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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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Initiative will fund over 100 doctoral students researching machine learning, computer vision, and natural-language processing at nine universities.
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NAACL 20222022Recent work in entity disambiguation (ED) has typically neglected structured knowledge base (KB) facts, and instead relied on a limited subset of KB information, such as entity descriptions or types. This limits the range of contexts in which entities can be disambiguated. To allow the use of all KB facts, as well as descriptions and types, we introduce an ED model which links entities by reasoning over
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CVPR 2022 Workshop on Gaze Estimation and Prediction in the Wild2022The classic object referring task aims at localizing the referred object in the image and requires a reference image and a natural language description as inputs. Given the facts that gaze signal can be easily obtained by a modern human-computer interaction system with a camera and that human tends to look at the object when referring to it, we propose a novel gaze-assisted object referring framework. The
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IWSLT 20222022This paper describes Amazon Alexa AI’s submission to the IWSLT 2022 Offline Speech Translation Task. Our system is an end-to-end speech translation model that leverages pre-trained models and cross modality transfer learning. We detail two improvements to the knowledge transfer schema. First, we implemented a new loss function that reduces knowledge gap between audio and text modalities in translation task
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NAACL 20222022Abstractive summarization models are typically pre-trained on large amounts of generic texts, then fine-tuned on tens or hundreds of thousands of annotated samples. However, in opinion summarization, large annotated datasets of reviews paired with reference summaries are not available and would be expensive to create. This calls for fine-tuning methods robust to overfitting on small datasets. In addition
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ICASSP 20222022Multimodal active speaker detection (ASD) methods assign a speaking/not-speaking label per individual in a video clip. ASD is critical for applications such as natural human-computer interaction, speaker diarization, and video reframing. Recent work has shown the success of transformers in multimodal settings, thus we propose a novel framework that leverages modern transformer and concatenation mechanisms
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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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