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In the Amazon KDD Cup 2022, we aim to apply natural language processing methods to improve the quality of search results that can significantly enhance user experience and engagement with search engines for e-commerce.
Learning to rank with nonsmooth cost functions
Christopher Burges, Robert Ragno, and Quoc Le. 2006 · 2006
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Distilling the knowledge in a neural network
Geoffrey Hinton, Oriol Vinyals, Jeff Dean, et al · 2015
Earlier work this paper cites.
Sentence-bert: Sentence embeddings using siamese bert-networks
Nils Reimers and Iryna Gurevych. 2019 · 2019
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Big bird: Transformers for longer sequences
Manzil Zaheer, Guru Guruganesh, Kumar Avinava Dubey, Joshua Ainslie, Chris Alberti, Santiago Ontanon, Philip Pham, Anirudh Ravula, Qifan Wang, Li Yang, et al · 2020
Cited alongside, same era.
Pengcheng He, Jianfeng Gao, and Weizhu Chen. 2021 · 2021
Cited alongside, same era.
Coco-lm: Correcting and contrasting text sequences for language model pretraining
Yu Meng, Chenyan Xiong, Payal Bajaj, Paul Bennett, Jiawei Han, Xia Song, et al · 2021
Later among the works it cites.
Shopping Queries Dataset: A Large-Scale ESCI Benchmark for Improving Product Search
Chandan K. Reddy, Lluís Màrquez, Fran Valero, Nikhil Rao, Hugo Zaragoza, Sambaran Bandyopadhyay, Arnab Biswas, Anlu Xing, and Karthik Subbian. 2022 · 2022
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