--- title: "Other — papers, page 16" description: "Other: 743 papers of the Elamur Research library · page 16 of 30 — our summary of each, its ideas, references and who cites it." canonical: "https://research.elamur.ai/free/en/shelves/other/page/16/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/shelves/other/page/16/) [home](https://md.research.elamur.ai/free/en/) / [shelves](https://md.research.elamur.ai/free/en/shelves/) / [Other](https://md.research.elamur.ai/free/en/shelves/other/) / page 16 # 📦 Other 743 papers · page 16 of 30 · newest first · [all shelves](https://md.research.elamur.ai/free/en/shelves/) Works whose topics fit none of the fields above yet. [← prev](https://md.research.elamur.ai/free/en/shelves/other/page/15/) [1](https://md.research.elamur.ai/free/en/shelves/other/) … [15](https://md.research.elamur.ai/free/en/shelves/other/page/15/) **16** [17](https://md.research.elamur.ai/free/en/shelves/other/page/17/) … [30](https://md.research.elamur.ai/free/en/shelves/other/page/30/) [next →](https://md.research.elamur.ai/free/en/shelves/other/page/17/) - [UL2: Unifying Language Learning Paradigms](https://md.research.elamur.ai/free/en/papers/tay-2022-ul2-unifying-language-learning-paradigms/) — Yi Tay, Mostafa Dehghani, Vinh Q. Tran, et al. · 2022 - [Using DeepSpeed and Megatron to Train Megatron-Turing NLG 530B, A Large-Scale Generative Language Model](https://md.research.elamur.ai/free/en/papers/smith-2022-using-deepspeed-megatron-train-megatron/) — Shaden Smith, Mostofa Patwary, Brandon Norick, et al. · 2022 - [WebShop: Towards Scalable Real-World Web Interaction with Grounded Language Agents](https://md.research.elamur.ai/free/en/papers/yao-2022-webshop-towards-scalable-real-world/) — Shunyu Yao, Howard Chen, John Yang, et al. · 2022 - [What learning algorithm is in-context learning? Investigations with linear models](https://md.research.elamur.ai/free/en/papers/akyurek-2022-learning-algorithm-context-learning-investigations/) — Ekin Akyürek, Dale Schuurmans, Jacob Andreas, et al. · 2022 - [A Survey of Data Augmentation Approaches for NLP](https://md.research.elamur.ai/free/en/papers/feng-2021-survey-data-augmentation-approaches-nlp/) — Steven Y. Feng, Varun Gangal, Jason Wei, et al. · 2021 - [An Explanation of In-context Learning as Implicit Bayesian Inference](https://md.research.elamur.ai/free/en/papers/xie-2021-explanation-context-learning-implicit-bayesian/) — Sang Michael Xie, Aditi Raghunathan, Percy Liang, et al. · 2021 - [ARBERT & MARBERT: Deep Bidirectional Transformers for Arabic](https://md.research.elamur.ai/free/en/papers/abdul-2021-mageed-arbert-marbert-deep-bidirectional-transformers/) — Muhammad Abdul-Mageed, AbdelRahim Elmadany, El Moatez Billah Nagoudi · 2021 - [BARTScore: Evaluating Generated Text as Text Generation](https://md.research.elamur.ai/free/en/papers/yuan-2021-bartscore-evaluating-generated-text-text/) — Weizhe Yuan, Graham Neubig, Pengfei Liu · 2021 - [BitFit: Simple Parameter-efficient Fine-tuning for Transformer-based Masked Language-models](https://md.research.elamur.ai/free/en/papers/ben-2021-zaken-bitfit-simple-parameter-efficient-fine/) — Elad Ben-Zaken, Shauli Ravfogel, Yoav Goldberg · 2021 - [Calibrate Before Use: Improving Few-Shot Performance of Language Models](https://md.research.elamur.ai/free/en/papers/zhao-2021-calibrate-before-use-improving-few/) — Tony Z. Zhao, Eric Wallace, Shi Feng, et al. · 2021 - [Carbon Emissions and Large Neural Network Training](https://md.research.elamur.ai/free/en/papers/patterson-2021-carbon-emissions-large-neural-network/) — David Patterson, Joseph Gonzalez, Quoc Le, et al. · 2021 - [Datasets: A Community Library for Natural Language Processing](https://md.research.elamur.ai/free/en/papers/lhoest-2021-datasets-community-library-natural-language/) — Quentin Lhoest, Albert Villanova del Moral, Yacine Jernite, et al. · 2021 - [DeBERTaV3: Improving DeBERTa using ELECTRA-Style Pre-Training with Gradient-Disentangled Embedding Sharing](https://md.research.elamur.ai/free/en/papers/he-2021-debertav3-improving-deberta-using-electra/) — Pengcheng He, Jianfeng Gao, Weizhu Chen · 2021 - [Efficiently Teaching an Effective Dense Retriever with Balanced Topic Aware Sampling](https://md.research.elamur.ai/free/en/papers/hofstatter-2021-efficiently-teaching-effective-dense-retriever/) — Sebastian Hofstatter, Sheng-Chieh Lin, Jheng-Hong Yang, et al. · 2021 - [Emerging Properties in Self-Supervised Vision Transformers](https://md.research.elamur.ai/free/en/papers/caron-2021-emerging-properties-self-supervised-vision/) — Mathilde Caron, Hugo Touvron, Ishan Misra, et al. · 2021 - [Entity-Based Knowledge Conflicts in Question Answering](https://md.research.elamur.ai/free/en/papers/longpre-2021-entity-based-knowledge-conflicts-question/) — Shayne Longpre, Kartik Perisetla, Anthony Chen, et al. · 2021 - [Ethical and social risks of harm from Language Models](https://md.research.elamur.ai/free/en/papers/weidinger-2021-ethical-social-risks-harm-language/) — Laura Weidinger, John Mellor, Maribeth Rauh, et al. · 2021 - [Few-shot Learning with Multilingual Language Models](https://md.research.elamur.ai/free/en/papers/lin-2021-few-shot-learning-multilingual-language/) — Xi Victoria Lin, Todor Mihaylov, Mikel Artetxe, et al. · 2021 - [Generating Datasets with Pretrained Language Models](https://md.research.elamur.ai/free/en/papers/schick-2021-generating-datasets-pretrained-language-models/) — Timo Schick, Hinrich Schutze · 2021 - [GLaM: Efficient Scaling of Language Models with Mixture-of-Experts](https://md.research.elamur.ai/free/en/papers/du-2021-glam-efficient-scaling-language-models/) — Nan Du, Yanping Huang, Andrew M. Dai, et al. · 2021 - [GPT Understands, Too](https://md.research.elamur.ai/free/en/papers/liu-2021-gpt-understands-too/) — Xiao Liu, Yanan Zheng, Zhengxiao Du, et al. · 2021 - [Highly accurate protein structure prediction with AlphaFold](https://md.research.elamur.ai/free/en/papers/jumper-2021-highly-accurate-protein-structure-prediction/) — John Jumper, Richard Evans, Alexander Pritzel, et al. · 2021 - [HuBERT: Self-Supervised Speech Representation Learning by Masked Prediction of Hidden Units](https://md.research.elamur.ai/free/en/papers/hsu-2021-hubert-self-supervised-speech-representation/) — Wei-Ning Hsu, Benjamin Bolte, Yao-Hung Hubert Tsai, et al. · 2021 - [Hurdles to Progress in Long-form Question Answering](https://md.research.elamur.ai/free/en/papers/krishna-2021-hurdles-progress-long-form-question/) — Kalpesh Krishna, Aurko Roy, Mohit Iyyer · 2021 - [LAION-400M: Open Dataset of CLIP-Filtered 400 Million Image-Text Pairs](https://md.research.elamur.ai/free/en/papers/schuhmann-2021-laion-400m-open-dataset-clip/) — Christoph Schuhmann, Richard Vencu, Romain Beaumont, et al. · 2021 [← prev](https://md.research.elamur.ai/free/en/shelves/other/page/15/) [1](https://md.research.elamur.ai/free/en/shelves/other/) … [15](https://md.research.elamur.ai/free/en/shelves/other/page/15/) **16** [17](https://md.research.elamur.ai/free/en/shelves/other/page/17/) … [30](https://md.research.elamur.ai/free/en/shelves/other/page/30/) [next →](https://md.research.elamur.ai/free/en/shelves/other/page/17/)