The Power of Prompt Tuning for Low-Resource Semantic Parsing

The Power of Prompt Tuning for Low-Resource Semantic Parsing

16 October 2021

Nathan Schucher

Siva Reddy

Papers citing "The Power of Prompt Tuning for Low-Resource Semantic Parsing"

9 / 9 papers shown

Title
FPT: Feature Prompt Tuning for Few-shot Readability Assessment Ziyang Wang Sanwoo Lee Hsiu-Yuan Huang Yunfang Wu AAML VLM 36 0 0 03 Apr 2024
Coupling Large Language Models with Logic Programming for Robust and General Reasoning from Text Zhun Yang Adam Ishay Joohyung Lee LRM ELM 33 51 0 15 Jul 2023
Knowledge Base Question Answering: A Semantic Parsing Perspective Yu Gu Vardaan Pahuja Gong Cheng Yu-Chuan Su 34 29 0 12 Sep 2022
Addressing Resource and Privacy Constraints in Semantic Parsing Through Data Augmentation Kevin Yang Olivia Deng Charles C. Chen Richard Shin Subhro Roy Benjamin Van Durme 43 10 0 18 May 2022
The Low-Resource Double Bind: An Empirical Study of Pruning for Low-Resource Machine Translation Orevaoghene Ahia Julia Kreutzer Sara Hooker 112 51 0 06 Oct 2021
PICARD: Parsing Incrementally for Constrained Auto-Regressive Decoding from Language Models Torsten Scholak Nathan Schucher Dzmitry Bahdanau 154 374 0 10 Sep 2021
Constrained Language Models Yield Few-Shot Semantic Parsers Richard Shin C. H. Lin Sam Thomson Charles C. Chen Subhro Roy Emmanouil Antonios Platanios Adam Pauls Dan Klein J. Eisner Benjamin Van Durme 292 198 0 18 Apr 2021
The Power of Scale for Parameter-Efficient Prompt Tuning Brian Lester Rami Al-Rfou Noah Constant VPVLM 280 3,848 0 18 Apr 2021
Exploiting Cloze Questions for Few Shot Text Classification and Natural Language Inference Timo Schick Hinrich Schütze 258 1,588 0 21 Jan 2020