Who cites «Learning and Evaluating General Linguistic Intelligence»
- Language Models are Few-Shot LearnersarXiv:2005.14165Tom B. Brown, Benjamin Mann, Nick Ryder, et al.2020 · 14,178 citations
- Learning Transferable Visual Models From Natural Language SupervisionarXiv:2103.00020Alec Radford, Jong Wook Kim, Chris Hallacy, et al.2021 · 8,767 citations
- Unified Language Model Pre-training for Natural Language Understanding and GenerationarXiv:1905.03197Li Dong, Nan Yang, Wenhui Wang, et al.2019 · 1,422 citations
- Calibrate Before Use: Improving Few-Shot Performance of Language ModelsarXiv:2102.09690Tony Z. Zhao, Eric Wallace, Shi Feng, et al.2021 · 825 citations
- Using DeepSpeed and Megatron to Train Megatron-Turing NLG 530B, A Large-Scale Generative Language ModelarXiv:2201.11990Shaden Smith, Mostofa Patwary, Brandon Norick, et al.2022 · 615 citations
- Pretrained Transformers Improve Out-of-Distribution RobustnessAnnual Meeting of the Association for Computational Linguistics (ACL)Dan Hendrycks, Xiaoyuan Liu, Eric Wallace, et al.2020 · 452 citations
- oLMpics — On what Language Model Pre-training CapturesTransactions of the Association for Computational Linguistics (TACL)Alon Talmor, Yanai Elazar, Yoav Goldberg, et al.2019 · 440 citations
- Information-Theoretic Probing with Minimum Description LengthConference on Empirical Methods in Natural Language Processing (EMNLP)Elena Voita, Ivan Titov2020 · 345 citations
- Can You Unpack That? Learning to Rewrite Questions-in-ContextConference on Empirical Methods in Natural Language Processing (EMNLP)Ahmed Elgohary, Denis Peskov, Jordan Boyd-Graber2019 · 245 citations
- Unsupervised Domain Adaptation of Contextualized Embeddings for Sequence LabelingConference on Empirical Methods in Natural Language Processing (EMNLP)Xiaochuang Han, Jacob Eisenstein2019 · 241 citations
- MultiQA: An Empirical Investigation of Generalization and Transfer in Reading ComprehensionAnnual Meeting of the Association for Computational Linguistics (ACL)Alon Talmor, Jonathan Berant2019 · 236 citations
- Syntactic Data Augmentation Increases Robustness to Inference HeuristicsAnnual Meeting of the Association for Computational Linguistics (ACL)Junghyun Min, R. Thomas McCoy, Dipanjan Das, et al.2020 · 220 citations
- What Happens To BERT Embeddings During Fine-tuning?BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLPAmil Merchant, Elahe Rahimtoroghi, Ellie Pavlick, et al.2020 · 220 citations
- CrossFit: A Few-shot Learning Challenge for Cross-task Generalization in NLPConference on Empirical Methods in Natural Language Processing (EMNLP)Qinyuan Ye, Bill Yuchen Lin, Xiang Ren2021 · 210 citations
- What to Pre-Train on? Efficient Intermediate Task SelectionConference on Empirical Methods in Natural Language Processing (EMNLP)Clifton Poth, Jonas Pfeiffer, Andreas Rücklé, et al.2021 · 132 citations
- English Intermediate-Task Training Improves Zero-Shot Cross-Lingual Transfer TooConference of the Asia-Pacific Chapter of the Association for Computational Linguistics (AACL)Jason Phang, Iacer Calixto, Phu Mon Htut, et al.2020 · 70 citations
- Investigating Language Relationships in Multilingual Sentence Encoders Through the Lens of Linguistic TypologyComputational LinguisticsRochelle Choenni, Ekaterina Shutova2022 · 24 citations
- Beyond Leaderboards: A survey of methods for revealing weaknesses in Natural Language Inference data and modelsarXiv:2005.14709Viktor Schlegel, Goran Nenadic, Riza Batista-Navarro2020 · 24 citations
- Sparse Adapter Fusion for Continual Learning in NLPConference of the European Chapter of the Association for Computational Linguistics (EACL)Min Zeng, Xi Chen, Haiqin Yang, et al.2026 · 1 citation
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