Fetching the paper…
Reading the bibliography…
Text classification is a crucial task encountered frequently in practical scenarios, yet it is still under-explored in the era of large language models (LLMs).
An evaluation dataset for intent classification and out-of-scope prediction
Stefan Larson, Anish Mahendran, Joseph J Peper, Christopher Clarke, Andrew Lee, Parker Hill, Jonathan K Kummerfeld, Kevin Leach, Michael A Laurenzano, Lingjia Tang, et al. 2019 · 2019
Earlier work this paper cites.
Adversarial category alignment network for cross-domain sentiment classification
Xiaoye Qu, Zhikang Zou, Yu Cheng, Yang Yang, and Pan Zhou. 2019 · 2019
Earlier work this paper cites.
Language models are few-shot learners
Tom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel M. Ziegler, Jeffrey Wu, Clemens Winter, Christopher Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei. 2020 · 2020
Earlier work this paper cites.
Efficient intent detection with dual sentence encoders
Iñigo Casanueva, Tadas Temčinas, Daniela Gerz, Matthew Henderson, and Ivan Vulić. 2020 · 2020
Earlier work this paper cites.
Description based text classification with reinforcement learning
Duo Chai, Wei Wu, Qinghong Han, Fei Wu, and Jiwei Li. 2020 · 2020
Earlier work this paper cites.
Unsupervised data augmentation for consistency training
Qizhe Xie, Zihang Dai, Eduard H. Hovy, Thang Luong, and Quoc Le. 2020 · 2020
Earlier work this paper cites.
Making pre-trained language models better few-shot learners
Tianyu Gao, Adam Fisch, and Danqi Chen. 2021 · 2021
Earlier work this paper cites.
Bertgcn: Transductive text classification by combining gnn and bert
Yuxiao Lin, Yuxian Meng, Xiaofei Sun, Qinghong Han, Kun Kuang, Jiwei Li, and Fei Wu. 2021 · 2021
Earlier work this paper cites.
Benchmarking natural language understanding services for building conversational agents
Xingkun Liu, Arash Eshghi, Pawel Swietojanski, and Verena Rieser. 2021 · 2021
Earlier work this paper cites.
Contrastnet: A contrastive learning framework for few-shot text classification
Junfan Chen, Richong Zhang, Yongyi Mao, and Jie Xu. 2022 · 2022
Earlier work this paper cites.
Large language models are zero-shot reasoners
Takeshi Kojima, Shixiang Shane Gu, Machel Reid, Yutaka Matsuo, and Yusuke Iwasawa. 2022 · 2022
Cited alongside, same era.
Automatic chain of thought prompting in large language models
Zhuosheng Zhang, Aston Zhang, Mu Li, and Alex Smola. 2022 · 2022
Cited alongside, same era.
Jinze Bai, Shuai Bai, Yunfei Chu, Zeyu Cui, Kai Dang, Xiaodong Deng, Yang Fan, Wenbin Ge, Yu Han, Fei Huang, Binyuan Hui, Luo Ji, Mei Li, Junyang Lin, Runji Lin, Dayiheng Liu, Gao Liu, Chengqiang Lu, Keming Lu, Jianxin Ma, Rui Men, Xingzhang Ren, Xuancheng Ren, Chuanqi Tan, Sinan Tan, Jianhong Tu, Peng Wang, Shijie Wang, Wei Wang, Shengguang Wu, Benfeng Xu, Jin Xu, An Yang, Hao Yang, Jian Yang, Shusheng Yang, Yang Yao, Bowen Yu, Hongyi Yuan, Zheng Yuan, Jianwei Zhang, Xingxuan Zhang, Yichang Zhang, Zhenru Zhang, Chang Zhou, Jingren Zhou, Xiaohuan Zhou, and Tianhang Zhu. 2023 · 2023
Cited alongside, same era.
Byoc: Personalized few-shot classification with co-authored class descriptions
Arth Bohra, Govert Verkes, Artem Harutyunyan, Pascal Weinberger, and Giovanni Campagna. 2023 · 2023
Cited alongside, same era.
Reasoning implicit sentiment with chain-of-thought prompting
Breaking the Bank with ChatGPT: Few-Shot Text Classification for Finance
Lefteris Loukas, Ilias Stogiannidis, Prodromos Malakasiotis, and Stavros Vassos. 2023 · 2023
Later among the works it cites.
In-context learning for text classification with many labels
Aristides Milios, Siva Reddy, and Dzmitry Bahdanau. 2023 · 2023
Later among the works it cites.
Large language models sensitivity to the order of options in multiple-choice questions
Pouya Pezeshkpour and Estevam Hruschka. 2023 · 2023
Later among the works it cites.
Text classification via large language models
Xiaofei Sun, Xiaoya Li, Jiwei Li, Fei Wu, Shangwei Guo, Tianwei Zhang, and Guoyin Wang. 2023 · 2023
Later among the works it cites.
Pre-training intent-aware encoders for zero- and few-shot intent classification
Mujeen Sung, James Gung, Elman Mansimov, Nikolaos Pappas, Raphael Shu, Salvatore Romeo, Yi Zhang, and Vittorio Castelli. 2023 · 2023
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Hao Fei, Bobo Li, Qian Liu, Lidong Bing, Fei Li, and Tat-Seng Chua. 2023 · 2023
Cited alongside, same era.
Specializing smaller language models towards multi-step reasoning
Yao Fu, Hao Peng, Litu Ou, Ashish Sabharwal, and Tushar Khot. 2023 · 2023
Cited alongside, same era.
Effective structured prompting by meta-learning and representative verbalizer
Weisen Jiang, Yu Zhang, and James Kwok. 2023 · 2023
Cited alongside, same era.
Spam-t5: Benchmarking large language models for few-shot email spam detection
Maxime Labonne and Sean Moran. 2023 · 2023
Cited alongside, same era.
Instant: Semi-supervised learning with instance-dependent thresholds
Muyang Li, Runze Wu, Haoyu Liu, Jun Yu, Xun Yang, Bo Han, and Tongliang Liu. 2023 · 2023
Cited alongside, same era.
Boosting few-shot text classification via distribution estimation
Han Liu, Feng Zhang, Xiaotong Zhang, Siyang Zhao, Fenglong Ma, Xiao-Ming Wu, Hongyang Chen, Hong Yu, and Xianchao Zhang. 2023 · 2023
Cited alongside, same era.
Boosting logical reasoning in large language models through a new framework: The graph of thought
Bin Lei, pei Hung Lin, Chunhua Liao, and Caiwen Ding. 2023a
Cited in the paper.
TART: Improved few-shot text classification using task-adaptive reference transformation
Shuo Lei, Xuchao Zhang, Jianfeng He, Fanglan Chen, and Chang-Tien Lu. 2023b
Cited in the paper.
Later among the works it cites.
Llama 2: Open foundation and fine-tuned chat models
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.
Self-consistency improves chain of thought reasoning in language models
Xuezhi Wang, Jason Wei, Dale Schuurmans, Quoc Le, Ed Chi, Sharan Narang, Aakanksha Chowdhery, and Denny Zhou. 2023 · 2023
Later among the works it cites.
Tree of thoughts: Deliberate problem solving with large language models
Shunyu Yao, Dian Yu, Jeffrey Zhao, Izhak Shafran, Thomas L. Griffiths, Yuan Cao, and Karthik R Narasimhan. 2023 · 2023
Later among the works it cites.
Chatgpt: Unlocking the future of nlp in finance
Adam Zaremba and Ender Demir. 2023 · 2023
Later among the works it cites.