Using Natural Language Explanations to Improve Robustness of In-context Learning

13 November 2023

Papers citing "Using Natural Language Explanations to Improve Robustness of In-context Learning"

8 / 8 papers shown

Title
Not another Negation Benchmark: The NaN-NLI Test Suite for Sub-clausal Negation Thinh Hung Truong Yulia Otmakhova Tim Baldwin Trevor Cohn Jey Han Lau Karin Verspoor 57 21 0 06 Oct 2022
Self-Consistency Improves Chain of Thought Reasoning in Language Models Xuezhi Wang Jason W. Wei Dale Schuurmans Quoc Le Ed H. Chi Sharan Narang Aakanksha Chowdhery Denny Zhou ReLM BDL LRM AI4CE 308 3,237 0 21 Mar 2022
Fantastically Ordered Prompts and Where to Find Them: Overcoming Few-Shot Prompt Order Sensitivity Yao Lu Max Bartolo Alastair Moore Sebastian Riedel Pontus Stenetorp AILaw LRM 277 1,120 0 18 Apr 2021
What Makes Good In-Context Examples for GPT- $3$ ? Jiachang Liu Dinghan Shen Yizhe Zhang Bill Dolan Lawrence Carin Weizhu Chen AAML RALM 275 1,312 0 17 Jan 2021
HypoNLI: Exploring the Artificial Patterns of Hypothesis-only Bias in Natural Language Inference Tianyu Liu Xin Zheng Baobao Chang Zhifang Sui 40 23 0 05 Mar 2020
e-SNLI: Natural Language Inference with Natural Language Explanations Oana-Maria Camburu Tim Rocktaschel Thomas Lukasiewicz Phil Blunsom LRM 255 620 0 04 Dec 2018
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding Alex Jinpeng Wang Amanpreet Singh Julian Michael Felix Hill Omer Levy Samuel R. Bowman ELM 297 6,950 0 20 Apr 2018
A causal framework for explaining the predictions of black-box sequence-to-sequence models David Alvarez-Melis Tommi Jaakkola CML 224 201 0 06 Jul 2017