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.
Automating Research Synthesis with Domain-Specific Large Language Model Fine-Tuning
202516 citationsTeo Sušnjak, P. Hwang et al.ACM Transactions on Knowledge Discovery from Dataprofile →
Citations per year, relative to Surangika Ranathunga Surangika Ranathunga (= 1×)
peers
Raghavendra Udupa
Countries citing papers authored by Surangika Ranathunga
Since
Specialization
Citations
This map shows the geographic impact of Surangika Ranathunga'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 Surangika Ranathunga with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Surangika Ranathunga more than expected).
Fields of papers citing papers by Surangika Ranathunga
This network shows the impact of papers produced by Surangika Ranathunga. 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 Surangika Ranathunga. The network helps show where Surangika Ranathunga may publish in the future.
Co-authorship network of co-authors of Surangika Ranathunga
This figure shows the co-authorship network connecting the top 25 collaborators of Surangika Ranathunga.
A scholar is included among the top collaborators of Surangika Ranathunga 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 Surangika Ranathunga. Surangika Ranathunga 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.
Sušnjak, Teo, P. Hwang, Napoleon H. Reyes, et al.. (2025). Automating Research Synthesis with Domain-Specific Large Language Model Fine-Tuning. ACM Transactions on Knowledge Discovery from Data. 19(3). 1–39.16 indexed citations breakdown →
Ranathunga, Surangika, et al.. (2020). Multi-lingual Mathematical Word Problem Generation using Long Short Term Memory Networks with Enhanced Input Features.. Language Resources and Evaluation. 4709–4716.4 indexed citations
9.
Ranathunga, Surangika, et al.. (2020). Word Embedding Evaluation for Sinhala. Language Resources and Evaluation. 1874–1881.4 indexed citations
10.
Ranathunga, Surangika, et al.. (2018). Annotating Opinions and Opinion Targets in Student Course Feedback. Language Resources and Evaluation.1 indexed citations
11.
Ranathunga, Surangika, et al.. (2018). Handling Rare Word Problem using Synthetic Training Data for Sinhala and Tamil Neural Machine Translation.. Language Resources and Evaluation.3 indexed citations
12.
Ranathunga, Surangika, et al.. (2018). Improving domain-specific SMT for low-resourced languages using data from different domains.. Language Resources and Evaluation.6 indexed citations
13.
Ranathunga, Surangika, et al.. (2017). Opinion Target Extraction for Student Course Feedback. International Conference on Computational Linguistics. 295–307.1 indexed citations
14.
Ranathunga, Surangika, et al.. (2017). Sinhala Word Joiner. 220–226.1 indexed citations
15.
Ranathunga, Surangika, et al.. (2016). Sinhala Short Sentence Similarity Calculation using Corpus-Based and Knowledge-Based Similarity Measures. International Conference on Computational Linguistics. 44–53.1 indexed citations
16.
Ranathunga, Surangika, et al.. (2016). Comprehensive Part-Of-Speech Tag Set and SVM based POS Tagger for Sinhala. International Conference on Computational Linguistics. 173–182.14 indexed citations
17.
Ranathunga, Surangika, et al.. (2016). Automatic Creation of a Sentence Aligned Sinhala-Tamil Parallel Corpus. International Conference on Computational Linguistics. 124–132.9 indexed citations
18.
Ranathunga, Surangika, et al.. (2015). Ruchi: Rating Individual Food Items in Restaurant Reviews.. 209–214.8 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.