Bryan Wilie

1.5k total citations · 1 hit paper
14 papers, 509 citations indexed

About

Bryan Wilie is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Social Psychology. According to data from OpenAlex, Bryan Wilie has authored 14 papers receiving a total of 509 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Artificial Intelligence, 3 papers in Computer Vision and Pattern Recognition and 1 paper in Social Psychology. Recurrent topics in Bryan Wilie's work include Topic Modeling (10 papers), Natural Language Processing Techniques (8 papers) and Speech and dialogue systems (4 papers). Bryan Wilie is often cited by papers focused on Topic Modeling (10 papers), Natural Language Processing Techniques (8 papers) and Speech and dialogue systems (4 papers). Bryan Wilie collaborates with scholars based in Hong Kong, Indonesia and Australia. Bryan Wilie's co-authors include Samuel Cahyawijaya, Pascale Fung, Ziwei Ji, Nayeon Lee, Tiezheng Yu, Willy Chung, Yan Xu, Holy Lovenia, Wenliang Dai and Dan Su and has published in prestigious journals such as Rare & Special e-Zone (The Hong Kong University of Science and Technology) and Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing.

In The Last Decade

Bryan Wilie

13 papers receiving 489 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.

A Multitask, Multilingual, Multimodal Evaluation of ChatGPT on Reasoning, Hallucination, and Interactivity

2023 388 citations Yejin Bang, Samuel Cahyawijaya et al. Rare & Special e-Zone (The Hong Kong University of Science and Technology) profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Bryan Wilie Hong Kong	6	361	82	79	37	33	14	509
Holy Lovenia Hong Kong	6	286 0.8×	60 0.7×	79 1.0×	34 0.9×	31 0.9×	13	431
Nayeon Lee South Korea	4	280 0.8×	61 0.7×	79 1.0×	27 0.7×	32 1.0×	6	417
Yejin Bang Hong Kong	5	291 0.8×	59 0.7×	80 1.0×	31 0.8×	39 1.2×	11	468
Willy Chung Hong Kong	2	262 0.7×	58 0.7×	79 1.0×	26 0.7×	30 0.9×	5	396
Samuel Cahyawijaya Hong Kong	11	620 1.7×	124 1.5×	79 1.0×	78 2.1×	47 1.4×	36	826
Piotr Miłkowski Poland	10	399 1.1×	44 0.5×	123 1.6×	28 0.8×	51 1.5×	17	581
Wenliang Dai Hong Kong	9	445 1.2×	80 1.0×	84 1.1×	129 3.5×	36 1.1×	18	691
Arkadiusz Janz Poland	7	297 0.8×	36 0.4×	119 1.5×	23 0.6×	36 1.1×	19	465
Kamil Kanclerz Poland	8	359 1.0×	41 0.5×	123 1.6×	27 0.7×	46 1.4×	11	529
Marcin Gruza Poland	8	405 1.1×	48 0.6×	125 1.6×	30 0.8×	62 1.9×	13	581

Countries citing papers authored by Bryan Wilie

Since Specialization

Citations

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

Fields of papers citing papers by Bryan Wilie

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Bryan Wilie

This figure shows the co-authorship network connecting the top 25 collaborators of Bryan Wilie. A scholar is included among the top collaborators of Bryan Wilie 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 Bryan Wilie. Bryan Wilie 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:

14 of 14 papers shown

Cahyawijaya, Samuel, Holy Lovenia, Fajri Koto, et al.. (2024). Cendol: Open Instruction-tuned Generative Large Language Models for Indonesian Languages. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 14899–14914. 3 indexed citations

Ji, Ziwei, Delong Chen, Etsuko Ishii, et al.. (2024). LLM Internal States Reveal Hallucination Risk Faced With a Query. 88–104. 4 indexed citations

Chung, Willy, Samuel Cahyawijaya, Bryan Wilie, Holy Lovenia, & Pascale Fung. (2023). InstructTODS: Large Language Models for End-to-End Task-Oriented Dialogue Systems. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 5 indexed citations

Ishii, Etsuko, Bryan Wilie, Ziwei Ji, et al.. (2023). Contrastive Learning for Inference in Dialogue. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 10202–10221. 1 indexed citations

Cahyawijaya, Samuel, Holy Lovenia, Fajri Koto, et al.. (2023). NusaWrites: Constructing High-Quality Corpora for Underrepresented and Extremely Low-Resource Languages. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 921–945. 5 indexed citations

Ji, Ziwei, Zihan Liu, Nayeon Lee, et al.. (2023). RHO: Reducing Hallucination in Open-domain Dialogues with Knowledge Grounding. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 4504–4522. 16 indexed citations

Bang, Yejin, Samuel Cahyawijaya, Nayeon Lee, et al.. (2023). A Multitask, Multilingual, Multimodal Evaluation of ChatGPT on Reasoning, Hallucination, and Interactivity. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 675–718. 388 indexed citations breakdown →

Cahyawijaya, Samuel, et al.. (2022). How Long Is Enough? Exploring the Optimal Intervals of Long-Range Clinical Note Language Modeling. 160–172.

Ishii, Etsuko, Bryan Wilie, Yan Xu, Samuel Cahyawijaya, & Pascale Fung. (2022). Integrating Question Rewrites in Conversational Question Answering: A Reinforcement Learning Approach. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 55–66. 2 indexed citations

10.

Ishii, Etsuko, Yan Xu, Samuel Cahyawijaya, & Bryan Wilie. (2022). Can Question Rewriting Help Conversational Question Answering?. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 94–99. 4 indexed citations

11.

Cahyawijaya, Samuel, Genta Indra Winata, Bryan Wilie, et al.. (2021). IndoNLG: Benchmark and Resources for Evaluating Indonesian Natural Language Generation. Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing. 8875–8898. 50 indexed citations

12.

Wilie, Bryan, Karissa Vincentio, Genta Indra Winata, et al.. (2020). IndoNLU: Benchmark and Resources for Evaluating Indonesian Natural Language Understanding. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 843–857. 28 indexed citations

13.

Wilie, Bryan, Samuel Cahyawijaya, & Widyawardana Adiprawita. (2018). CountNet: End to End Deep Learning for Crowd Counting. 128–132. 2 indexed citations

14.

Cahyawijaya, Samuel, Bryan Wilie, & Widyawardana Adiprawita. (2018). IDEnet : Inception-Based Deep Convolutional Neural Network for Crowd Counting Estimation. 548–553. 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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