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Google at EMNLP 2022

Google Research AI blog

Zhao , Yi Luan , Keith B. A Protocol for Evaluating the Faithfulness of Input Salience Methods for Text Classification (see blog post ) Jasmijn Bastings , Sebastian Ebert , Polina Zablotskaia , Anders Sandholm , Katja Filippova Intriguing Properties of Compression on Multilingual Models Kelechi Ogueji*, Orevaoghene Ahia, Gbemileke A.

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Stanford AI Lab Papers and Talks at NeurIPS 2021

Stanford AI Lab Blog

We’re excited to share all the work from SAIL that’s being presented at the main conference , at the Datasets and Benchmarks track and the various workshops , and you’ll find links to papers, videos and blogs below. Powers, Yianni Laloudakis, Sidhika Balachandar, Bowen Jing, Brandon Anderson, Stephan Eismann, Risi Kondor, Russ B.

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Google at ICML 2023

Google Research AI blog

Sajjadi , Gaurav Aggarwal , Thomas Kipf , Deepak Pathak , Katerina Fragkiadaki> Algorithms for Bounding Contribution for Histogram Estimation Under User-Level Privacy Yuhan Liu *, Ananda Theertha Suresh , Wennan Zhu , Peter Kairouz , Marco Gruteser Bandit Online Linear Optimization with Hints and Queries Aditya Bhaskara , Ashok Cutkosky , Ravi Kumar (..)

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How to Improve User Experience (and Behavior): Three Papers from Stanford's Alexa Prize Team

Stanford AI Lab Blog

. ↩ Roller, Stephen, Emily Dinan, Naman Goyal, Da Ju, Mary Williamson, Yinhan Liu, Jing Xu et al. Towards empathetic open-domain conversation models: A new benchmark and dataset. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pages 5370-5381, Florence, Italy.

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Google at NeurIPS 2022

Google Research AI blog

Chi The Nature of Temporal Difference Errors in Multi-step Distributional Reinforcement Learning Yunhao Tang, Mark Rowland, Rémi Munos, Bernardo Ávila Pires, Will Dabney, Marc G. Ruoxi Sun , Hanjun Dai , Adams Yu Drawing Out of Distribution with Neuro-Symbolic Generative Models Yichao Liang, Joshua B.

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Genspark’s Super Agent ups the ante in the general AI agent race

VentureBeat

This week, Palo Alto-based startup Genspark released what it calls Super Agent, a fast-moving autonomous system designed to handle real-world tasks across a wide range of domains including some that raise eyebrows, like making phone calls to restaurants using a realistic synthetic voice. Read More

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