NeurIPS 2024 Honors GANs and Sequence Models With Test of Time Awards
NeurIPS 2024 recognizes two highly influential papers from 2014 that laid the groundwork for modern generative AI and large language models. The awarded works introduce generative adversarial networks and the foundational encoder-decoder architecture.
NeurIPS 2024 announces the Test of Time Paper Awards, recognizing two exceptional papers published at NeurIPS 2014 that significantly shape the current artificial intelligence landscape. The conference makes a rare exception this year to honor two separate works due to their undeniable and massive influence on the entire research field.
The first awarded paper is Generative Adversarial Nets by Ian Goodfellow and colleagues, which boasts over 85,000 citations and serves as a foundational pillar for modern generative modeling. The second awarded paper is Sequence to Sequence Learning with Neural Networks by Ilya Sutskever and colleagues, which accumulates over 27,000 citations and establishes the crucial encoder-decoder architecture that paves the way for today's large language models.
Both award-winning authors present their historically significant works in person at the NeurIPS conference on Friday, December 13th, 2024, followed by a brief question and answer session. Conference organizers look forward to revealing additional prestigious NeurIPS awards as the event continues to unfold.