Wai Lam

7.5k total citations · 3 hit papers
185 papers, 4.2k citations indexed

About

Wai Lam is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition. According to data from OpenAlex, Wai Lam has authored 185 papers receiving a total of 4.2k indexed citations (citations by other indexed papers that have themselves been cited), including 164 papers in Artificial Intelligence, 73 papers in Information Systems and 20 papers in Computer Vision and Pattern Recognition. Recurrent topics in Wai Lam's work include Topic Modeling (101 papers), Natural Language Processing Techniques (66 papers) and Web Data Mining and Analysis (37 papers). Wai Lam is often cited by papers focused on Topic Modeling (101 papers), Natural Language Processing Techniques (66 papers) and Web Data Mining and Analysis (37 papers). Wai Lam collaborates with scholars based in Hong Kong, China and United States. Wai Lam's co-authors include Lidong Bing, Xin Li, Yang Deng, Wenxuan Zhang, Tak-Lam Wong, Bei Shi, Piji Li, Xin Li, Zihao Wang and Wenxuan Zhang and has published in prestigious journals such as The Lancet, IEEE Transactions on Pattern Analysis and Machine Intelligence and Cancer.

In The Last Decade

Wai Lam

178 papers receiving 3.9k citations

Hit Papers

Transformation Networks for Target-Oriented Sentiment Cla... 2018 2026 2020 2023 2018 2022 2019 100 200 300
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.

  1. Transformation Networks for Target-Oriented Sentiment Classification
    2018 341 citations Lidong Bing, Wai Lam et al. profile →
  2. A Survey on Aspect-Based Sentiment Analysis: Tasks, Methods, and Challenges
    2022 237 citations Wenxuan Zhang, Xin Li et al. IEEE Transactions on Knowledge and Data Engineering profile →
  3. Exploiting BERT for End-to-End Aspect-based Sentiment Analysis
    2019 218 citations Xin Li, Lidong Bing et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Wai Lam Hong Kong 32 3.3k 1.2k 410 318 167 185 4.2k
Xiangyu Zhao China 30 1.1k 0.3× 1.2k 1.0× 463 1.1× 364 1.1× 273 1.6× 196 2.6k
Martha Larson Netherlands 29 1.1k 0.3× 1.5k 1.2× 963 2.3× 338 1.1× 104 0.6× 150 3.0k
Vincent Ng Hong Kong 37 3.4k 1.0× 1.5k 1.3× 349 0.9× 248 0.8× 524 3.1× 190 5.5k
Zheng Chen China 21 1.1k 0.3× 969 0.8× 429 1.0× 98 0.3× 85 0.5× 74 2.3k
Xiaoyan Zhu China 38 5.1k 1.5× 1.3k 1.1× 669 1.6× 342 1.1× 30 0.2× 171 6.4k
Chandan K. Reddy United States 31 1.7k 0.5× 529 0.4× 396 1.0× 164 0.5× 59 0.4× 155 3.6k
Harald Steck United States 20 871 0.3× 1.3k 1.1× 347 0.8× 440 1.4× 36 0.2× 39 2.1k
Arif Mehmood Pakistan 28 1.5k 0.4× 617 0.5× 293 0.7× 93 0.3× 46 0.3× 87 2.9k
Xiangnan Kong United States 31 1.8k 0.5× 640 0.5× 492 1.2× 106 0.3× 210 1.3× 132 3.3k

Countries citing papers authored by Wai Lam

Since Specialization
Citations

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

Fields of papers citing papers by Wai Lam

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Wai Lam

This figure shows the co-authorship network connecting the top 25 collaborators of Wai Lam. A scholar is included among the top collaborators of Wai Lam 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 Wai Lam. Wai Lam is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Lu, Hongyuan, Yang Liu, Xiang Zhang, et al.. (2025). Stephanie: Step-by-Step Dialogues for Mimicking Human Interactions in Social Conversations. 153–166. 1 indexed citations
2.
3.
Deng, Yang, Moxin Li, Liang Pang, Wenxuan Zhang, & Wai Lam. (2025). Unveiling Knowledge Boundary of Large Language Models for Trustworthy Information Access. 4086–4089.
4.
Deng, Yang, Lizi Liao, Wenqiang Lei, et al.. (2025). Proactive Conversational AI: A Comprehensive Survey of Advancements and Opportunities. ACM Transactions on Information Systems. 43(3). 1–45. 5 indexed citations
5.
Siro, Clemencia, et al.. (2024). Asking Multimodal Clarifying Questions in Mixed-Initiative Conversational Search. Research at the University of Copenhagen (University of Copenhagen). 1474–1485. 2 indexed citations
6.
Zhao, Xiaoyan, Yang Deng, Min Yang, et al.. (2024). A Comprehensive Survey on Relation Extraction: Recent Advances and New Frontiers. ACM Computing Surveys. 56(11). 1–39. 42 indexed citations
7.
8.
Lam, Wai, et al.. (2023). Joint learning of text alignment and abstractive summarization for long documents via unbalanced optimal transport. Natural Language Engineering. 30(3). 525–553.
9.
Deng, Yang, et al.. (2023). Learning to Ask Clarification Questions with Spatial Reasoning. 2113–2117. 4 indexed citations
10.
Deng, Yang, et al.. (2023). Nonfactoid Question Answering as Query-Focused Summarization With Graph-Enhanced Multihop Inference. IEEE Transactions on Neural Networks and Learning Systems. 35(8). 11231–11245. 26 indexed citations
11.
Zhang, Wenxuan, et al.. (2023). Multimodal Fashion Knowledge Extraction as Captioning. 52–62. 2 indexed citations
12.
Deng, Yang, Wenqiang Lei, Wenxuan Zhang, Wai Lam, & Tat‐Seng Chua. (2022). PACIFIC: Towards Proactive Conversational Question Answering over Tabular and Textual Data in Finance. 6970–6984. 14 indexed citations
13.
Yuan, Yifei, Shi Chen, Runze Wang, et al.. (2022). McQueen: a Benchmark for Multimodal Conversational Query Rewrite. 4834–4844. 5 indexed citations
14.
Xu, Weiwen, et al.. (2022). ConReader: Exploring Implicit Relations in Contracts for Contract Clause Extraction. 2581–2594. 2 indexed citations
15.
Deng, Yang, Yaliang Li, Bolin Ding, & Wai Lam. (2022). Leveraging Long Short-Term User Preference in Conversational Recommendation via Multi-agent Reinforcement Learning. IEEE Transactions on Knowledge and Data Engineering. 35(11). 11541–11555. 12 indexed citations
16.
Deng, Yang, et al.. (2022). A Unified Multi-task Learning Framework for Multi-goal Conversational Recommender Systems. ACM Transactions on Information Systems. 41(3). 1–25. 40 indexed citations
17.
Zhang, Wenxuan, Xin Li, Yang Deng, Lidong Bing, & Wai Lam. (2021). Towards Generative Aspect-Based Sentiment Analysis. 504–510. 129 indexed citations
18.
Li, Piji, Wai Lam, Lidong Bing, & Zihao Wang. (2017). Deep Recurrent Generative Decoder for Abstractive Text Summarization. 2091–2100. 113 indexed citations
19.
Yu, Qian, et al.. (2016). Exploiting interactions of review text, hidden user communities and item groups, and time for collaborative filtering. Knowledge and Information Systems. 52(1). 221–254. 6 indexed citations
20.
Yu, Xiaofeng & Wai Lam. (2010). Accelerated Training of Maximum Margin Markov Models for Sequence Labeling: A Case Study of NP Chunking. International Conference on Computational Linguistics. 1408–1416. 1 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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