuracy as depth increases. — tap to centre the map on it Residual networks are easier tooptimize than plain ones and keepgaining accuracy as depth increases. Last stated 11 years ago 10 Dec 2015 JS Jian Sun — holds since 2015-12-10 — tap for who they are KH Kaiming He — holds since 2015-12-10 — tap for who they are Same subject: AlexNet's real breakthrough was not computer vision but the discovery of a universal function approximator that can learn any function. — tap to centre the map on it AlexNet's real breakthrough was notcomputer vision but the discovery ofa universal function approximatorthat can learn any function. Last stated 3 months ago 26 Jul 2026 JH Jensen Huang — holds since 2026-07-26 — tap for who they are Same subject: Atlas is the first model to unify pixel generation and pixel reconstruction, two tracks computer vision has kept apart for over half a century. — tap to centre the map on it Atlas is the first model to unifypixel generation and pixelreconstruction, two tracks computervision has kept apart for over halfa century. Last stated 2 months ago 4 Sept 2026 FL Fei-Fei Li — holds since 2026-09-04 — tap for who they are Same subject: Growth of internet image data can enable more sophisticated models for indexing and interacting with multimedia. — tap to centre the map on it Growth of internet image data canenable more sophisticated models forindexing and interacting withmultimedia. Last stated 17 years ago 1 Jun 2009 FL Fei-Fei Li — holds since 2009-06-01 — tap for who they are Same subject: Batteries will replace transmission as the cheapest way to keep the lights on, and the grid will shrink rather than grow. — tap to centre the map on it Batteries will replace transmissionas the cheapest way to keep thelights on, and the grid will shrinkrather than grow. Last stated 11 months ago 8 Dec 2025 CH Casey Handmer — holds since 2023-10-11 — tap for who they are CH Casey Handmer — holds since 2025-12-08 — tap for who they are Same subject: Most agent harnesses need some pruning during context compaction anyway for cost reasons, which Jev might help with. — tap to centre the map on it Most agent harnesses need somepruning during context compactionanyway for cost reasons, which Jevmight help with. Last stated a month ago 18 Sept 2026 AR Armin Ronacher — holds since 2026-09-18 — tap for who they are Same subject: Neuroplasticity is as much the removal of connections as the growth of new ones, so pruning is a form of learning rather than a form of decay. — tap to centre the map on it Neuroplasticity is as much theremoval of connections as the growthof new ones, so pruning is a form oflearning rather than a form ofdecay. Last stated 3 months ago 20 Jul 2026 TW Tommy Wood — holds since 2026-07-20 — tap for who they are Same subject: Image is the most versatile input modality for a model, since it can represent text, tabular data, and audio — tap to centre the map on it Image is the most versatile inputmodality for a model, since it canrepresent text, tabular data, andaudio Last stated 3 years ago 10 Oct 2023 CH Chip Huyen — holds since 2023-10-10 — tap for who they are Same subject: Video never became intelligence the way text did because text arrives already abstracted into the bits humans care about. — tap to centre the map on it Video never became intelligence theway text did because text arrivesalready abstracted into the bitshumans care about. Last stated a year ago 12 Sept 2025 SL Sergey Levine — holds since 2025-09-12 — tap for who they are Same subject: A badly written AI outbound email is evidence of a bad vendor, not of a limit of AI. — tap to centre the map on it A badly written AI outbound email isevidence of a bad vendor, not of alimit of AI. Last stated 10 months ago 1 Jan 2026 JL Jason Lemkin — holds since 2026-01-01 — tap for who they are
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At the centre Graph transformer networks allow multimodule document recognition systems to be trained globally with gradient methods to minimize overall performance. Last stated 1 Jan 1998 · 29 years ago Holds Yoshua Bengio Read this korrent →