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Lexical Semantic Change Detection stands out as one of the few areas where Large Language Models (LLMs) have not been extensively involved.
A generalized solution of the orthogonal procrustes problem
Peter Schönemann. 1966 · 1966
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Efficient estimation of word representations in vector space
Tomas Mikolov, Kai Chen, Greg Corrado, and Jeffrey Dean. 2013 · 2013
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Statistically significant detection of linguistic change
Vivek Kulkarni, Rami Al-Rfou, Bryan Perozzi, and Steven Skiena. 2014 · 2014
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin. 2017 · 2017
Earlier work this paper cites.
Diachronic word embeddings reveal statistical laws of semantic change
William L. Hamilton, Jure Leskovec, and Dan Jurafsky. 2018 · 2018
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Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
Earlier work this paper cites.
Diachronic sense modeling with deep contextualized word embeddings: An ecological view
Renfen Hu, Shen Li, and Shichen Liang. 2019 · 2019
Earlier work this paper cites.
A Wind of Change: Detecting and Evaluating Lexical Semantic Change across Times and Domains
Dominik Schlechtweg, Anna Hätty, Marco Del Tredici, and Sabine Schulte im Walde. 2019 · 2019
Cited alongside, same era.
Survey of computational approaches to lexical semantic change
Nina Tahmasebi, Lars Borin, and Adam Jatowt. 2019 · 2019
Cited alongside, same era.
Analysing lexical semantic change with contextualised word representations
Mario Giulianelli, Marco Del Tredici, and Raquel Fernández. 2020 · 2020
Cited alongside, same era.
Capturing evolution in word usage: Just add more clusters?
Matej Martinc, Syrielle Montariol, Elaine Zosa, and Lidia Pivovarova. 2020 · 2020
Cited alongside, same era.
TempoWiC: An Evaluation Benchmark for Detecting Meaning Shift in Social Media
Daniel Loureiro, Aminette D’Souza, Areej Nasser Muhajab, Isabella A. White, Gabriel Wong, Luis Espinosa Anke, Leonardo Neves, Francesco Barbieri, and Jose Camacho-Collados. 2022 · 2022
Sparks of artificial general intelligence: Early experiments with gpt-4
Sébastien Bubeck, Varun Chandrasekaran, Ronen Eldan, Johannes Gehrke, Eric Horvitz, Ece Kamar, Peter Lee, Yin Tat Lee, Yuanzhi Li, Scott Lundberg, et al. 2023 · 2023
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Tabllm: Few-shot classification of tabular data with large language models
Stefan Hegselmann, Alejandro Buendia, Hunter Lang, Monica Agrawal, Xiaoyi Jiang, and David Sontag. 2023 · 2023
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Large language models are zero-shot rankers for recommender systems
Yupeng Hou, Junjie Zhang, Zihan Lin, Hongyu Lu, Ruobing Xie, Julian McAuley, and Wayne Xin Zhao. 2023 · 2023
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Code Llama: Open Foundation Models for Code
Baptiste Rozière, Jonas Gehring, Fabian Gloeckle, Sten Sootla, Itai Gat, Xiaoqing Ellen Tan, Yossi Adi, Jingyu Liu, Tal Remez, Jérémy Rapin, Artyom Kozhevnikov, Ivan Evtimov, Joanna Bitton, Manish Bhatt, Cristian Canton Ferrer, Aaron Grattafiori, Wenhan Xiong, Alexandre Défossez, Jade Copet, Faisal Azhar, Hugo Touvron, Louis Martin, Nicolas Usunier, Thomas Scialom, and Gabriel Synnaeve. 2023 · 2023
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Cited alongside, same era.
MLLabs-LIG at TempoWiC 2022: A Generative Approach for Examining Temporal Meaning Shift
Chenyang Lyu, Yongxin Zhou, and Tianbo Ji. 2022 · 2022
Cited alongside, same era.
OpenAI. 2023a
Cited in the paper.
OpenAI. 2023b
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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, Edouard Grave, and Guillaume Lample. 2023 · 2023
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A survey of large language models
Wayne Xin Zhao, Kun Zhou, Junyi Li, Tianyi Tang, Xiaolei Wang, Yupeng Hou, Yingqian Min, Beichen Zhang, Junjie Zhang, Zican Dong, et al. 2023 · 2023
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