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pro vyhledávání: '"Afra, A."'
This work examines the fairness of generative mobility models, addressing the often overlooked dimension of equity in model performance across geographic regions. Predictive models built on crowd flow data are instrumental in understanding urban stru
Externí odkaz:
http://arxiv.org/abs/2411.04453
Numerous previous studies have sought to determine to what extent language models, pretrained on natural language text, can serve as useful models of human cognition. In this paper, we are interested in the opposite question: whether we can directly
Externí odkaz:
http://arxiv.org/abs/2410.13086
Transformer-based language models have shown an excellent ability to effectively capture and utilize contextual information. Although various analysis techniques have been used to quantify and trace the contribution of single contextual cues to a tar
Externí odkaz:
http://arxiv.org/abs/2410.03447
Neural speech models build deeply entangled internal representations, which capture a variety of features (e.g., fundamental frequency, loudness, syntactic category, or semantic content of a word) in a distributed encoding. This complexity makes it d
Externí odkaz:
http://arxiv.org/abs/2410.03037
Indonesia ranks fourth globally in the number of deaf cases. Individuals with hearing impairments often find communication challenging, necessitating the use of sign language. However, there are limited public services that offer such inclusivity. On
Externí odkaz:
http://arxiv.org/abs/2409.01975
Best-of-N (BoN) is a popular and effective algorithm for aligning language models to human preferences. The algorithm works as follows: at inference time, N samples are drawn from the language model, and the sample with the highest reward, as judged
Externí odkaz:
http://arxiv.org/abs/2407.06057
Human listeners effortlessly compensate for phonological changes during speech perception, often unconsciously inferring the intended sounds. For example, listeners infer the underlying /n/ when hearing an utterance such as "clea[m] pan", where [m] a
Externí odkaz:
http://arxiv.org/abs/2406.15265
Theory of Mind (ToM) reasoning entails recognizing that other individuals possess their own intentions, emotions, and thoughts, which is vital for guiding one's own thought processes. Although large language models (LLMs) excel in tasks such as summa
Externí odkaz:
http://arxiv.org/abs/2406.05659
Autonomous Vehicles (AVs) redefine transportation with sophisticated technology, integrating sensors, cameras, and intricate algorithms. Implementing machine learning in AV perception demands robust hardware accelerators to achieve real-time performa
Externí odkaz:
http://arxiv.org/abs/2405.00062
Autor:
Malagutti, Luca, Buinovskij, Andrius, Svete, Anej, Meister, Clara, Amini, Afra, Cotterell, Ryan
For nearly three decades, language models derived from the $n$-gram assumption held the state of the art on the task. The key to their success lay in the application of various smoothing techniques that served to combat overfitting. However, when neu
Externí odkaz:
http://arxiv.org/abs/2403.17240