DE eng

Search in the Catalogues and Directories

Hits 1 – 20 of 20

1
Enhancing Cross-lingual Prompting with Mask Token Augmentation ...
Zhou, Meng; Li, Xin; Jiang, Yue. - : arXiv, 2022
BASE
Show details
2
Cross-lingual Aspect-based Sentiment Analysis with Aspect Term Code-Switching ...
BASE
Show details
3
Towards Multi-Sense Cross-Lingual Alignment of Contextual Embeddings ...
BASE
Show details
4
Knowledge Based Multilingual Language Model ...
Liu, Linlin; Li, Xin; He, Ruidan. - : arXiv, 2021
BASE
Show details
5
MELM: Data Augmentation with Masked Entity Language Modeling for Low-Resource NER ...
Zhou, Ran; Li, Xin; He, Ruidan. - : arXiv, 2021
BASE
Show details
6
Multilingual AMR Parsing with Noisy Knowledge Distillation ...
BASE
Show details
7
GlobalWoZ: Globalizing MultiWoZ to Develop Multilingual Task-Oriented Dialogue Systems ...
BASE
Show details
8
Multi-perspective Coherent Reasoning for Helpfulness Prediction of Multimodal Reviews ...
BASE
Show details
9
On the Effectiveness of Adapter-based Tuning for Pretrained Language Model Adaptation ...
BASE
Show details
10
Towards Generative Aspect-Based Sentiment Analysis ...
BASE
Show details
11
Argument Pair Extraction via Attention-guided Multi-Layer Multi-Cross Encoding ...
BASE
Show details
12
Learning Span-Level Interactions for Aspect Sentiment Triplet Extraction ...
Abstract: Read paper: https://www.aclanthology.org/2021.acl-long.367 Abstract: Aspect Sentiment Triplet Extraction (ASTE) is the most recent subtask of ABSA which outputs triplets of an aspect target, its associated sentiment, and the corresponding opinion term. Recent models perform the triplet extraction in an end-to-end manner but heavily rely on the interactions between each target word and opinion word. Thereby, they cannot perform well on targets and opinions which contain multiple words. Our proposed span-level approach explicitly considers the interaction between the whole spans of targets and opinions when predicting their sentiment relation. Thus, it can make predictions with the semantics of whole spans, ensuring better sentiment consistency. To ease the high computational cost caused by span enumeration, we propose a dual-channel span pruning strategy by incorporating supervision from the Aspect Term Extraction (ATE) and Opinion Term Extraction (OTE) tasks. This strategy not only improves computational ...
Keyword: Computational Linguistics; Condensed Matter Physics; Deep Learning; Electromagnetism; FOS Physical sciences; Information and Knowledge Engineering; Neural Network; Semantics
URL: https://underline.io/lecture/26091-learning-span-level-interactions-for-aspect-sentiment-triplet-extraction
https://dx.doi.org/10.48448/6erd-yc36
BASE
Hide details
13
MulDA: A Multilingual Data Augmentation Framework for Low-Resource Cross-Lingual NER ...
BASE
Show details
14
Unsupervised Cross-lingual Adaptation for Sequence Tagging and Beyond ...
Li, Xin; Bing, Lidong; Zhang, Wenxuan. - : arXiv, 2020
BASE
Show details
15
Dynamic Topic Tracker for KB-to-Text Generation
BASE
Show details
16
Transferable End-to-End Aspect-based Sentiment Analysis with Selective Adversarial Learning ...
Li, Zheng; Li, Xin; Wei, Ying. - : arXiv, 2019
BASE
Show details
17
A knowledge regularized hierarchical approach for emotion cause analysis
Gui, Lin; Bing, Lidong; Xu, Ruifeng. - : Association for Computational Linguistics, 2019
BASE
Show details
18
Neural Rating Regression with Abstractive Tips Generation for Recommendation ...
Li, Piji; Wang, Zihao; Ren, Zhaochun. - : arXiv, 2017
BASE
Show details
19
Reader-Aware Multi-Document Summarization via Sparse Coding ...
Li, Piji; Bing, Lidong; Lam, Wai. - : arXiv, 2015
BASE
Show details
20
Abstractive Multi-Document Summarization via Phrase Selection and Merging ...
Bing, Lidong; Li, Piji; Liao, Yi. - : arXiv, 2015
BASE
Show details

Catalogues
0
0
0
0
0
0
0
Bibliographies
0
0
0
0
0
0
0
0
0
Linked Open Data catalogues
0
Online resources
0
0
0
0
Open access documents
20
0
0
0
0
© 2013 - 2024 Lin|gu|is|tik | Imprint | Privacy Policy | Datenschutzeinstellungen ändern