IEEE

Learning From Multi-Perception Features for Real-Word Image Super-Resolution

Abstract: Actual image super-resolution is an extremely challenging task due to complex degradations existing in the image. To solve this problem, two dominant methodologies have emerged: ...
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‘We have a lot of problems’ Amorim reflects on 2-2 draw at Tottenham

‘We have a lot of problems’ Amorim reflects on 2-2 draw at Tottenham The members of Congress who got paid during the government shutdown US bishops announce new Bible changes for America Police raided ...
marktechpost

Google AI Unveils Supervised Reinforcement Learning (SRL): A Step Wise Framework with Expert Trajectories to Teach Small Language Models to Reason through Hard Problems

How can a small model learn to solve tasks it currently fails at, without rote imitation or relying on a correct rollout? A team of researchers from Google Cloud AI Research and UCLA have released a ...
syncedreview

Do NLP Models Cheat at Math Word Problems? Microsoft Research Says Even SOTA Models Rely on Shallow Heuristics

“Yoshua recently turned 57. He is three years younger than Yann. How old is Yann?” Solving such a math word problem (MWP) requires understanding the short natural language narrative describing a state ...
IEEE

Evaluation of Deep Learning Models for Multi-Step Ahead Time Series Prediction

Abstract: Time series prediction with neural networks has been the focus of much research in the past few decades. Given the recent deep learning revolution, there has been much attention in using ...