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Found 4 papers, 1 papers with code
Multi Task Inverse Reinforcement Learning for Common Sense Reward
One of the challenges in applying reinforcement learning in a complex real-world environment lies in providing the agent with a sufficiently detailed reward function.
Combining Language Models For Specialized Domains: A Colorful Approach
In this work, we introduce a novel approach that integrates domain-specific or secondary LM into general-purpose LM.
Open-vocabulary Keyword-spotting with Adaptive Instance Normalization
Open vocabulary keyword spotting is a crucial and challenging task in automatic speech recognition (ASR) that focuses on detecting user-defined keywords within a spoken utterance.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
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Auxiliary Learning as an Asymmetric Bargaining Game
Auxiliary learning is an effective method for enhancing the generalization capabilities of trained models, particularly when dealing with small datasets.
