Zobrazeno 1 - 10
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pro vyhledávání: '"Khosla P"'
Over the past decade, predictive modeling of neural responses in the primate visual system has advanced significantly, largely driven by various DNN approaches. These include models optimized directly for visual recognition, cross-modal alignment thr
Externí odkaz:
http://arxiv.org/abs/2410.14031
Publikováno v:
Published in Data-centric Machine Learning Research Worshop @ ICML 2024
Graph Neural Networks (GNNs) have achieved state-of-the-art results in node classification tasks. However, most improvements are in multi-class classification, with less focus on the cases where each node could have multiple labels. The first challen
Externí odkaz:
http://arxiv.org/abs/2406.12439
In recent years, continual learning (CL) techniques have made significant progress in learning from streaming data while preserving knowledge across sequential tasks, particularly in the realm of euclidean data. To foster fair evaluation and recogniz
Externí odkaz:
http://arxiv.org/abs/2406.01229
Pre-trained deep learning (DL) models are increasingly accessible in public repositories, i.e., model zoos. Given a new prediction task, finding the best model to fine-tune can be computationally intensive and costly, especially when the number of pr
Externí odkaz:
http://arxiv.org/abs/2404.03988
Autor:
Lu, Jiasen, Clark, Christopher, Lee, Sangho, Zhang, Zichen, Khosla, Savya, Marten, Ryan, Hoiem, Derek, Kembhavi, Aniruddha
We present Unified-IO 2, the first autoregressive multimodal model that is capable of understanding and generating image, text, audio, and action. To unify different modalities, we tokenize inputs and outputs -- images, text, audio, action, bounding
Externí odkaz:
http://arxiv.org/abs/2312.17172
Autor:
Kohli, Guneet Singh, Parida, Shantipriya, Sekhar, Sambit, Saha, Samirit, Nair, Nipun B, Agarwal, Parul, Khosla, Sonal, Patiyal, Kusumlata, Dhal, Debasish
Building LLMs for languages other than English is in great demand due to the unavailability and performance of multilingual LLMs, such as understanding the local context. The problem is critical for low-resource languages due to the need for instruct
Externí odkaz:
http://arxiv.org/abs/2312.12624
This paper explores Memory-Augmented Neural Networks (MANNs), delving into how they blend human-like memory processes into AI. It covers different memory types, like sensory, short-term, and long-term memory, linking psychological theories with AI ap
Externí odkaz:
http://arxiv.org/abs/2312.06141
Purpose: Enhanced health literacy has been linked to better health outcomes; however, few interventions have been studied. We investigate whether large language models (LLMs) can serve as a medium to improve health literacy in children and other popu
Externí odkaz:
http://arxiv.org/abs/2311.10075
Autor:
Khosla, Meenakshi, Williams, Alex H.
Common measures of neural representational (dis)similarity are designed to be insensitive to rotations and reflections of the neural activation space. Motivated by the premise that the tuning of individual units may be important, there has been recen
Externí odkaz:
http://arxiv.org/abs/2311.09466
We present BYOKG, a universal question-answering (QA) system that can operate on any knowledge graph (KG), requires no human-annotated training data, and can be ready to use within a day -- attributes that are out-of-scope for current KGQA systems. B
Externí odkaz:
http://arxiv.org/abs/2311.07850