Titlebook: Chinese ComputationalLinguistics; 20th China National Sheng Li,Maosong Sun,Gaoqi Rao Conference proceedings 2021 Springer Nature Switzerla

BUMP

Hypopnea

不規(guī)則的跳動(dòng)

Lecture Notes in Computer Sciencepresent a novel multi-speaker dialogue summarizer to demonstrate how large-scale commonsense knowledge can facilitate dialogue understanding and summary generation. In detail, we consider utterance and commonsense knowledge as two different types of data and design a Dialogue Heterogeneous Graph Net

白楊

緯度

micronutrients

Norbert Hundeshagen,Martin Langele by asking several Yes/No questions which are answered by oracle. How to ask proper questions is crucial to achieve the final goal of the whole task. Previous methods generally use an word-level generator, which is hard to grasp the dialogue-level questioning strategy. They often generate repeated

Insubordinate

Reaching Algebra Readiness (RAR)on classification. Most previous works on few-shot relation classification are based on learning-to-match paradigms, which focus on learning an effective universal matcher between the query and . target class prototype based on inner-class support sets. However, the learning-to-match paradigm focuse

迎合

Reaching Algebra Readiness (RAR)dels generally fall into two separate parts: evidence extraction and answer prediction, where the former extracts the key evidence corresponding to the question, and the latter predicts the answer based on those sentences. However, such pipeline paradigms tend to accumulate errors, i.e. extracting t

cogitate

palliate

Low-Resource Machine Translation Based on Asynchronous Dynamic Programmingent learning affect the performance of the model. The reward for generating translation is determined by the scalability and iteration of the sampling strategy, so it is difficult for the model to achieve bias-variance trade-off. Therefore, according to the poor ability of the model to analyze the s