Improving Search for New Product Categories via Synthetic Query Generation Strategies

Author:

Jagatap Akshay1ORCID,Merugu Srujana1ORCID,Comar Prakash Mandayam1ORCID

Affiliation:

1. Amazon, Bangalore, India

Publisher

ACM

Reference34 articles.

1. James Bergstra Rémi Bardenet Yoshua Bengio and Balázs Kégl. 2011. Algorithms for Hyper-Parameter Optimization. In Advances in Neural Information Processing Systems.

2. James Bergstra Brent Komer Chris Eliasmith Dan Yamins and David D Cox. 2015. Hyperopt: a Python library for model selection and hyperparameter optimization. (2015).

3. Prajjwal Bhargava Aleksandr Drozd and Anna Rogers. 2021. Generalization in NLI: Ways (Not) To Go Beyond Simple Heuristics. arxiv: 2110.01518 [cs.CL]

4. Tom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel M. Ziegler, Jeffrey Wu, Clemens Winter, Christopher Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei. 2020. Language Models are Few-Shot Learners. arxiv: 2005.14165 [cs.CL]

5. Aditi Chaudhary Karthik Raman Krishna Srinivasan Kazuma Hashimoto Mike Bendersky and Marc Najork. 2023. Exploring the Viability of Synthetic Query Generation for Relevance Prediction. (2023).

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