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July 10, 20265 min readHydroShear, a new physics-based simulator, teaches robots how to use their sense of touch to perform complex manipulation tasks, in a way that transfers seamlessly to the real world. -
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Hosted by Danielle Perszyk, cognitive scientist at Amazon's AGI Lab, the podcast features researchers tackling the hardest problems in agentic AI — from building reliable perception systems to designing training environments that mirror human learning.
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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Interspeech 20232023In interactive automatic speech recognition (ASR) systems, low-latency requirements limit the amount of search space that can be explored during decoding, particularly in end-to-end neural ASR. In this paper, we present a novel streaming ASR architecture that outputs a confusion network while maintaining limited latency, as needed for interactive applications. We show that 1-best results of our model are
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KDD 20232023In Learning-to-Rank (LTR) problems, the task of delivering relevant search results and allocating fair exposure to items of a protected group can conflict. Previous works in Fair LTR have attempted to resolve this by combining the objectives of relevant ranking and fair ranking into a single linear combination, but this approach is limited by the nonconvexity of the objective functions and can result in
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KDD 20232023Learning to Rank (LTR) technique is ubiquitous in Information Retrieval systems, especially in search ranking applications. The relevance labels used to train ranking models are often noisy measurements of human behavior, such as product ratings in product searches. This results in non-unique ground truth rankings and ambiguity. To address this, Multi-Label LTR (MLLTR) is used to train models using multiple
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Interspeech 20232023Speaker diarization (SD) is typically used with an automatic speech recognition (ASR) system to ascribe speaker labels to recognized words. The conventional approach reconciles outputs from independently optimized ASR and SD systems, where the SD system typically uses only acoustic information to identify the speakers in the audio stream. This approach can lead to speaker errors especially around speaker
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Interspeech 20232023Personal rare word recognition is an important yet challenging task for end-to-end speech recognition. Contextual biasing has demonstrated success in tackling this problem. Though effective in improving rare word recognition, these mechanisms can lead to errors due to false-biasing while facing further challenges when attempting to expand them to many domains. To address these limitations, in this work
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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
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Courtesy of Pai-Ling Yin
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