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Generate-and-Retrieve: use your predictions to improve retrieval for
  semantic parsing

Generate-and-Retrieve: use your predictions to improve retrieval for semantic parsing

29 September 2022
Yury Zemlyanskiy
Michiel de Jong
Joshua Ainslie
Panupong Pasupat
Peter Shaw
Linlu Qiu
Sumit Sanghai
Fei Sha
    RALM
ArXivPDFHTML

Papers citing "Generate-and-Retrieve: use your predictions to improve retrieval for semantic parsing"

6 / 6 papers shown
Title
CTQScorer: Combining Multiple Features for In-context Example Selection
  for Machine Translation
CTQScorer: Combining Multiple Features for In-context Example Selection for Machine Translation
Aswanth Kumar
Ratish Puduppully
Raj Dabre
Anoop Kunchukuttan
38
12
0
23 May 2023
Active Retrieval Augmented Generation
Active Retrieval Augmented Generation
Zhengbao Jiang
Frank F. Xu
Luyu Gao
Zhiqing Sun
Qian Liu
Jane Dwivedi-Yu
Yiming Yang
Jamie Callan
Graham Neubig
RALM
20
254
0
11 May 2023
RepoCoder: Repository-Level Code Completion Through Iterative Retrieval
  and Generation
RepoCoder: Repository-Level Code Completion Through Iterative Retrieval and Generation
Fengji Zhang
B. Chen
Yue Zhang
Jacky Keung
Jin Liu
Daoguang Zan
Yi Mao
Jian-Guang Lou
Weizhu Chen
27
219
0
22 Mar 2023
Retrieve-and-Fill for Scenario-based Task-Oriented Semantic Parsing
Retrieve-and-Fill for Scenario-based Task-Oriented Semantic Parsing
Akshat Shrivastava
Shrey Desai
Anchit Gupta
A. Elkahky
Aleksandr Livshits
Alexander Zotov
Ahmed Aly
135
6
0
02 Feb 2022
Controllable Semantic Parsing via Retrieval Augmentation
Controllable Semantic Parsing via Retrieval Augmentation
Panupong Pasupat
Yuan Zhang
Kelvin Guu
132
47
0
16 Oct 2021
Making Pre-trained Language Models Better Few-shot Learners
Making Pre-trained Language Models Better Few-shot Learners
Tianyu Gao
Adam Fisch
Danqi Chen
243
1,919
0
31 Dec 2020
1