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Using Captum to Explain Generative Language Models
Captum is a comprehensive library for model explainability in PyTorch, offering a range of methods from the interpretability literature to enhance users' understanding of PyTorch models.
A Smart Adaptively Reconfigurable DC Battery for Higher Efficiency of Electric Vehicle Drive Trains
Furthermore, it can substantially reduce the distortion, particularly at lower modulation indices, e. g., down to 1/2 compared to conventional space-vector modulation and even 1/3 for discontinuous pulse-width modulation with hard-wired battery.
Comparative Explanations of Recommendations
As recommendation is essentially a comparative (or ranking) process, a good explanation should illustrate to users why an item is believed to be better than another, i. e., comparative explanations about the recommended items.
Explanation as a Defense of Recommendation
At training time, the two learning tasks are joined by a latent sentiment vector, which is encoded by the recommendation module and used to make word choices for explanation generation.
