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July 30, 20268 min readInstead of compromising among parameter updates dictated by different training objectives, ControlG allocates computational capacity to objectives sequentially and dynamically. -
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July 9, 202610 min read
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The Build on Trainium program is a $110 million credit initiative supporting AI research at 30 universities including Stanford, UC Berkeley, UIUC, UCLA, CMU, and MIT, with a focus on Responsible AI.
The Antibody Developability Benchmark is powered by one of the most diverse antibody datasets in public literature, enabling transparent performance evaluation for AI-guided antibody design.
Challenge pushes teams to demonstrate measurable gains in secure-coding performance while building AI agents that advance real-world utility and reliability at scale.
Initiative will fund over 100 doctoral students researching machine learning, computer vision, and natural-language processing at nine universities.
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ICLR 2021 Workshop on Practical ML for Developing Countries2021While the strong zero-shot performance of multilingual BERT has been shown to drop in case of word order divergence between source and target language, the problem has been studied rarely to date. In this paper, we explore light-weight techniques to improve BERT-based zero-shot spoken language understanding for English-Hindi, which are languages with divergent word orders. We show that word order divergence
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EACL 20212021Voice assistants, e.g., Alexa or Google Assistant, have dramatically improved in recent years. Supporting voice-based search, exploration, and refinement are fundamental tasks for voice assistants, and remain an open challenge. For example, when using voice to search an online shopping site, a user often needs to refine their search by some aspect or facet. This common user intent is usually available through
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The Web Conference 2021 Workshop on Knowledge Management in E-Commerce2021The vocabulary gap between search queries and product descriptions is an important problem in modern e-commerce search engines. Most of the existing methods deal with the vocabulary gap issues by rewriting user-input queries. In this work, we describe another way to address vocabulary gap issues in the e-commerce search systems. In particular, we propose an unsupervised synonym extraction framework for
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NAACL 20212021In entity linking, mentions of named entities in raw text are disambiguated against a knowledge base (KB). This work focuses on linking to unseen KBs that do not have training data and whose schema is unknown during training. Our approach relies on methods to flexibly convert entities with several attribute-value pairs from arbitrary KBs into flat strings, which we use in conjunction with state-of-the-art
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NAACL 20212021Scaling conversational personal assistants to a multitude of languages puts high demands on collecting and labelling data, a setting in which cross-lingual learning techniques can help to reconcile the need for well-performing natural language understanding (NLU) with a desideratum to support many languages without incurring unacceptable cost. In this paper, we show that automatically annotating unlabeled
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Gretchen Ertl
The program offers unrestricted funds and other resources to support research at academic institutions and non-profit organizations in areas that align with our mission.
A global university competition to drive secure innovation in generative AI technology, which focuses on responsible AI and large language model coding security.
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