Xinting Huang

577 total citations · 1 hit paper
20 papers, 135 citations indexed

About

Xinting Huang is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems. According to data from OpenAlex, Xinting Huang has authored 20 papers receiving a total of 135 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Artificial Intelligence, 7 papers in Computer Vision and Pattern Recognition and 2 papers in Information Systems. Recurrent topics in Xinting Huang's work include Topic Modeling (9 papers), Natural Language Processing Techniques (8 papers) and Multimodal Machine Learning Applications (6 papers). Xinting Huang is often cited by papers focused on Topic Modeling (9 papers), Natural Language Processing Techniques (8 papers) and Multimodal Machine Learning Applications (6 papers). Xinting Huang collaborates with scholars based in China, Australia and United States. Xinting Huang's co-authors include Qili Wang, Wei Xu, Rui Zhang, Jianzhong Qi, Yu Sun, Yue Zhang, S. Shi, Yulong Chen, Freda Shi and Longyue Wang and has published in prestigious journals such as BMC Public Health, Neurocomputing and Computational Linguistics.

In The Last Decade

Xinting Huang

17 papers receiving 129 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.

🧜Siren’s Song in the AI Ocean: A Survey on Hallucination in Large Language Models

2025 27 citations Yue Zhang, Yafu Li et al. Computational Linguistics profile →

Peers

Xinting Huang

AI

MSOR

EE

FINAN

EEE

Sidra Mehtab United States

Thiyanga S. Talagala Australia

Pablo Montero‐Manso Australia

Xiaojie Mao United States

Ben Boukai United States

Julien Pérolat United Kingdom

Germán Hernández Colombia

E. Mejuto-Villa Italy

Anuj Mahajan India

Yanyan Zou China

Sidra Mehtab United States

Xinting Huang

40 ×0.7

AI

122 ×2.7

MSOR

38 ×1.5

EE

49 ×2.1

FINAN

43 ×2.5

EEE

Citations per year, relative to Xinting Huang Xinting Huang (= 1×) peers Sidra Mehtab

Countries citing papers authored by Xinting Huang

Since Specialization

Citations

This map shows the geographic impact of Xinting Huang'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 Xinting Huang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xinting Huang more than expected).

Fields of papers citing papers by Xinting Huang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Xinting Huang. 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 Xinting Huang. The network helps show where Xinting Huang may publish in the future.

Co-authorship network of co-authors of Xinting Huang

This figure shows the co-authorship network connecting the top 25 collaborators of Xinting Huang. A scholar is included among the top collaborators of Xinting Huang 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 Xinting Huang. Xinting Huang 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, Yue, Yafu Li, Leyang Cui, et al.. (2025). 🧜Siren’s Song in the AI Ocean: A Survey on Hallucination in Large Language Models. Computational Linguistics. 51(4). 1373–1418. 27 indexed citations breakdown →

2.

Huang, Xinting, et al.. (2024). DoG-Instruct: Towards Premium Instruction-Tuning Data via Text-Grounded Instruction Wrapping. 4125–4135. 2 indexed citations

3.

Huang, Xinting, Tingchen Fu, Qintong Li, et al.. (2024). BBA: Bi-Modal Behavioral Alignment for Reasoning with Large Vision-Language Models. 7255–7279. 1 indexed citations

4.

Chen, Xu, et al.. (2024). See or Guess: Counterfactually Regularized Image Captioning. 965–974. 2 indexed citations

5.

Shi, Shuming, Wei Bi, Deng Cai, et al.. (2023). Effidit: An Assistant for Improving Writing Efficiency. 508–515. 1 indexed citations

6.

Huang, Xinting, et al.. (2023). Explore-Instruct: Enhancing Domain-Specific Instruction Coverage through Active Exploration. 9435–9454. 2 indexed citations

7.

Huang, Xinting, et al.. (2023). Pre-training Multi-party Dialogue Models with Latent Discourse Inference. 9584–9599. 1 indexed citations

8.

Huang, Xinting & Nora Hollenstein. (2023). Long-Range Language Modeling with Selective Cache. 4838–4858. 1 indexed citations

9.

Li, Wei, et al.. (2023). Online detection system for adhesive quality of cigarettes carton based on improved GhostNet-YOLOv4. IET conference proceedings.. 2023(30). 1–4.

10.

Yang, Shiquan, Xinting Huang, Jey Han Lau, & Sarah Erfani. (2022). Robust Task-Oriented Dialogue Generation with Contrastive Pre-training and Adversarial Filtering. 1220–1234.

11.

Chen, Qizhu, et al.. (2022). Prevalence and Factors Associated with BRCA1/2 Gene Mutation in Chinese Populations with Breast Cancer. International Journal of General Medicine. Volume 15. 6783–6789. 1 indexed citations

12.

Huang, Xinting, Jianzhong Qi, Yu Sun, & Rui Zhang. (2021). Latent Reasoning for Low-Resource Question Generation. 3008–3022. 3 indexed citations

13.

Huang, Xinting, Jianzhong Qi, Yu Sun, & Rui Zhang. (2020). MALA: Cross-Domain Dialogue Generation with Action Learning. Proceedings of the AAAI Conference on Artificial Intelligence. 34(5). 7977–7984. 11 indexed citations

14.

Huang, Xinting, Jianzhong Qi, Yu Sun, & Rui Zhang. (2020). Generalizable and Explainable Dialogue Generation via Explicit Action Learning. 3981–3991. 3 indexed citations

15.

Huang, Xinting, et al.. (2020). KaLM at SemEval-2020 Task 4: Knowledge-aware Language Models for Comprehension and Generation. 543–550. 4 indexed citations

16.

Lau, Joseph T. F., Xinting Huang, Chao Pan, et al.. (2019). Why some donors are more willing to donate platelets? ----a qualitative study on 25 regular platelet donors in Guangzhou, China. BMC Public Health. 19(1). 1671–1671. 9 indexed citations

17.

Wang, Qili, et al.. (2019). Enhancing intraday stock price manipulation detection by leveraging recurrent neural networks with ensemble learning. Neurocomputing. 347. 46–58. 59 indexed citations

18.

Huang, Xinting, Jianzhong Qi, Yu Sun, Rui Zhang, & Hai-Tao Zheng. (2019). CARL: Aggregated Search with Context-Aware Module Embedding Learning. 1–8. 5 indexed citations

19.

Yan, Xiaoqing, Jinfang Zhang, & Xinting Huang. (2018). Peak capacity analysis of coal power in China based on full-life cycle cost model optimization. IOP Conference Series Earth and Environmental Science. 121. 52065–52065. 1 indexed citations

20.

Gong, Jingjing, Xinting Huang, Jun Huang, et al.. (2014). A fiber optic sensor for 2-cholrophenol analysis based on oxygen sensing system. Journal of Wuhan University of Technology-Mater Sci Ed. 29(6). 1178–1182. 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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