Customer-obsessed science
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August 21, 20269 min readExtendable framework enables testing agents on the full set of capabilities required to successfully complete a procedure, not isolated proxy tasks. -
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July 9, 202610 min read
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Featured news
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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Who moderates on Twitch and what do they do? Quantifying practices in community moderation on TwitchGROUP 20232023Volunteer moderators are an increasingly essential component of effective community management across a range of services, such as Facebook, Reddit, Discord, YouTube, and Twitch. Prior work has investigated how users of these services become moderators, their attitudes towards community moderation, and the work that they perform, largely through interviews with community moderators and managers. In this
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WACV 2023 Workshop on Pretraining Large Vision and Multimodal Models2023Data augmentation is a necessity to enhance data efficiency in deep learning. For vision-language pre-training, data is only augmented either for images or for text in previous works. In this paper, we present MixGen: a joint data augmentation for vision-language representation learning to further improve data efficiency. It generates new imagetext pairs with semantic relationships preserved by interpolating
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WSDM 20232023Semantic matching is an important component of a product search pipeline. Its goal is to capture the semantic intent of the search query as opposed to the syntactic matching performed by a lexical matching system. A semantic matching model captures relationships like synonyms, and also captures common behavioral patterns to retrieve relevant results by generalizing from purchase data. Semantic matching
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AAAI 2023 Workshop on Uncertainty Reasoning and Quantification in Decision Making2023Conversational agents like chat bots and voice assistants are trained to understand and respond to user intents. On encountering an utterance with an intent different from the ones they have been trained on, these agents are expected to classify the intent as “unknown” or “out of domain”. This problem is known as out of domain (OOD) intent detection. Podolskiy et al. (2021), showed that Mahalanobis distance
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WACV 2023 Workshop on Video/Audio Quality in Computer Vision2023Video quality assessment (VQA) has sparked a lot of interest in the computer vision community, as it plays a critical role in services that provide customers with high quality video content. Due to the lack of high quality reference videos and the difficulties in collecting subjective evaluations, assessing video quality is a challenging and still unsolved problem. Moreover, most of the public research
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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.
Credit: Wolfram Scheible
We partner with particular academic organizations across the world for deep and sustained collaborations in multiple research areas of mutual interest.
Courtesy of Pai-Ling Yin
We hire world-class academics to work on large-scale technical challenges, while they continue to teach and conduct research at their universities.
