The Stanford AI Lab Blog

JANUARY 21, 2022

Conference of the North American Chapter of the Association for Computational Linguistics. ↩ Devlin, J., Annual Meeting of the Association for Computational Linguistics. ↩ Brown et al. IEEE International Conference on Computer Vision and Pattern Recognition. ↩ Radford, A., Neumann, M.,

Robotics 40

Robotics Computational Linguistics BERT Computer Vision 40

Sebastian Ruder

NOVEMBER 14, 2022

Initiatives   The Association for Computational Linguistics (ACL) has emphasized the importance of language diversity, with a special theme track at the main ACL 2022 conference on this topic. In Findings of the Association for Computational Linguistics: ACL 2022 (pp. In Proceedings of NIPS 2017. Winata, G.

Natural Language Processing 52

Natural Language Processing NLP Computational Linguistics BERT 52

Topbots

JANUARY 30, 2023

In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics , pages 5185–5198, Online. Association for Computational Linguistics. [2] Association for Computational Linguistics. [4] Climbing towards NLU: On Meaning, Form, and Understanding in the Age of Data. 10.48550/arXiv.2212.08120.

Large Language Models 52

Large Language Models Computational Linguistics LLM Natural Language Processing 52

The Stanford AI Lab Blog

OCTOBER 13, 2021

In Proceedings of the IEEE International Conference on Computer Vision, pp. In Association for Computational Linguistics (ACL), pp. In Advances in Neural Information Processing Systems (NeurIPS), 2017. ↩ ↩ 2 Ran El-Yaniv and Yair Wiener. Ziwei Liu, Ping Luo, Xiaogang Wang, and Xiaoou Tang.

Neural Network 40

Neural Network Machine Learning Computational Linguistics Deep Learning 40

Sebastian Ruder

JANUARY 24, 2022

In computer vision, supervised pre-trained models such as Vision Transformer [2] have been scaled up [3] and self-supervised pre-trained models have started to match their performance [4]. Transactions of the Association for Computational Linguistics, 9, 978–994. In Proceedings of NIPS 2017.

NLP 52

NLP ML BERT Computational Linguistics 52

ML Review

MARCH 5, 2019

If the embedding vectors work as expected, computer vision papers should be closer together in this space, and reinforcement learning (RL) papers close to other RL papers. vector: Probing sentence embeddings for linguistic properties. Simple, like with like. S., & Dean, J. In NIPS (pp. 3111–3119). Bojanowski, P., Conneau, A.,

AI 40

AI AI Computer Vision Computational Linguistics 40