Datasets and Benchmarks
Dataset and Benchmark Track 3
Joaquin Vanschoren · Serena Yeung
Moderator : Alice Oh
The Datasets and Benchmarks track serves as a novel venue for high-quality publications, talks, and posters on highly valuable machine learning datasets and benchmarks, as well as a forum for discussions on how to improve dataset development. Datasets and benchmarks are crucial for the development of machine learning methods, but also require their own publishing and reviewing guidelines. For instance, datasets can often not be reviewed in a double-blind fashion, and hence full anonymization will not be required. On the other hand, they do require additional specific checks, such as a proper description of how the data was collected, whether they show intrinsic bias, and whether they will remain accessible.
Schedule
Fri 12:00 a.m. - 12:10 a.m.
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Programming Puzzles
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Oral
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SlidesLive Video |
Tal Schuster · Ashwin Kalyan · Alex Polozov · Adam Kalai 🔗 |
Fri 12:10 a.m. - 12:20 a.m.
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Adversarial GLUE: A Multi-Task Benchmark for Robustness Evaluation of Language Models
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Oral
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SlidesLive Video |
Boxin Wang · Chejian Xu · Shuohang Wang · Zhe Gan · Yu Cheng · Jianfeng Gao · Ahmed Awadallah · Bo Li 🔗 |
Fri 12:20 a.m. - 12:30 a.m.
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NaturalProofs: Mathematical Theorem Proving in Natural Language
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Oral
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SlidesLive Video |
Sean Welleck · Jiacheng Liu · Ronan Le Bras · Hanna Hajishirzi · Yejin Choi · Kyunghyun Cho 🔗 |
Fri 12:30 a.m. - 12:40 a.m.
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HumBugDB: A Large-scale Acoustic Mosquito Dataset
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Oral
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SlidesLive Video |
16 presentersIvan Kiskin · Marianne Sinka · Adam Cobb · Waqas Rafique · Lawrence Wang · Davide Zilli · Benjamin Gutteridge · Rinita Dam · Theodoros Marinos · Yunpeng Li · Dickson Msaky · Emmanuel Kaindoa · Gerard Killeen · Eva Herreros-Moya · Kathy Willis · Stephen J Roberts |
Fri 12:40 a.m. - 1:00 a.m.
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Joint Q&A
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Q&A
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