Search Results for author: Qinghong Han

Found 11 papers, 6 papers with code

BertGCN: Transductive Text Classification by Combining GCN and BERT

1 code implementation12 May 2021 Yuxiao Lin, Yuxian Meng, Xiaofei Sun, Qinghong Han, Kun Kuang, Jiwei Li, Fei Wu

In this work, we propose BertGCN, a model that combines large scale pretraining and transductive learning for text classification.

text-classification Text Classification +1

OpenViDial: A Large-Scale, Open-Domain Dialogue Dataset with Visual Contexts

1 code implementation30 Dec 2020 Yuxian Meng, Shuhe Wang, Qinghong Han, Xiaofei Sun, Fei Wu, Rui Yan, Jiwei Li

Based on this dataset, we propose a family of encoder-decoder models leveraging both textual and visual contexts, from coarse-grained image features extracted from CNNs to fine-grained object features extracted from Faster R-CNNs.

Decoder Dialogue Generation

Self-Explaining Structures Improve NLP Models

1 code implementation3 Dec 2020 Zijun Sun, Chun Fan, Qinghong Han, Xiaofei Sun, Yuxian Meng, Fei Wu, Jiwei Li

The proposed model comes with the following merits: (1) span weights make the model self-explainable and do not require an additional probing model for interpretation; (2) the proposed model is general and can be adapted to any existing deep learning structures in NLP; (3) the weight associated with each text span provides direct importance scores for higher-level text units such as phrases and sentences.

Natural Language Inference Paraphrase Identification +1

Non-Autoregressive Neural Dialogue Generation

no code implementations11 Feb 2020 Qinghong Han, Yuxian Meng, Fei Wu, Jiwei Li

Unfortunately, under the framework of the \sts model, direct decoding from $\log p(y|x) + \log p(x|y)$ is infeasible since the second part (i. e., $p(x|y)$) requires the completion of target generation before it can be computed, and the search space for $y$ is enormous.

Dialogue Generation Open-Domain Dialog +1

Description Based Text Classification with Reinforcement Learning

no code implementations ICML 2020 Duo Chai, Wei Wu, Qinghong Han, Fei Wu, Jiwei Li

We observe significant performance boosts over strong baselines on a wide range of text classification tasks including single-label classification, multi-label classification and multi-aspect sentiment analysis.

General Classification Multi-Label Classification +6

A Unified MRC Framework for Named Entity Recognition

8 code implementations ACL 2020 Xiaoya Li, Jingrong Feng, Yuxian Meng, Qinghong Han, Fei Wu, Jiwei Li

Instead of treating the task of NER as a sequence labeling problem, we propose to formulate it as a machine reading comprehension (MRC) task.

Ranked #2 on Nested Mention Recognition on ACE 2004 (using extra training data)

Chinese Named Entity Recognition Entity Extraction using GAN +4

Is Word Segmentation Necessary for Deep Learning of Chinese Representations?

no code implementations ACL 2019 Xiaoya Li, Yuxian Meng, Xiaofei Sun, Qinghong Han, Arianna Yuan, Jiwei Li

Based on these observations, we conduct comprehensive experiments to study why word-based models underperform char-based models in these deep learning-based NLP tasks.

Chinese Word Segmentation Language Modelling +6

Glyce: Glyph-vectors for Chinese Character Representations

2 code implementations NeurIPS 2019 Yuxian Meng, Wei Wu, Fei Wang, Xiaoya Li, Ping Nie, Fan Yin, Muyu Li, Qinghong Han, Xiaofei Sun, Jiwei Li

However, due to the lack of rich pictographic evidence in glyphs and the weak generalization ability of standard computer vision models on character data, an effective way to utilize the glyph information remains to be found.

Chinese Dependency Parsing Chinese Named Entity Recognition +21

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