Baobao Chang

5.9k total citations · 2 hit papers
110 papers, 2.8k citations indexed

About

Baobao Chang is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition. According to data from OpenAlex, Baobao Chang has authored 110 papers receiving a total of 2.8k indexed citations (citations by other indexed papers that have themselves been cited), including 98 papers in Artificial Intelligence, 11 papers in Information Systems and 11 papers in Computer Vision and Pattern Recognition. Recurrent topics in Baobao Chang's work include Topic Modeling (78 papers), Natural Language Processing Techniques (73 papers) and Advanced Text Analysis Techniques (19 papers). Baobao Chang is often cited by papers focused on Topic Modeling (78 papers), Natural Language Processing Techniques (73 papers) and Advanced Text Analysis Techniques (19 papers). Baobao Chang collaborates with scholars based in China, United States and India. Baobao Chang's co-authors include Zhifang Sui, Lei Sha, Tao Ge, Furu Wei, Ming Zhou, Wenhui Wang, Nan Yang, Runxin Xu, Tianyu Liu and Fuli Luo and has published in prestigious journals such as Physics of Fluids, Lecture notes in computer science and Language Resources and Evaluation.

In The Last Decade

Baobao Chang

101 papers receiving 2.6k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Gated Self-Matching Networks for Reading Comprehension and Question Answering

2017 360 citations Baobao Chang et al. profile →
A Survey on In-context Learning

2024 173 citations Damai Dai, Ce Zheng et al. profile →

Peers

Baobao Chang

AI

CVPR

IS

MSOR

MB

Zhifang Sui China

Gabor Angeli United States

Xu Han China

Chengqing Zong China

Tianyu Gao China

Ivan Vulić United Kingdom

Jonathan Berant Israel

Shay B. Cohen United Kingdom

Antoine Bordes Israel

Ting Liu China

Zhifang Sui China

Baobao Chang

1.7k ×0.7

AI

359 ×0.7

CVPR

259 ×0.7

IS

124 ×0.8

MSOR

101 ×0.8

MB

Citations per year, relative to Baobao Chang Baobao Chang (= 1×) peers Zhifang Sui

Countries citing papers authored by Baobao Chang

Since Specialization

Citations

This map shows the geographic impact of Baobao Chang's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Baobao Chang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Baobao Chang more than expected).

Fields of papers citing papers by Baobao Chang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Baobao Chang. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Baobao Chang. The network helps show where Baobao Chang may publish in the future.

Co-authorship network of co-authors of Baobao Chang

This figure shows the co-authorship network connecting the top 25 collaborators of Baobao Chang. A scholar is included among the top collaborators of Baobao Chang based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Baobao Chang. Baobao Chang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Zhang, Rongyu, Huanrui Yang, Denis Gudovskiy, et al.. (2024). VeCAF: Vision-language Collaborative Active Finetuning with Training Objective Awareness. 5451–5459. 3 indexed citations

2.

Zeng, Shuang, et al.. (2023). SANTA: Separate Strategies for Inaccurate and Incomplete Annotation Noise in Distantly-Supervised Named Entity Recognition. 3883–3896. 2 indexed citations

3.

Zheng, Ce, Yiming Wang, & Baobao Chang. (2023). Query Your Model with Definitions in FrameNet: An Effective Method for Frame Semantic Role Labeling. Proceedings of the AAAI Conference on Artificial Intelligence. 37(11). 14029–14037. 3 indexed citations

4.

Xu, Runxin, Tianyu Liu, Lei Li, & Baobao Chang. (2021). Document-level Event Extraction via Heterogeneous Graph-based Interaction Model with a Tracker. 3533–3546. 51 indexed citations

5.

Zheng, Hua, Damai Dai, Lei Li, et al.. (2021). Decompose, Fuse and Generate: A Formation-Informed Method for Chinese Definition Generation. 5524–5531. 3 indexed citations

6.

Wang, Kexiang, Tianyu Liu, Baobao Chang, & Zhifang Sui. (2020). An Anchor-Based Automatic Evaluation Metric for Document Summarization. 5696–5701. 1 indexed citations

7.

Liu, Tianyu, Xin Zheng, Baobao Chang, & Zhifang Sui. (2020). HypoNLI: Exploring the Artificial Patterns of Hypothesis-only Bias in Natural Language Inference. arXiv (Cornell University). 6852–6860. 2 indexed citations

8.

Wang, Kexiang, Baobao Chang, & Zhifang Sui. (2020). A Spectral Method for Unsupervised Multi-Document Summarization. 435–445. 8 indexed citations

9.

Luo, Fuli, Peng Li, Pengcheng Yang, et al.. (2019). Towards Fine-grained Text Sentiment Transfer. 2013–2022. 21 indexed citations

10.

Luo, Fuli, Damai Dai, Pengcheng Yang, et al.. (2019). Learning to Control the Fine-grained Sentiment for Story Ending Generation. 6020–6026. 29 indexed citations

11.

Sui, Zhifang, et al.. (2019). Preliminary Study on the Construction of Chinese Medical Knowledge Graph. 33(10). 1–9. 36 indexed citations

12.

Jiang, Tingsong, Tianyu Liu, Tao Ge, et al.. (2016). Encoding Temporal Information for Time-Aware Link Prediction. 2350–2354. 65 indexed citations

13.

Sha, Lei, Baobao Chang, Zhifang Sui, & Sujian Li. (2016). Reading and Thinking: Re-read LSTM Unit for Textual Entailment Recognition. International Conference on Computational Linguistics. 2870–2879. 36 indexed citations

14.

Ge, Tao, Lei Cui, Baobao Chang, Zhifang Sui, & Ming Zhou. (2016). Event Detection with Burst Information Networks. International Conference on Computational Linguistics. 3276–3286. 12 indexed citations

15.

Jiang, Tingsong, Tianyu Liu, Tao Ge, et al.. (2016). Towards Time-Aware Knowledge Graph Completion. International Conference on Computational Linguistics. 1715–1724. 47 indexed citations

16.

Chang, Baobao & Dongxu Han. (2010). Enhancing Domain Portability of Chinese Segmentation Model Using Chi-Square Statistics and Bootstrapping. Empirical Methods in Natural Language Processing. 789–798. 7 indexed citations

17.

Chang, Baobao. (2010). Maximum Margin Markov Networks-Based Chinese Word Segmentation Method. Zhongwen xinxi xuebao. 1 indexed citations

18.

Chang, Baobao. (2009). Chinese Semantic Role Labeling Based on Semantic Chunking. Zhongwen xinxi xuebao. 1 indexed citations

19.

Chang, Baobao. (2008). Maximum Entropy-Based Semantic Role Classification. Zhongwen xinxi xuebao.

20.

Chang, Baobao. (2007). Chinese Multi-word Chunks Extraction for Computer Aided Translation. Zhongwen xinxi xuebao. 2 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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