A survey on semantic processing techniques

R Mao, K He, X Zhang, G Chen, J Ni, Z Yang… - Information …, 2024 - Elsevier
Semantic processing is a fundamental research domain in computational linguistics. In the
era of powerful pre-trained language models and large language models, the advancement …

Deep reinforcement learning for sequence-to-sequence models

Y Keneshloo, T Shi, N Ramakrishnan… - IEEE transactions on …, 2019 - ieeexplore.ieee.org
In recent times, sequence-to-sequence (seq2seq) models have gained a lot of popularity
and provide state-of-the-art performance in a wide variety of tasks, such as machine …

Dcr-net: A deep co-interactive relation network for joint dialog act recognition and sentiment classification

L Qin, W Che, Y Li, M Ni, T Liu - Proceedings of the AAAI conference on …, 2020 - ojs.aaai.org
In dialog system, dialog act recognition and sentiment classification are two correlative tasks
to capture speakers' intentions, where dialog act and sentiment can indicate the explicit and …

A comprehensive review on feature set used for anaphora resolution

K Lata, P Singh, K Dutta - Artificial Intelligence Review, 2021 - Springer
Abstract In linguistics, the Anaphora Resolution (AR) is the method of identifying the
antecedent for anaphora. In simple terms, this is the problem that helps to solve what the …

CASA: Conversational aspect sentiment analysis for dialogue understanding

L Song, C Xin, S Lai, A Wang, J Su, K Xu - Journal of Artificial Intelligence …, 2022 - jair.org
Dialogue understanding has always been a bottleneck for many conversational tasks, such
as dialogue response generation and conversational question answering. To expedite the …

Deep reinforcement learning for chinese zero pronoun resolution

Q Yin, Y Zhang, W Zhang, T Liu, WY Wang - arXiv preprint arXiv …, 2018 - arxiv.org
Deep neural network models for Chinese zero pronoun resolution learn semantic
information for zero pronoun and candidate antecedents, but tend to be short-sighted---they …

Zero pronoun resolution with attention-based neural network

Q Yin, Y Zhang, W Zhang, T Liu… - Proceedings of the 27th …, 2018 - aclanthology.org
Recent neural network methods for zero pronoun resolution explore multiple models for
generating representation vectors for zero pronouns and their candidate antecedents …

ZPR2: Joint zero pronoun recovery and resolution using multi-task learning and BERT

L Song, K Xu, Y Zhang, J Chen… - Proceedings of the 58th …, 2020 - aclanthology.org
Zero pronoun recovery and resolution aim at recovering the dropped pronoun and pointing
out its anaphoric mentions, respectively. We propose to better explore their interaction by …

One model to learn both: Zero pronoun prediction and translation

L Wang, Z Tu, X Wang, S Shi - arXiv preprint arXiv:1909.00369, 2019 - arxiv.org
Zero pronouns (ZPs) are frequently omitted in pro-drop languages, but should be recalled in
non-pro-drop languages. This discourse phenomenon poses a significant challenge for …

Cross-lingual zero pronoun resolution

A Aloraini, M Poesio - … of the Twelfth Language Resources and …, 2020 - aclanthology.org
Abstract In languages like Arabic, Chinese, Italian, Japanese, Korean, Portuguese, Spanish,
and many others, predicate arguments in certain syntactic positions are not realized instead …