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Human-like large language models (LLMs), especially the most powerful and popular ones in OpenAI's GPT family, have proven to be very helpful for many natural language processing (NLP) related tasks.
Scaling laws for neural language models,
J. Kaplan, S. McCandlish, T. Henighan, T. B. Brown, B. Chess, R. Child, S. Gray, A. Radford, J. Wu, D. Amodei, · 2001
Earlier work this paper cites.
The GENIA corpus: An annotated research abstract corpus in molecular biology domain,
T. Ohta, Y. Tateisi, J.-D. Kim, H. Mima, J. Tsujii, · 2002
Earlier work this paper cites.
Introduction to the conll-2003 shared task: Language-independent named entity recognition,
E. F. T. K. Sang, F. D. Meulder, · 2003
Earlier work this paper cites.
The automatic content extraction (ACE) program - tasks, data, and evaluation,
G. R. Doddington, A. Mitchell, M. A. Przybocki, L. A. Ramshaw, S. M. Strassel, R. M. Weischedel, · 2004
Earlier work this paper cites.
A linear programming formulation for global inference in natural language tasks,
D. Roth, W. Yih, · 2004
Earlier work this paper cites.
Semeval-2014 task 4: Aspect based sentiment analysis,
M. Pontiki, D. Galanis, J. Pavlopoulos, H. Papageorgiou, I. Androutsopoulos, S. Manandhar, · 2004
Earlier work this paper cites.
Ace 2005 multilingual training corpus,
C. Walker, S. Strassel, J. Medero, K. Maeda, · 2006
Earlier work this paper cites.
Semeval-2010 task 8: Multi-way classification of semantic relations between pairs of nominals,
I. Hendrickx, S. N. Kim, Z. Kozareva, P. Nakov, D. Ó. Séaghdha, S. Padó, M. Pennacchiotti, L. Romano, S. Szpakowicz, · 2010
Earlier work this paper cites.
Semeval-2016 task 5: Aspect based sentiment analysis,
M. Pontiki, D. Galanis, H. Papageorgiou, I. Androutsopoulos, S. Manandhar, M. Al-Smadi, M. Al-Ayyoub, Y. Zhao, B. Qin, O. D. Clercq, V. Hoste, M. Apidianaki, X. Tannier, N. V. Loukachevitch, E. V. Kotelnikov, N. Bel, S. M. J. Zafra, G. Eryigit, · 2016
Earlier work this paper cites.
Attention is all you need,
A. Vaswani, N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A. N. Gomez, L. Kaiser, I. Polosukhin, · 2017
Earlier work this paper cites.
Deep reinforcement learning from human preferences,
P. F. Christiano, J. Leike, T. B. Brown, M. Martic, S. Legg, D. Amodei, · 2017
Earlier work this paper cites.
Coupled multi-layer attentions for co-extraction of aspect and opinion terms,
W. Wang, S. J. Pan, D. Dahlmeier, X. Xiao, · 2017
Earlier work this paper cites.
Improving language understanding by generative pre-training (2018)
A. Radford, K. Narasimhan, T. Salimans, I. Sutskever, et al., · 2018
Earlier work this paper cites.
Extracting relational facts by an end-to-end neural model with copy mechanism,
X. Zeng, D. Zeng, S. He, K. Liu, J. Zhao, · 2018
Earlier work this paper cites.
BERT: pre-training of deep bidirectional transformers for language understanding,
J. Devlin, M. Chang, K. Lee, K. Toutanova, · 2019
Earlier work this paper cites.
Language models are unsupervised multitask learners,
A. Radford, J. Wu, R. Child, D. Luan, D. Amodei, I. Sutskever, et al., · 2019
Earlier work this paper cites.
Target-oriented opinion words extraction with target-fused neural sequence labeling,
Z. Fan, Z. Wu, X. Dai, S. Huang, J. Chen, · 2019
Earlier work this paper cites.
Language models are few-shot learners,
T. B. Brown, B. Mann, N. Ryder, M. Subbiah, J. Kaplan, P. Dhariwal, A. Neelakantan, P. Shyam, G. Sastry, A. Askell, S. Agarwal, A. Herbert-Voss, G. Krueger, T. Henighan, R. Child, A. Ramesh, D. M. Ziegler, J. Wu, C. Winter, C. Hesse, M. Chen, E. Sigler, M. Litwin, S. Gray, B. Chess, J. Clark, C. Berner, S. McCandlish, A. Radford, I. Sutskever, D. Amodei, · 2020
Earlier work this paper cites.
BART: denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension,
M. Lewis, Y. Liu, N. Goyal, M. Ghazvininejad, A. Mohamed, O. Levy, V. Stoyanov, L. Zettlemoyer, · 2020
Earlier work this paper cites.
A unified MRC framework for named entity recognition,
X. Li, J. Feng, Y. Meng, Q. Han, F. Wu, J. Li, · 2020
Earlier work this paper cites.
Reasoning with latent structure refinement for document-level relation extraction,
G. Nan, Z. Guo, I. Sekulic, W. Lu, · 2020
Earlier work this paper cites.
A joint neural model for information extraction with global features,
Y. Lin, H. Ji, F. Huang, L. Wu, · 2020
Earlier work this paper cites.
Relation-aware collaborative learning for unified aspect-based sentiment analysis,
Z. Chen, T. Qian, · 2020
Earlier work this paper cites.
CASIE: extracting cybersecurity event information from text,
T. Satyapanich, F. Ferraro, T. Finin, · 2020
Earlier work this paper cites.
Knowing what, how and why: A near complete solution for aspect-based sentiment analysis,
H. Peng, L. Xu, L. Bing, F. Huang, W. Lu, L. Si, · 2020
Earlier work this paper cites.
Position-aware tagging for aspect sentiment triplet extraction,
L. Xu, H. Li, W. Lu, L. Bing, · 2020
Earlier work this paper cites.
Automated concatenation of embeddings for structured prediction,
X. Wang, Y. Jiang, N. Bach, T. Wang, Z. Huang, F. Huang, K. Tu, · 2021
Earlier work this paper cites.
Few-nerd: A few-shot named entity recognition dataset,
N. Ding, G. Xu, Y. Chen, X. Wang, X. Han, P. Xie, H. Zheng, Z. Liu, · 2021
Earlier work this paper cites.
Representation iterative fusion based on heterogeneous graph neural network for joint entity and relation extraction,
K. Zhao, H. Xu, Y. Cheng, X. Li, K. Gao, · 2021
Earlier work this paper cites.
Distantly supervised relation extraction using global hierarchy embeddings and local probability constraints,
T. Peng, R. Han, H. Cui, L. Yue, J. Han, L. Liu, · 2021
Cited alongside, same era.
Effective use of graph convolution network and contextual sub-tree for commodity news event extraction,
M. Lee, L.-K. Soon, E.-G. Siew, · 2021
Cited alongside, same era.
A unified generative framework for aspect-based sentiment analysis,
H. Yan, J. Dai, T. Ji, X. Qiu, Z. Zhang, · 2021
Cited alongside, same era.
Target-specified sequence labeling with multi-head self-attention for target-oriented opinion words extraction,
Y. Feng, Y. Rao, Y. Tang, N. Wang, H. Liu, · 2021
Cited alongside, same era.
An annotated commodity news corpus for event extraction,
M. Lee, L.-K. Soon, E.-G. Siew, L. F. Sugianto, · 2021
Cited alongside, same era.
Is chatgpt A good translator? A preliminary study,
W. Jiao, W. Wang, J. Huang, X. Wang, Z. Tu, · 2023
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A multitask, multilingual, multimodal evaluation of chatgpt on reasoning, hallucination, and interactivity,
Y. Bang, S. Cahyawijaya, N. Lee, W. Dai, D. Su, B. Wilie, H. Lovenia, Z. Ji, T. Yu, W. Chung, Q. V. Do, Y. Xu, P. Fung, · 2023
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Are emergent abilities of large language models a mirage?,
R. Schaeffer, B. Miranda, S. Koyejo, · 2023
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Planning for agi and beyond,
S. Altman, · 2023
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Sparks of artificial general intelligence: Early experiments with GPT-4,
S. Bubeck, V. Chandrasekaran, R. Eldan, J. Gehrke, E. Horvitz, E. Kamar, P. Lee, Y. T. Lee, Y. Li, S. M. Lundberg, H. Nori, H. Palangi, M. T. Ribeiro, Y. Zhang, · 2023
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A joint training dual-mrc framework for aspect based sentiment analysis,
Y. Mao, Y. Shen, C. Yu, L. Cai, · 2021
Cited alongside, same era.
Towards generative aspect-based sentiment analysis,
W. Zhang, X. Li, Y. Deng, L. Bing, W. Lam, · 2021
Cited alongside, same era.
Lamda: Language models for dialog applications,
R. Thoppilan, D. D. Freitas, J. Hall, N. Shazeer, A. Kulshreshtha, H. Cheng, A. Jin, T. Bos, L. Baker, Y. Du, Y. Li, H. Lee, H. S. Zheng, A. Ghafouri, M. Menegali, Y. Huang, M. Krikun, D. Lepikhin, J. Qin, D. Chen, Y. Xu, Z. Chen, A. Roberts, M. Bosma, Y. Zhou, C. Chang, I. Krivokon, W. Rusch, M. Pickett, K. S. Meier-Hellstern, M. R. Morris, T. Doshi, R. D. Santos, T. Duke, J. Soraker, B. Zevenbergen, V. Prabhakaran, M. Diaz, B. Hutchinson, K. Olson, A. Molina, E. Hoffman-John, J. Lee, L. Aroyo, R. Rajakumar, A. Butryna, M. Lamm, V. Kuzmina, J. Fenton, A. Cohen, R. Bernstein, R. Kurzweil, B. Aguera-Arcas, C. Cui, M. Croak, E. H. Chi, Q. Le, · 2022
Cited alongside, same era.
Chain-of-thought prompting elicits reasoning in large language models,
J. Wei, X. Wang, D. Schuurmans, M. Bosma, B. Ichter, F. Xia, E. H. Chi, Q. V. Le, D. Zhou, · 2022
Cited alongside, same era.
Multitask prompted training enables zero-shot task generalization,
V. Sanh, A. Webson, C. Raffel, S. H. Bach, L. Sutawika, Z. Alyafeai, A. Chaffin, A. Stiegler, A. Raja, M. Dey, M. S. Bari, C. Xu, U. Thakker, S. S. Sharma, E. Szczechla, T. Kim, G. Chhablani, N. V. Nayak, D. Datta, J. Chang, M. T. Jiang, H. Wang, M. Manica, S. Shen, Z. X. Yong, H. Pandey, R. Bawden, T. Wang, T. Neeraj, J. Rozen, A. Sharma, A. Santilli, T. Févry, J. A. Fries, R. Teehan, T. L. Scao, S. Biderman, L. Gao, T. Wolf, A. M. Rush, · 2022
Cited alongside, same era.
Training language models to follow instructions with human feedback,
L. Ouyang, J. Wu, X. Jiang, D. Almeida, C. L. Wainwright, P. Mishkin, C. Zhang, S. Agarwal, K. Slama, A. Ray, J. Schulman, J. Hilton, F. Kelton, L. Miller, M. Simens, A. Askell, P. Welinder, P. F. Christiano, J. Leike, R. Lowe, · 2022
Cited alongside, same era.
CQG: A simple and effective controlled generation framework for multi-hop question generation,
Z. Fei, Q. Zhang, T. Gui, D. Liang, S. Wang, W. Wu, X. Huang, · 2022
Cited alongside, same era.
Gaussian prior reinforcement learning for nested named entity recognition,
Y. Yang, X. Hu, F. Ma, S. Li, A. Liu, L. Wen, P. S. Yu, · 2023
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Reviewing labels: Label graph network with top-k prediction set for relation extraction,
B. Li, W. Ye, J. Zhang, S. Zhang, · 2023
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A novel tensor learning model for joint relational triplet extraction,
Z. Wang, H. Nie, W. Zheng, Y. Wang, X. Li, · 2023
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Syngen: A syntactic plug-and-play module for generative aspect-based sentiment analysis,
C. Yu, T. Wu, J. Li, X. Bai, Y. Yang, · 2023
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The moral authority of chatgpt,
S. Krügel, A. Ostermaier, M. Uhl, · 2023
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Does synthetic data generation of llms help clinical text mining?,
R. Tang, X. Han, X. Jiang, X. Hu, · 2023
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The utility of chatgpt for cancer treatment information,
S. Chen, B. H. Kann, M. B. Foote, H. J. Aerts, G. K. Savova, R. H. Mak, D. S. Bitterman, · 2023
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On the educational impact of chatgpt: Is artificial intelligence ready to obtain a university degree?,
K. Malinka, M. Peresíni, A. Firc, O. Hujnak, F. Janus, · 2023
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A short survey of viewing large language models in legal aspect,
Z. Sun, · 2023
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How close is chatgpt to human experts? comparison corpus, evaluation, and detection,
B. Guo, X. Zhang, Z. Wang, M. Jiang, J. Nie, Y. Ding, J. Yue, Y. Wu, · 2023
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Applying BERT and chatgpt for sentiment analysis of lyme disease in scientific literature,
T. Susnjak, · 2023
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Is chatgpt a general-purpose natural language processing task solver?,
C. Qin, A. Zhang, Z. Zhang, J. Chen, M. Yasunaga, D. Yang, · 2023
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Can chatgpt understand too? A comparative study on chatgpt and fine-tuned BERT,
Q. Zhong, L. Ding, J. Liu, B. Du, D. Tao, · 2023
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Zero-shot information extraction via chatting with chatgpt,
X. Wei, X. Cui, N. Cheng, X. Wang, X. Zhang, S. Huang, P. Xie, J. Xu, Y. Chen, M. Zhang, Y. Jiang, W. Han, · 2023
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B. Li, G. Fang, Y. Yang, Q. Wang, W. Ye, W. Zhao, S. Zhang, · 2023
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Efficient hybrid generation framework for aspect-based sentiment analysis,
H. Lv, J. Liu, H. Wang, Y. Wang, J. Luo, Y. Liu, · 2023
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Universal information extraction as unified semantic matching,
J. Lou, Y. Lu, D. Dai, W. Jia, H. Lin, X. Han, L. Sun, H. Wu, · 2023
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Instructuie: Multi-task instruction tuning for unified information extraction,
X. Wang, W. Zhou, C. Zu, H. Xia, T. Chen, Y. Zhang, R. Zheng, J. Ye, Q. Zhang, T. Gui, J. Kang, J. Yang, S. Li, C. Du, · 2023
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Rexuie: A recursive method with explicit schema instructor for universal information extraction,
C. Liu, F. Zhao, Y. Kang, J. Zhang, X. Zhou, C. Sun, K. Kuang, F. Wu, · 2023
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Revisiting relation extraction in the era of large language models,
S. Wadhwa, S. Amir, B. C. Wallace, · 2023
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Can chatgpt replace traditional KBQA models? an in-depth analysis of the question answering performance of the GPT LLM family,
Y. Tan, D. Min, Y. Li, W. Li, N. Hu, Y. Chen, G. Qi, · 2023
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Chatgpt is a knowledgeable but inexperienced solver: An investigation of commonsense problem in large language models,
N. Bian, X. Han, L. Sun, H. Lin, Y. Lu, B. He, S. Jiang, B. Dong, · 2024
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Semeval-2015 task 12: Aspect based sentiment analysis,
M. Pontiki, D. Galanis, H. Papageorgiou, S. Manandhar, I. Androutsopoulos, · 2082
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