On Degrees of Freedom in Defining and Testing Natural Language Understanding

24 May 2023

Papers citing "On Degrees of Freedom in Defining and Testing Natural Language Understanding"

14 / 14 papers shown

Title
Stochastic LLMs do not Understand Language: Towards Symbolic, Explainable and Ontologically Based LLMs Walid S. Saba 14 18 0 12 Sep 2023
Training language models to follow instructions with human feedback Long Ouyang Jeff Wu Xu Jiang Diogo Almeida Carroll L. Wainwright ... Amanda Askell Peter Welinder Paul Christiano Jan Leike Ryan J. Lowe OSLM ALM 313 11,953 0 04 Mar 2022
Measure and Improve Robustness in NLP Models: A Survey Xuezhi Wang Haohan Wang Diyi Yang 139 130 0 15 Dec 2021
Analyzing Dynamic Adversarial Training Data in the Limit Eric Wallace Adina Williams Robin Jia Douwe Kiela 198 30 0 16 Oct 2021
BBQ: A Hand-Built Bias Benchmark for Question Answering Alicia Parrish Angelica Chen Nikita Nangia Vishakh Padmakumar Jason Phang Jana Thompson Phu Mon Htut Sam Bowman 217 367 0 15 Oct 2021
Beyond Fair Pay: Ethical Implications of NLP Crowdsourcing Boaz Shmueli Jan Fell Soumya Ray Lun-Wei Ku 108 86 0 20 Apr 2021
Competency Problems: On Finding and Removing Artifacts in Language Data Matt Gardner William Merrill Jesse Dodge Matthew E. Peters Alexis Ross Sameer Singh Noah A. Smith 168 107 0 17 Apr 2021
Did Aristotle Use a Laptop? A Question Answering Benchmark with Implicit Reasoning Strategies Mor Geva Daniel Khashabi Elad Segal Tushar Khot Dan Roth Jonathan Berant RALM 250 677 0 06 Jan 2021
With Little Power Comes Great Responsibility Dallas Card Peter Henderson Urvashi Khandelwal Robin Jia Kyle Mahowald Dan Jurafsky 230 115 0 13 Oct 2020
Towards Ecologically Valid Research on Language User Interfaces H. D. Vries Dzmitry Bahdanau Christopher D. Manning 212 51 0 28 Jul 2020
To Test Machine Comprehension, Start by Defining Comprehension Jesse Dunietz Greg Burnham Akash Bharadwaj Owen Rambow Jennifer Chu-Carroll D. Ferrucci FaML 54 65 0 04 May 2020
How Can We Accelerate Progress Towards Human-like Linguistic Generalization? Tal Linzen 220 188 0 03 May 2020
Are We Modeling the Task or the Annotator? An Investigation of Annotator Bias in Natural Language Understanding Datasets Mor Geva Yoav Goldberg Jonathan Berant 242 320 0 21 Aug 2019
Towards A Rigorous Science of Interpretable Machine Learning Finale Doshi-Velez Been Kim XAI FaML 254 3,684 0 28 Feb 2017