Zobrazeno 1 - 10
of 4 545
pro vyhledávání: '"Little, A. J."'
With the advent of Large Language Models (LLMs) and Multimodal (Visio-lingual) LLMs, a flurry of research has emerged, analyzing the performance of such models across a diverse array of tasks. While most studies focus on evaluating the capabilities o
Externí odkaz:
http://arxiv.org/abs/2410.04778
Autor:
Goyal, Ravi, Nguyen, Kevin, De Gruttola, Victor, Little, Susan J, Cohen, Colby, Martin, Natasha K
Molecular HIV Surveillance (MHS) has been described as key to enabling rapid responses to HIV outbreaks. It operates by linking individuals with genetically similar viral sequences, which forms a network. A major limitation of MHS is that it depends
Externí odkaz:
http://arxiv.org/abs/2407.16135
Autor:
Chow, Matthew N. H., Buchemmavari, Vikas, Omanakuttan, Sivaprasad, Little, Bethany J., Pandey, Saurabh, Deutsch, Ivan H., Jau, Yuan-Yu
Publikováno v:
PRX Quantum 5, 040343 (2024)
Leakage out of the computational subspace is a major limitation of current state-of-the-art neutral-atom quantum computers and a significant challenge for scalable systems. In a quantum processor with cesium atoms, we demonstrate proof-of-principle c
Externí odkaz:
http://arxiv.org/abs/2405.10434
The emergence of attention-based transformer models has led to their extensive use in various tasks, due to their superior generalization and transfer properties. Recent research has demonstrated that such models, when prompted appropriately, are exc
Externí odkaz:
http://arxiv.org/abs/2404.11732
Existing dense or paragraph video captioning approaches rely on holistic representations of videos, possibly coupled with learned object/action representations, to condition hierarchical language decoders. However, they fundamentally lack the commons
Externí odkaz:
http://arxiv.org/abs/2303.07545
Publikováno v:
2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), Waikoloa, HI, USA, 2024, pp. 988-998
Recent advances in pixel-level tasks (e.g. segmentation) illustrate the benefit of of long-range interactions between aggregated region-based representations that can enhance local features. However, such aggregated representations, often in the form
Externí odkaz:
http://arxiv.org/abs/2212.03338
We propose a bootstrapping framework to enhance human optical flow and pose. We show that, for videos involving humans in scenes, we can improve both the optical flow and the pose estimation quality of humans by considering the two tasks at the same
Externí odkaz:
http://arxiv.org/abs/2210.15121
Neural Radiance Fields (NeRFs) increase reconstruction detail for novel view synthesis and scene reconstruction, with applications ranging from large static scenes to dynamic human motion. However, the increased resolution and model-free nature of su
Externí odkaz:
http://arxiv.org/abs/2206.11952
We demonstrate discrimination of ground-state hyperfine manifolds of a cesium atom in an optical tweezer using a simple probe beam with 99.91(2)% detection fidelity and 0.9(2)% detection-driven loss of bright state atoms. Our detection infidelity of
Externí odkaz:
http://arxiv.org/abs/2206.00144
Publikováno v:
In Computer Vision and Image Understanding October 2024 247
