A survey of GPT-3 family large language models including ChatGPT and GPT-4

Deep Residual Learning for Image Recognition

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ImageNet classification with deep convolutional neural networks

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Long Short-Term Memory

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MizAR 60 for Mizar 50

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BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

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ImageNet: A large-scale hierarchical image database

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Going deeper with convolutions

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Glove: Global Vectors for Word Representation

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Efficient Estimation of Word Representations in Vector Space

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A Unified Approach to Interpreting Model Predictions

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A survey on transfer learning

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Language Models are Few-Shot Learners

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BLEU: a method for automatic evaluation of machine translation

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Sequence to Sequence Learning with Neural Networks

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RoBERTa: A Robustly Optimized BERT Pretraining Approach

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Neural Machine Translation by Jointly Learning to Align and Translate

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A survey on Image Data Augmentation for Deep Learning

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On a Method to Measure Supervised Multiclass Model’s Interpretability: Application to Degradation Diagnosis (Short Paper)

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Deep Contextualized Word Representations

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Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling

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Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer

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Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions

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Enriching Word Vectors with Subword Information

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BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension

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Effective Approaches to Attention-based Neural Machine Translation

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BioBERT: a pre-trained biomedical language representation model for biomedical text mining

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A Comprehensive Survey on Transfer Learning

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2009 IEEE Conference on Computer Vision and Pattern Recognition

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Unsupervised Cross-lingual Representation Learning at Scale

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DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter

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LLaMA: Open and Efficient Foundation Language Models

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Character-level Convolutional Networks for Text ClassificationPreprint

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ALBERT: A Lite BERT for Self-supervised Learning of Language Representations

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Chain-of-Thought Prompting Elicits Reasoning in Large Language Models

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A Survey on Evaluation of Large Language Models

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GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding

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Training language models to follow instructions with human feedback

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Untitled work

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Performance of ChatGPT on USMLE: Potential for AI-assisted medical education using large language models

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Universal Language Model Fine-tuning for Text Classification

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Large language models encode clinical knowledge

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Large Language Models Encode Clinical Knowledge

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A Convolutional Neural Network for Modelling Sentences

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Training Language Models to Follow Instructions with Human Feedback

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Chatting and cheating: Ensuring academic integrity in the era of ChatGPT

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A Survey on Multi-Task Learning

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Chatting and Cheating. Ensuring academic integrity in the era of ChatGPT

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Recent Trends in Deep Learning Based Natural Language Processing [Review Article]

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BERTScore: Evaluating Text Generation with BERT

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A survey on semi-supervised learning

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Llama 2: Open Foundation and Fine-Tuned Chat Models

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PaLM: Scaling Language Modeling with Pathways

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EDA: Easy Data Augmentation Techniques for Boosting Performance on Text Classification Tasks

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Longformer: The Long-Document Transformer

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No Language Left Behind: Scaling Human-Centered Machine TranslationPreprint

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Domain-specific language model pretraining for biomedical natural language processing

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A Survey of Large Language Models

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A Survey of Large Language Models

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DeBERTa: Decoding-enhanced BERT with Disentangled AttentionPreprint

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Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena

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ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators

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A Survey of the Usages of Deep Learning for Natural Language Processing

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Multilingual Denoising Pre-training for Neural Machine Translation

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Toward expert-level medical question answering with large language models

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mT5: A Massively Multilingual Pre-trained Text-to-Text Transformer

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Pre-trained models for natural language processing: A survey

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Cross-lingual Language Model Pretraining

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Sparks of Artificial General Intelligence: Early experiments with GPT-4

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CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and Generation

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CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and Generation

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Defects4J: a database of existing faults to enable controlled testing studies for Java programs

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Scaling Instruction-Finetuned Language Models

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Evaluating Large Language Models Trained on Code

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A survey of transformers

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DeBERTaV3: Improving DeBERTa using ELECTRA-Style Pre-Training with Gradient-Disentangled Embedding SharingPreprint

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Efficient transformers: A survey

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Emergent Abilities of Large Language Models

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Don’t Give Me the Details, Just the Summary! Topic-Aware Convolutional Neural Networks for Extreme Summarization

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ChatGPT outperforms crowd workers for text-annotation tasks

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Comparing scientific abstracts generated by ChatGPT to real abstracts with detectors and blinded human reviewers

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Recent Advances in Recurrent Neural NetworksPreprint

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BERTweet: A pre-trained language model for English Tweets

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Competition-level code generation with AlphaCode

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Large Language Models for Software Engineering: A Systematic Literature Review

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An MTurk Crisis? Shifts in Data Quality and the Impact on Study Results

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Pre-trained models: Past, present and future

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A Survey of Data Augmentation Approaches for NLP

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Training Compute-Optimal Large Language Models

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TruthfulQA: Measuring How Models Mimic Human Falsehoods

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Findings of the Association for Computational Linguistics: EMNLP 2021

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A survey on multimodal large language models

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FrugalGPT: How to Use Large Language Models While Reducing Cost and Improving Performance

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Is ChatGPT a General-Purpose Natural Language Processing Task Solver?

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Linformer: Self-Attention with Linear Complexity

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A Survey on Text Classification: From Traditional to Deep Learning

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GPTScore: Evaluate as You Desire

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LaMDA: Language Models for Dialog Applications

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Unsupervised Learning of Sentence Embeddings Using Compositional n-Gram Features

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ChatGPT: Jack of all trades, master of none

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Regulating ChatGPT and other Large Generative AI Models

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CodeT5+: Open Code Large Language Models for Code Understanding and Generation

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BloombergGPT: A Large Language Model for Finance

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BARTScore: Evaluating Generated Text as Text Generation

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Learning to Generate Reviews and Discovering Sentiment

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CodeGen: An Open Large Language Model for Code with Multi-Turn Program Synthesis

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Is ChatGPT A Good Translator? Yes With GPT-4 As The Engine

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BRIO: Bringing Order to Abstractive Summarization

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SciBench: Evaluating College-Level Scientific Problem-Solving Abilities of Large Language ModelsPreprint

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ToxiGen: A Large-Scale Machine-Generated Dataset for Adversarial and Implicit Hate Speech Detection

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Want To Reduce Labeling Cost? GPT-3 Can Help

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A Survey on Model Compression for Large Language Models

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AnnoLLM: Making Large Language Models to Be Better Crowdsourced Annotators

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A Holistic Approach to Undesired Content Detection in the Real World

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Automatic Detection of Generated Text is Easiest when Humans are Fooled

Ippolito, D., Duckworth, D., Callison-Burch, C., & Eck, D. (2019) · arXiv · doi:10.48550/arxiv.1911.00650 · Cited by 264

StarCoder: may the source be with you!

Li, R., Allal, L. B., Zi, Y., Muennighoff, N., Kocetkov, D., Mou, C., Marone, M., Akiki, C., Li, J., Chim, J., et al. (2023) · arXiv · doi:10.48550/arxiv.2305.06161 · Cited by 261

Will ChatGPT get you caught? Rethinking of Plagiarism Detection

Khalil, M., & Er, E. (2023) · doi:10.35542/osf.io/fnh48 · Cited by 259

FinQA: A Dataset of Numerical Reasoning over Financial Data

Chen, Z., Chen, W., Smiley, C., Shah, S., Borova, I., Langdon, D., Moussa, R., Beane, M., Huang, T.-H., Routledge, B., et al. (2021) · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing · doi:10.18653/v1/2021.emnlp-main.300 · Cited by 258

Towards Out-Of-Distribution Generalization: A Survey

Liu, J., Shen, Z., He, Y., Zhang, X., Xu, R., Yu, H., & Cui, P. (2021) · arXiv · doi:10.48550/arxiv.2108.13624 · Cited by 253

AudioGPT: Understanding and Generating Speech, Music, Sound, and Talking Head

Huang, R., Li, M., Yang, D., Shi, J., Chang, X., Ye, Z., Wu, Y., Hong, Z., Huang, J., Liu, J., et al. (2024) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v38i21.30570 · Cited by 250

A Survey on In-context Learning

Dong, Q., Li, L., Dai, D., Zheng, C., Ma, J., Li, R., Xia, H., Xu, J., Wu, Z., Liu, T., et al. (2023) · arXiv · doi:10.48550/arxiv.2301.00234 · Cited by 248

Is ChatGPT better than Human Annotators? Potential and Limitations of ChatGPT in Explaining Implicit Hate Speech

Huang, F., Kwak, H., & An, J. (2023) · International World Wide Web Conference (WWW) · doi:10.1145/3543873.3587368 · Cited by 247

Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP Tasks

Wang, Y., Mishra, S., Alipoormolabashi, P., Kordi, Y., Mirzaei, A., Naik, A., Ashok, A., Dhanasekaran, A. S., Arunkumar, A., Stap, D., et al. (2022) · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing · doi:10.18653/v1/2022.emnlp-main.340 · Cited by 247

QuixBugs: a multi-lingual program repair benchmark set based on the quixey challenge

Lin, D., Koppel, J., Chen, A., & Solar-Lezama, A. (2017) · Proceedings Companion of the 2017 ACM SIGPLAN International Conference on Systems, Programming, Languages, and Applications: Software for Humanity · doi:10.1145/3135932.3135941 · Cited by 242

Large language models for code completion: A systematic literature review

Husein, R. A., Aburajouh, H., & Catal, C. (2025) · Computer Standards & Interfaces · doi:10.1016/j.csi.2024.103917 · Cited by 72

Survey on AI-generated plagiarism detection: The impact of large language models on academic integrity

Pudasaini, S., Miralles-Pechuán, L., Lillis, D., & Llorens Salvador, M. (2025) · Journal of Academic Ethics · doi:10.1007/s10805-024-09576-x · Cited by 70

Tiny Language Models for Automation and Control: Overview, Potential Applications, and Future Research Directions

Lamaakal, I., Maleh, Y., El Makkaoui, K., Ouahbi, I., Pławiak, P., Alfarraj, O., Almousa, M., & Abd El-Latif, A. A. (2025) · Sensors · doi:10.3390/s25051318 · Cited by 60

Large Language Models in Systematic Review Screening: Opportunities, Challenges, and Methodological Considerations

Galli, C., Gavrilova, A. V., & Calciolari, E. (2025) · Information · doi:10.3390/info16050378 · Cited by 36

Perceptions of Artificial Intelligence and ChatGPT by Speech-Language Pathologists and Students

Austin, J., Benas, K., Caicedo, S., Imiolek, E., Piekutowski, A., & Ghanim, I. (2025) · American Journal of Speech-Language Pathology · doi:10.1044/2024_ajslp-24-00218 · Cited by 31

The Effect of Mentoring on Successor Nurturing in Family Businesses

Samei, H., & Feyzbakhsh, A. (2016) · The Journal of Entrepreneurship · doi:10.1177/0971355716650370 · Cited by 17

Interpreting NLRB V. Burns Int'l Sec. Servs., Inc.: The Not So "Perfectly Clear" Successor Exception

Willis, D., & Bales, R. A. (2010) · Seton Hall University eRepository (Seton Hall University)

Review on Research of Marxism Popularity in 2008

Xia, T. (2009) · Journal of Bohai University

The Evolving Roles of Leader and Successor

Aronoff, C. E., McClure, S. L., & Ward, J. L. (2011) · Palgrave Macmillan US eBooks · doi:10.1007/978-1-137-51208-6_8

The female perspective on family business successor commitment

Otten‐Pappas, D. (2013) · Journal of Family Business Management · doi:10.1108/20436231311326463 · Cited by 36