Sep 17, 2019 · A model with stronger length control capacity can produce sentences with more specific length, however, it usually sacrifices semantic accuracy ...
Two reinforcement learning methods to adjust the trade-off between length control capacity and semantic accuracy of length control models are proposed and ...
Here, we denote a concept of Controllable Length Control (CLC) for the trade-off between length control capacity and semantic accuracy of the language ...
Dec 11, 2022 · This work employs reinforcement learning (RL) for unsupervised abstractive summarization1. RL enables a model to learn to summarize using re-.
Sep 17, 2019 · To control the output length, Kikuchi et al. (2016) first proposed two learning-based models for neural encoder- decoder named LenInit and ...
Controllable Length Control Neural Encoder-Decoder via Reinforcement Learning, length control, 2019, local. 10, Controllable Text Simplification with Lexical ...
In this paper, we propose and investigate four methods for controlling the output sequence length for neural encoder-decoder models. The former two methods are ...
Missing: Reinforcement | Show results with:Reinforcement
Two decoding-based and two learning-based methods are proposed for controlling the output sequence length for neural encoder-decoder models and show that ...
Missing: via Reinforcement
In this paper, we propose methods for controlling the output sequence length for neural encoder-decoder models: two decoding-based methods and two learning- ...
Apr 16, 2019 · Controllable Length Control Neural Encoder-Decoder via Reinforcement Learning. Controlling output length in neural language generation is ...
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