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When Peanuts Fall in Love: N400 Evidence for the Power of Discourse
Mante S Nieuwland and Jos JA Van Berkum. 2006 · 2006
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Effects of Event Knowledge in Processing Verbal Arguments
Klinton Bicknell, Jeffrey L Elman, Mary Hare, Ken McRae, and Marta Kutas. 2010 · 2010
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Composing and Updating Verb Argument Expectations: A Distributional Semantic Model
Alessandro Lenci. 2011 · 2011
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Reporting Bias and Knowledge Acquisition
Jonathan Gordon and Benjamin Van Durme. 2013 · 2013
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Fitting linear mixed-effects models using lme4
Dougla Bates. 2014 · 2014
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The Social N400 Effect: How the Presence of Other Listeners Affects Language Comprehension
Shirley-Ann Rueschemeyer, Tom Gardner, and Cat Stoner. 2015 · 2015
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Towards a Distributional Model of Semantic Complexity
Emmanuele Chersoni, Philippe Blache, and Alessandro Lenci. 2016 · 2016
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Event Participant Modelling with Neural Networks
Ottokar Tilk, Vera Demberg, Asad Sayeed, Dietrich Klakow, and Stefan Thater. 2016 · 2016
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Event Knowledge in Sentence Processing: A New Dataset for the Evaluation of Argument Typicality
Paolo Vassallo, Emmanuele Chersoni, Enrico Santus, Alessandro Lenci, and Philippe Blache. 2018 · 2018
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A Structured Distributional Model of Sentence Meaning and Processing
Emmanuele Chersoni, Enrico Santus, Ludovica Pannitto, Alessandro Lenci, Philippe Blache, and Chu-Ren Huang. 2019 · 2019
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Neural Language Models as Psycholinguistic Subjects: Representations of Syntactic State
Richard Futrell, Ethan Wilcox, Takashi Morita, Peng Qian, Miguel Ballesteros, and Roger Levy. 2019 · 2019
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Tracking Colisteners’ Knowledge States during Language Comprehension
Olessia Jouravlev, Rachael Schwartz, Dima Ayyash, Zachary Mineroff, Edward Gibson, and Evelina Fedorenko. 2019 · 2019
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Lack of Selectivity for Syntax Relative to Word Meanings Throughout the Language Network
Evelina Fedorenko, Idan Asher Blank, Matthew Siegelman, and Zachary Mineroff. 2020 · 2020
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A Systematic Assessment of Syntactic Generalization in Neural Language Models
Jennifer Hu, Jon Gauthier, Peng Qian, Ethan Wilcox, and Roger P Levy. 2020 · 2020
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Negated and Misprimed Probes for Pretrained Language Models: Birds Can Talk, but Cannot Fly
Nora Kassner and Hinrich Schütze. 2020 · 2020
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How Well Does Surprisal Explain N400 Amplitude Under Different Experimental Conditions?
James A Michaelov and Benjamin K Bergen. 2020 · 2020
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Masked language model scoring
Julian Salazar, Davis Liang, Toan Q. Nguyen, and Katrin Kirchhoff. 2020 · 2020
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BLiMP: The Benchmark of Linguistic Minimal Pairs for English
Alex Warstadt, Alicia Parrish, Haokun Liu, Anhad Mohananey, Wei Peng, Sheng-Fu Wang, and Samuel R Bowman. 2020 · 2020
Cited alongside, same era.
The Language Model Understood the Prompt was Ambiguous: Probing Syntactic Uncertainty through Generation
Laura Aina and Tal Linzen. 2021 · 2021
Cited alongside, same era.
Not All Arguments Are Processed Equally: A Distributional Model of Argument Complexity
Emmanuele Chersoni, Enrico Santus, Alessandro Lenci, Philippe Blache, and Chu-Ren Huang. 2021 · 2021
Cited alongside, same era.
Surface Form Competition: Why the Highest Probability Answer Isn’t Always Right
Ari Holtzman, Peter West, Vered Shwartz, Yejin Choi, and Luke Zettlemoyer. 2021 · 2021
Cited alongside, same era.
Implicit Representations of Meaning in Neural Language Models
Belinda Z Li, Maxwell Nye, and Jacob Andreas. 2021 · 2021
Cited alongside, same era.
When Language Models Fall in Love: Animacy Processing in Transformer Language Models
Michael Hanna, Yonatan Belinkov, and Sandro Pezzelle. 2023 · 2023
Later among the works it cites.
Prompting Is Not a Substitute for Probability Measurements in Large Language Models
Jennifer Hu and Roger Levy. 2023 · 2023
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Albert Q Jiang, Alexandre Sablayrolles, Arthur Mensch, Chris Bamford, Devendra Singh Chaplot, Diego de las Casas, Florian Bressand, Gianna Lengyel, Guillaume Lample, Lucile Saulnier, et al. 2023 · 2023
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Impact of Co-occurrence on Factual Knowledge of Large Language Models
Cheongwoong Kang and Jaesik Choi. 2023 · 2023
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A Better Way to Do Masked Language Model Scoring
Carina Kauf and Anna Ivanova. 2023 · 2023
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Did the Cat Drink the Coffee? Challenging Transformers with Generalized Event Knowledge
Paolo Pedinotti, Giulia Rambelli, Emmanuele Chersoni, Enrico Santus, Alessandro Lenci, and Philippe Blache. 2021 · 2021
Cited alongside, same era.
Learning how to Ask: Querying LMs with Mixtures of Soft Prompts
Guanghui Qin and Jason Eisner. 2021 · 2021
Cited alongside, same era.
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, et al. 2022 · 2022
Cited alongside, same era.
Measuring Causal Effects of Data Statistics on Language Model’s Factual Predictions
Yanai Elazar, Nora Kassner, Shauli Ravfogel, Amir Feder, Abhilasha Ravichander, Marius Mosbach, Yonatan Belinkov, Hinrich Schütze, and Yoav Goldberg. 2022 · 2022
Cited alongside, same era.
Andrew Kyle Lampinen. 2022 · 2022
Cited alongside, same era.
Probing via Prompting
Jiaoda Li, Ryan Cotterell, and Mrinmaya Sachan. 2022 · 2022
Cited alongside, same era.
When Classifying Grammatical Role, BERT Doesn’t Care about Word Order… Except When It Matters
Isabel Papadimitriou, Richard Futrell, and Kyle Mahowald. 2022 · 2022
Cited alongside, same era.
Event Knowledge in Large Language Models: The Gap Between the Impossible and the Unlikely
Carina Kauf, Anna A Ivanova, Giulia Rambelli, Emmanuele Chersoni, Jingyuan Selena She, Zawad Chowdhury, Evelina Fedorenko, and Alessandro Lenci. 2023 · 2023
Later among the works it cites.
Can Peanuts Fall in Love with Distributional Semantics?
James A Michaelov, Seana Coulson, and Benjamin K Bergen. 2023 · 2023
Later among the works it cites.
Introducing MPT-7B: A New Standard for Open-Source, Commercially Usable LLMs
MosaicML NLP Team. 2023 · 2023
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Automatic Prompt Optimization with "Gradient Descent" and Beam Search
Reid Pryzant, Dan Iter, Jerry Li, Yin Tat Lee, Chenguang Zhu, and Michael Zeng. 2023 · 2023
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Melanie Sclar, Yejin Choi, Yulia Tsvetkov, and Alane Suhr. 2023 · 2023
Later among the works it cites.
Just Ask for Calibration: Strategies for Eliciting Calibrated Confidence Scores from Language Models Fine-Tuned with Human Feedback
Katherine Tian, Eric Mitchell, Allan Zhou, Archit Sharma, Rafael Rafailov, Huaxiu Yao, Chelsea Finn, and Christopher Manning. 2023 · 2023
Later among the works it cites.
Llama: Open and Efficient Foundation Language Models
Hugo Touvron, Thibaut Lavril, Gautier Izacard, Xavier Martinet, Marie-Anne Lachaux, Timothée Lacroix, Baptiste Rozière, Naman Goyal, Eric Hambro, Faisal Azhar, Aurelien Rodriguez, Armand Joulin, Grave Edouard, and Guillaume Lample. 2023 · 2023
Later among the works it cites.
Instruction Tuning for Large Language Models: A Survey
Shengyu Zhang, Linfeng Dong, Xiaoya Li, Sen Zhang, Xiaofei Sun, Shuhe Wang, Jiwei Li, Runyi Hu, Tianwei Zhang, Fei Wu, et al. 2023 · 2023
Later among the works it cites.
Yongchao Chen, Jacob Arkin, Yilun Hao, Yang Zhang, Nicholas Roy, and Chuchu Fan. 2024 · 2024
Closest in time.
Language Models Align with Human Judgments on key Grammatical Constructions
Jennifer Hu, Kyle Mahowald, Gary Lupyan, Anna Ivanova, and Roger Levy. 2024 · 2024
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Psychometric Predictive Power of Large Language Models
Tatsuki Kuribayashi, Yohei Oseki, and Timothy Baldwin. 2024 · 2024
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Kanishka Misra, Allyson Ettinger, and Kyle Mahowald. 2024 · 2024
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