Fetching the paper…
Reading the bibliography…
Recent studies of the emergent capabilities of transformer-based Natural Language Understanding (NLU) models have indicated that they have an understanding of lexical and compositional semantics.
Linguistic knowledge and transferability of contextual representations
Nelson F Liu, Matt Gardner, Yonatan Belinkov, Matthew E Peters, and Noah A Smith. 2019a · 1903
Earlier work this paper cites.
Can neural networks understand monotonicity reasoning?
Hitomi Yanaka, Koji Mineshima, Daisuke Bekki, Kentaro Inui, Satoshi Sekine, Lasha Abzianidze, and Johan Bos. 2019 · 1906
Earlier work this paper cites.
Roberta: A robustly optimized bert pretraining approach
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019b · 1907
Earlier work this paper cites.
Revealing the dark secrets of bert
Olga Kovaleva, Alexey Romanov, Anna Rogers, and Anna Rumshisky. 2019 · 1908
Earlier work this paper cites.
Do nlp models know numbers? probing numeracy in embeddings
Eric Wallace, Yizhong Wang, Sujian Li, Sameer Singh, and Matt Gardner. 2019 · 1909
Earlier work this paper cites.
Benchmarking zero-shot text classification: Datasets, evaluation and entailment approach
Wenpeng Yin, Jamaal Hay, and Dan Roth. 2019 · 1909
Earlier work this paper cites.
Adversarial nli: A new benchmark for natural language understanding
Yixin Nie, Adina Williams, Emily Dinan, Mohit Bansal, Jason Weston, and Douwe Kiela. 2019 · 1910
Earlier work this paper cites.
Distilbert, a distilled version of bert: smaller, faster, cheaper and lighter
Victor Sanh, Lysandre Debut, Julien Chaumond, and Thomas Wolf. 2019 · 1910
Earlier work this paper cites.
The general notion of entailment
Michael Clark. 1967 · 1950
Earlier work this paper cites.
Introduction to semantics and formalization of logic
Rudolf Carnap. 1959 · 1959
Earlier work this paper cites.
Logic and conversation
Herbert P Grice. 1975 · 1975
Earlier work this paper cites.
Pragmatic presuppositions
Robert Stalnaker, Milton K Munitz, and Peter Unger. 1977 · 1977
Earlier work this paper cites.
Behavior analysis of nli models: Uncovering the influence of three factors on robustness
V Ivan Sanchez Carmona, Jeff Mitchell, and Sebastian Riedel. 2018 · 1985
Earlier work this paper cites.
Compositional semantics and language understanding
Stephen Schiffer. 1986 · 1986
Earlier work this paper cites.
Deducibility, entailment and analytic containment
Richard B Angell. 1989 · 1989
Earlier work this paper cites.
Semantics, pragmatics, and situated meaning
Aaron Cicourel. 1991 · 1991
Earlier work this paper cites.
Natural language understanding
James Allen. 1995 · 1995
Earlier work this paper cites.
The berkeley framenet project
Collin F Baker, Charles J Fillmore, and John B Lowe. 1998 · 1998
Earlier work this paper cites.
Entailment, intensionality and text understanding
Cleo Condoravdi, Dick Crouch, Valeria De Paiva, Reinhard Stolle, and Daniel Bobrow. 2003 · 2003
Earlier work this paper cites.
Jensen-shannon divergence and hilbert space embedding
Bent Fuglede and Flemming Topsoe. 2004 · 2004
Earlier work this paper cites.
Neural natural language inference models partially embed theories of lexical entailment and negation
Atticus Geiger, Kyle Richardson, and Christopher Potts. 2020 · 2004
Earlier work this paper cites.
Are natural language inference models imppressive? learning implicature and presupposition
Paloma Jeretic, Alex Warstadt, Suvrat Bhooshan, and Adina Williams. 2020a · 2004
Cited alongside, same era.
The pascal recognising textual entailment challenge
Ido Dagan, Oren Glickman, and Bernardo Magnini. 2005 · 2005
Cited alongside, same era.
Beyond accuracy: Behavioral testing of nlp models with checklist
Marco Tulio Ribeiro, Tongshuang Wu, Carlos Guestrin, and Sameer Singh. 2020 · 2005
Cited alongside, same era.
Deberta: Decoding-enhanced bert with disentangled attention
Pengcheng He, Xiaodong Liu, Jianfeng Gao, and Weizhu Chen. 2020 · 2006
Cited alongside, same era.
Glue: A multi-task benchmark and analysis platform for natural language understanding
Alex Wang, Amanpreet Singh, Julian Michael, Felix Hill, Omer Levy, and Samuel R Bowman. 2018 · 2018
Later among the works it cites.
Swag: A large-scale adversarial dataset for grounded commonsense inference
Rowan Zellers, Yonatan Bisk, Roy Schwartz, and Yejin Choi. 2018 · 2018
Later among the works it cites.
Representation of constituents in neural language models: Coordination phrase as a case study
Aixiu An, Peng Qian, Ethan Wilcox, and Roger Levy. 2019 · 2019
Later among the works it cites.
What does BERT look at? an analysis of BERT’s attention
Kevin Clark, Urvashi Khandelwal, Omer Levy, and Christopher D. Manning. 2019 · 2019
Later among the works it cites.
A structural probe for finding syntax in word representations
John Hewitt and Christopher D Manning. 2019 · 2019
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Corby Rosset, Chenyan Xiong, Minh Phan, Xia Song, Paul Bennett, and Saurabh Tiwary. 2020 · 2007
Cited alongside, same era.
Can neural networks acquire a structural bias from raw linguistic data?
Alex Warstadt and Samuel R Bowman. 2020 · 2007
Cited alongside, same era.
Kullback-leibler divergence
James M Joyce. 2011 · 2011
Cited alongside, same era.
Context-dependent semantic processing in the human brain: Evidence from idiom comprehension
Joost Rommers, Ton Dijkstra, and Marcel Bastiaansen. 2013 · 2013
Cited alongside, same era.
Kolmogorov–smirnov test: Overview
Vance W Berger and YanYan Zhou. 2014 · 2014
Cited alongside, same era.
Compositional semantics: An introduction to the syntax/semantics interface
Pauline I Jacobson. 2014 · 2014
Cited alongside, same era.
A large annotated corpus for learning natural language inference
Samuel R Bowman, Gabor Angeli, Christopher Potts, and Christopher D Manning. 2015 · 2015
Cited alongside, same era.
Learning natural language inference with lstm
Shuohang Wang and Jing Jiang. 2015 · 2015
Cited alongside, same era.
What does bert learn about the structure of language?
Ganesh Jawahar, Benoît Sagot, and Djamé Seddah. 2019 · 2019
Later among the works it cites.
Mike Lewis, Yinhan Liu, Naman Goyal, Marjan Ghazvininejad, Abdelrahman Mohamed, Omer Levy, Ves Stoyanov, and Luke Zettlemoyer. 2019 · 2019
Later among the works it cites.
Right for the wrong reasons: Diagnosing syntactic heuristics in natural language inference
Tom McCoy, Ellie Pavlick, and Tal Linzen. 2019 · 2019
Later among the works it cites.
EQUATE: A benchmark evaluation framework for quantitative reasoning in natural language inference
Abhilasha Ravichander, Aakanksha Naik, Carolyn Rose, and Eduard Hovy. 2019 · 2019
Later among the works it cites.
Superglue: A stickier benchmark for general-purpose language understanding systems
Alex Wang, Yada Pruksachatkun, Nikita Nangia, Amanpreet Singh, Julian Michael, Felix Hill, Omer Levy, and Samuel Bowman. 2019 · 2019
Later among the works it cites.
Probing natural language inference models through semantic fragments
Kyle Richardson, Hai Hu, Lawrence Moss, and Ashish Sabharwal. 2020 · 2020
Later among the works it cites.
Koustuv Sinha, Prasanna Parthasarathi, Joelle Pineau, and Adina Williams. 2020 · 2020
Later among the works it cites.
Transformers: State-of-the-art natural language processing
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, Rémi Louf, Morgan Funtowicz, Joe Davison, Sam Shleifer, Patrick von Platen, Clara Ma, Yacine Jernite, Julien Plu, Canwen Xu, Teven Le Scao, Sylvain Gugger, Mariama Drame, Quentin Lhoest, and Alexander M. Rush. 2020 · 2020
Later among the works it cites.
Semantics-aware bert for language understanding
Zhuosheng Zhang, Yuwei Wu, Hai Zhao, Zuchao Li, Shuailiang Zhang, Xi Zhou, and Xiang Zhou. 2020 · 2020
Later among the works it cites.
Koustuv Sinha, Prasanna Parthasarathi, Joelle Pineau, and Adina Williams. 2021 · 2021
Later among the works it cites.
Finetuned language models are zero-shot learners
Jason Wei, Maarten Bosma, Vincent Y Zhao, Kelvin Guu, Adams Wei Yu, Brian Lester, Nan Du, Andrew M Dai, and Quoc V Le. 2021 · 2021
Later among the works it cites.
Probing classifiers: Promises, shortcomings, and advances
Yonatan Belinkov. 2022 · 2022
Later among the works it cites.
Scaling instruction-finetuned language models
Hyung Won Chung, Le Hou, Shayne Longpre, Barret Zoph, Yi Tay, William Fedus, Yunxuan Li, Xuezhi Wang, Mostafa Dehghani, Siddhartha Brahma, Albert Webson, Shixiang Shane Gu, Zhuyun Dai, Mirac Suzgun, Xinyun Chen, Aakanksha Chowdhery, Alex Castro-Ros, Marie Pellat, Kevin Robinson, Dasha Valter, Sharan Narang, Gaurav Mishra, Adams Yu, Vincent Zhao, Yanping Huang, Andrew Dai, Hongkun Yu, Slav Petrov, Ed H. Chi, Jeff Dean, Jacob Devlin, Adam Roberts, Denny Zhou, Quoc V. Le, and Jason Wei. 2022 · 2022
Later among the works it cites.
Language models show human-like content effects on reasoning
Ishita Dasgupta, Andrew K Lampinen, Stephanie CY Chan, Antonia Creswell, Dharshan Kumaran, James L McClelland, and Felix Hill. 2022 · 2022
Later among the works it cites.
Large language models are zero-shot reasoners
Takeshi Kojima, Shixiang Shane Gu, Machel Reid, Yutaka Matsuo, and Yusuke Iwasawa. 2022 · 2022
Later among the works it cites.
Survey of hallucination in natural language generation
Ziwei Ji, Nayeon Lee, Rita Frieske, Tiezheng Yu, Dan Su, Yan Xu, Etsuko Ishii, Ye Jin Bang, Andrea Madotto, and Pascale Fung. 2023 · 2023
Later among the works it cites.