Zobrazeno 1 - 10
of 23 214
pro vyhledávání: '"A. A, Danish"'
Machine learning (ML) based indoor localization solutions are critical for many emerging applications, yet their efficacy is often compromised by hardware/software variations across mobile devices (i.e., device heterogeneity) and the threat of ML dat
Externí odkaz:
http://arxiv.org/abs/2411.09055
While a large body of work inspects language models for biases concerning gender, race, occupation and religion, biases of geographical nature are relatively less explored. Some recent studies benchmark the degree to which large language models encod
Externí odkaz:
http://arxiv.org/abs/2411.07320
Autor:
Rastogi, Saksham, Pruthi, Danish
Amidst rising concerns about the internet being proliferated with content generated from language models (LMs), watermarking is seen as a principled way to certify whether text was generated from a model. Many recent watermarking techniques slightly
Externí odkaz:
http://arxiv.org/abs/2411.05277
We introduce a manifold analysis technique for neural network representations. Normalized Space Alignment (NSA) compares pairwise distances between two point clouds derived from the same source and having the same size, while potentially possessing d
Externí odkaz:
http://arxiv.org/abs/2411.04512
Medical image segmentation is pivotal in healthcare, enhancing diagnostic accuracy, informing treatment strategies, and tracking disease progression. This process allows clinicians to extract critical information from visual data, enabling personaliz
Externí odkaz:
http://arxiv.org/abs/2410.22223
Language models are now deployed in a wide variety of user-facing applications, often for specific purposes like answering questions about documentation or acting as coding assistants. As these models are intended for particular purposes, they should
Externí odkaz:
http://arxiv.org/abs/2410.21597
Historically, machine learning training pipelines have predominantly relied on batch training models, retraining models every few hours. However, industrial practitioners have proved that real-time training can lead to a more adaptive and personalize
Externí odkaz:
http://arxiv.org/abs/2410.15533
In this work, we focus our attention on developing a benchmark for instruction-following where it is easy to verify both task performance as well as instruction-following capabilities. We adapt existing knowledge benchmarks and augment them with inst
Externí odkaz:
http://arxiv.org/abs/2410.12972
Modern machine learning (ML) models of chemical and materials systems with billions of parameters require vast training datasets and considerable computational efforts. Lightweight kernel or decision tree based methods, however, can be rapidly traine
Externí odkaz:
http://arxiv.org/abs/2409.20471
Website accessibility is essential for inclusiveness and regulatory compliance. Although third-party advertisements (ads) are a vital revenue source for free web services, they introduce significant accessibility challenges. Leasing a website\'s spac
Externí odkaz:
http://arxiv.org/abs/2409.18590