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Neural Topic Model with Reinforcement Learning

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Figure

Figure 1: Neural topic model with reinforcement learning.
Table 1: Perplexity and topic coherence results of dif-ference models. ‘the vocabulary is constructed by filtering out rare wordswhile ‘frequency-based vocab.’ denotes thatRL-based vocab.’ denotes that the vocabulary isdynamically generated by our model using RL.
Table 2: Number of parameters for each model and theaverage training time per epoch with vocabulary size2,000 and topic number 50.

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