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2022: We reviewed this year’s AI breakthroughs

Applied Data Science

Just wait until you hear what happened in 2022. In our review of 2019 we talked a lot about reinforcement learning and Generative Adversarial Networks (GANs), in 2020 we focused on Natural Language Processing (NLP) and algorithmic bias, in 202 1 Transformers stole the spotlight. In 2022 we got diffusion models ( NeurIPS paper ).

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ACL 2022 Highlights

Sebastian Ruder

ACL 2022 took place in Dublin from 22nd–27th May 2022. Language diversity and multimodality Panelists and their spoken languages at the ACL 2022 keynote panel on supporting linguistic diversity. This was my first in-person conference since ACL 2019. This is also my first conference highlights post since NAACL 2019.

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SQuARE: Towards Multi-Domain and Few-Shot Collaborating Question Answering Agents

ODSC - Open Data Science

Moreover, combining expert agents is an immensely easier task to learn by neural networks than end-to-end QA. Iryna is co-director of the NLP program within ELLIS, a European network of excellence in machine learning. She is currently the president of the Association of Computational Linguistics. Iryna Gurevych.

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68 Summaries of Machine Learning and NLP Research

Marek Rei

EMNLP 2022. EMNLP 2022. NeurIPS 2022. EMNLP 2022. EMNLP 2022. They show performance improvements in some settings and speed improvements in all evaluated settings, showing particular usefulness in settings where the LLM needs to retrieve information about multiple entities (e.g. UC Berkeley, CMU. Google Research.

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Modular Deep Learning

Sebastian Ruder

For modular fine-tuning for NLP, check out our EMNLP 2022 tutorial. Computation Function We consider a neural network $f_theta$ as a composition of functions $f_{theta_1} odot f_{theta_2} odot ldots odot f_{theta_l}$, each with their own set of parameters $theta_i$. For a more in-depth review, refer to our survey.

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ML and NLP Research Highlights of 2021

Sebastian Ruder

It also requires developing models for which the input does not exist in a vacuum but is grounded to extra-linguistic context and the real world. For more work on this topic, check out the EvoNLP workshop at EMNLP 2022. Transactions of the Association for Computational Linguistics, 9, 978–994. Schneider, R.,

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Explainable AI and ChatGPT Detection

Mlearning.ai

Classifiers based on neural networks are known to be poorly calibrated outside of their training data [3]. 2019 Annual Conference of the North American Chapter of the Association for Computational Linguistics. [7] 57th Annual Meeting of the Association for Computational Linguistics [9] C. OpenAI [4] E.