Fetching the paper…
Reading the bibliography…
Large Language Models (LLMs) have recently shown remarkable advancement in various NLP tasks.
Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al. 2020 · 1901
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. 2019 · 1907
Earlier work this paper cites.
Kawin Ethayarajh. 2019 · 1909
Earlier work this paper cites.
Mike Lewis, Yinhan Liu, Naman Goyal, Marjan Ghazvininejad, Abdelrahman Mohamed, Omer Levy, Ves Stoyanov, and Luke Zettlemoyer. 2019 · 1910
Earlier work this paper cites.
WordNet: An Electronic Lexical Database
Christiane Fellbaum. 1998 · 1998
Earlier work this paper cites.
Linguistic regularities in continuous space word representations
Tomas Mikolov, Wen-tau Yih, and Geoffrey Zweig. 2013b · 2013
Earlier work this paper cites.
Linguistic regularities in sparse and explicit word representations
Omer Levy and Yoav Goldberg. 2014 · 2014
Earlier work this paper cites.
GloVe: Global vectors for word representation
Jeffrey Pennington, Richard Socher, and Christopher Manning. 2014 · 2014
Earlier work this paper cites.
Word embeddings, analogies, and machine learning: Beyond king - man + woman = queen
Aleksandr Drozd, Anna Gladkova, and Satoshi Matsuoka. 2016 · 2016
Earlier work this paper cites.
Analogy-based detection of morphological and semantic relations with word embeddings: what works and what doesn’t
Anna Gladkova, Aleksandr Drozd, and Satoshi Matsuoka. 2016 · 2016
Earlier work this paper cites.
Issues in evaluating semantic spaces using word analogies
Tal Linzen. 2016 · 2016
Earlier work this paper cites.
Daniel Cer, Yinfei Yang, Sheng yi Kong, Nan Hua, Nicole Limtiaco, Rhomni St. John, Noah Constant, Mario Guajardo-Cespedes, Steve Yuan, Chris Tar, Yun-Hsuan Sung, Brian Strope, and Ray Kurzweil. 2018 · 2018
Earlier work this paper cites.
Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2018 · 2018
Earlier work this paper cites.
Dissecting contextual word embeddings: Architecture and representation
Matthew E Peters, Mark Neumann, Luke Zettlemoyer, and Wen-tau Yih. 2018 · 2018
Cited alongside, same era.
Massively multilingual sentence embeddings for zero-shot cross-lingual transfer and beyond
Mikel Artetxe and Holger Schwenk. 2019 · 2019
Cited alongside, same era.
Sentence-bert: Sentence embeddings using siamese bert-networks
Nils Reimers and Iryna Gurevych. 2019 · 2019
Cited alongside, same era.
Analogies minus analogy test: measuring regularities in word embeddings
Louis Fournier, Emmanuel Dupoux, and Ewan Dunbar. 2020 · 2020
Cited alongside, same era.
Contextual and non-contextual word embeddings: an in-depth linguistic investigation
Alessio Miaschi and Felice Dell’Orletta. 2020 · 2020
Rohan Anil, Andrew M Dai, Orhan Firat, Melvin Johnson, Dmitry Lepikhin, Alexandre Passos, Siamak Shakeri, Emanuel Taropa, Paige Bailey, Zhifeng Chen, et al. 2023 · 2023
Later among the works it cites.
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
Later among the works it cites.
Yash Mahajan, Naman Bansal, and Shubhra Kanti Karmaker. 2023 · 2023
Later among the works it cites.
Zero-shot multi-label topic inference with sentence encoders and llms
Souvika Sarkar, Dongji Feng, and Shubhra Kanti Karmaker Santu. 2023 · 2023
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Simcse: Simple contrastive learning of sentence embeddings
Tianyu Gao, Xingcheng Yao, and Danqi Chen. 2021 · 2021
Cited alongside, same era.
Patterns of lexical ambiguity in contextualised language models
Janosch Haber and Massimo Poesio. 2021 · 2021
Cited alongside, same era.
Palm: Scaling language modeling with pathways
Aakanksha Chowdhery, Sharan Narang, Jacob Devlin, Maarten Bosma, Gaurav Mishra, Adam Roberts, Paul Barham, Hyung Won Chung, Charles Sutton, Sebastian Gehrmann, et al. 2022 · 2022
Cited alongside, same era.
Why can gpt learn in-context? language models secretly perform gradient descent as meta optimizers
Damai Dai, Yutao Sun, Li Dong, Yaru Hao, Zhifang Sui, and Furu Wei. 2022 · 2022
Cited alongside, same era.
Glam: Efficient scaling of language models with mixture-of-experts
Nan Du, Yanping Huang, Andrew M Dai, Simon Tong, Dmitry Lepikhin, Yuanzhong Xu, Maxim Krikun, Yanqi Zhou, Adams Wei Yu, Orhan Firat, et al. 2022 · 2022
Cited alongside, same era.
Exploring universal sentence encoders for zero-shot text classification
Souvika Sarkar, Dongji Feng, and Shubhra Kanti Karmaker Santu. 2022 · 2022
Cited alongside, same era.
Shaden Smith, Mostofa Patwary, Brandon Norick, Patrick LeGresley, Samyam Rajbhandari, Jared Casper, Zhun Liu, Shrimai Prabhumoye, George Zerveas, Vijay Korthikanti, et al. 2022 · 2022
Cited alongside, same era.
Hugo Touvron, Louis Martin, Kevin Stone, Peter Albert, Amjad Almahairi, Yasmine Babaei, Nikolay Bashlykov, Soumya Batra, Prajjwal Bhargava, Shruti Bhosale, Dan Bikel, Lukas Blecher, Cristian Canton Ferrer, Moya Chen, Guillem Cucurull, David Esiobu, Jude Fernandes, Jeremy Fu, Wenyin Fu, Brian Fuller, Cynthia Gao, Vedanuj Goswami, Naman Goyal, Anthony Hartshorn, Saghar Hosseini, Rui Hou, Hakan Inan, Marcin Kardas, Viktor Kerkez, Madian Khabsa, Isabel Kloumann, Artem Korenev, Punit Singh Koura, Marie-Anne Lachaux, Thibaut Lavril, Jenya Lee, Diana Liskovich, Yinghai Lu, Yuning Mao, Xavier Martinet, Todor Mihaylov, Pushkar Mishra, Igor Molybog, Yixin Nie, Andrew Poulton, Jeremy Reizenstein, Rashi Rungta, Kalyan Saladi, Alan Schelten, Ruan Silva, Eric Michael Smith, Ranjan Subramanian, Xiaoqing Ellen Tan, Binh Tang, Ross Taylor, Adina Williams, Jian Xiang Kuan, Puxin Xu, Zheng Yan, Iliyan Zarov, Yuchen Zhang, Angela Fan, Melanie Kambadur, Sharan Narang, Aurelien Rodriguez, Robert Stojnic, Sergey Edunov, and Thomas Scialom. 2023 · 2023
Later among the works it cites.
Claude3.5-sonnet
2024 · 2024
Closest in time.
Capturing the relationship between sentence triplets for llm and human-generated texts to enhance sentence embeddings
Na Min An, Sania Waheed, and James Thorne. 2024 · 2024
Closest in time.
Olmo: Accelerating the science of language models
Dirk Groeneveld, Iz Beltagy, Pete Walsh, Akshita Bhagia, Rodney Kinney, Oyvind Tafjord, Ananya Harsh Jha, Hamish Ivison, Ian Magnusson, Yizhong Wang, et al. 2024 · 2024
Closest in time.
Polysemy—evidence from linguistics, behavioral science, and contextualized language models
Janosch Haber and Massimo Poesio. 2024 · 2024
Closest in time.
Probing the representational structure of regular polysemy via sense analogy questions: Insights from contextual word vectors
Jiangtian Li and Blair C Armstrong. 2024 · 2024
Closest in time.
ALIGN-SIM: A task-free test bed for evaluating and interpreting sentence embeddings through semantic similarity alignment
Yash Mahajan, Naman Bansal, Eduardo Blanco, and Santu Karmaker. 2024 · 2024
Closest in time.
Openelm: An efficient language model family with open-source training and inference framework
Sachin Mehta, Mohammad Hossein Sekhavat, Qingqing Cao, Maxwell Horton, Yanzi Jin, Chenfan Sun, Iman Mirzadeh, Mahyar Najibi, Dmitry Belenko, Peter Zatloukal, et al. 2024 · 2024
Closest in time.