Smaranda Muresan

3.0k total citations · 1 hit paper
86 papers, 1.5k citations indexed

About

Smaranda Muresan is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition. According to data from OpenAlex, Smaranda Muresan has authored 86 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 76 papers in Artificial Intelligence, 13 papers in Information Systems and 13 papers in Computer Vision and Pattern Recognition. Recurrent topics in Smaranda Muresan's work include Topic Modeling (55 papers), Natural Language Processing Techniques (41 papers) and Sentiment Analysis and Opinion Mining (19 papers). Smaranda Muresan is often cited by papers focused on Topic Modeling (55 papers), Natural Language Processing Techniques (41 papers) and Sentiment Analysis and Opinion Mining (19 papers). Smaranda Muresan collaborates with scholars based in United States, Netherlands and China. Smaranda Muresan's co-authors include Nina Wacholder, Roberto González‐Ibáñez, Debanjan Ghosh, Judith L. Klavans, Tuhin Chakrabarty, Elena Musi, Weiwei Guo, Christopher Hidey, Kathy McKeown and Savvas Petridis and has published in prestigious journals such as Computational Linguistics, Language Resources and Evaluation and Journal of the Association for Information Science and Technology.

In The Last Decade

Smaranda Muresan

76 papers receiving 1.4k 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.

Art or Artifice? Large Language Models and the False Promise of Creativity

2024 45 citations Tuhin Chakrabarty, Smaranda Muresan et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Smaranda Muresan United States	21	1.3k	274	174	142	108	86	1.5k
Yulia Tsvetkov United States	21	1.4k 1.1×	159 0.6×	145 0.8×	174 1.2×	154 1.4×	96	1.7k
Michael Heilman United States	22	1.8k 1.4×	387 1.4×	99 0.6×	105 0.7×	217 2.0×	40	2.3k
Alice Oh South Korea	20	1.2k 1.0×	323 1.2×	286 1.6×	121 0.9×	97 0.9×	98	1.8k
Barbara Plank Denmark	26	1.9k 1.4×	235 0.9×	149 0.9×	74 0.5×	352 3.3×	145	2.2k
Thamar Solorio United States	24	1.5k 1.2×	468 1.7×	169 1.0×	49 0.3×	123 1.1×	116	1.9k
Tomek Strzalkowski United States	20	1.4k 1.1×	347 1.3×	79 0.5×	94 0.7×	62 0.6×	117	1.6k
Muhammad Abdul-Mageed Canada	19	1.5k 1.2×	249 0.9×	137 0.8×	79 0.6×	43 0.4×	88	1.7k
Horacio Saggion Spain	29	2.6k 2.1×	359 1.3×	106 0.6×	91 0.6×	164 1.5×	172	3.0k
Kenji Araki Japan	18	772 0.6×	186 0.7×	96 0.6×	152 1.1×	82 0.8×	175	1.1k
Patrick Juola United States	18	1.2k 1.0×	312 1.1×	205 1.2×	52 0.4×	62 0.6×	59	1.5k

Countries citing papers authored by Smaranda Muresan

Since Specialization

Citations

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

Fields of papers citing papers by Smaranda Muresan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Smaranda Muresan

This figure shows the co-authorship network connecting the top 25 collaborators of Smaranda Muresan. A scholar is included among the top collaborators of Smaranda Muresan 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 Smaranda Muresan. Smaranda Muresan 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.

Muresan, Smaranda, et al.. (2024). ICLEF: In-Context Learning with Expert Feedback for Explainable Style Transfer. 16141–16163. 2 indexed citations

2.

Chakrabarty, Tuhin, et al.. (2024). Connecting the Dots: Evaluating Abstract Reasoning Capabilities of LLMs Using the New York Times Connections Word Game. 21219–21236. 2 indexed citations

3.

Muresan, Smaranda, et al.. (2024). Large Language Models are Few-Shot Training Example Generators: A Case Study in Fallacy Recognition. 12323–12334.

4.

Chakrabarty, Tuhin, et al.. (2023). I Spy a Metaphor: Large Language Models and Diffusion Models Co-Create Visual Metaphors. 7370–7388. 16 indexed citations

5.

Chakrabarty, Tuhin, et al.. (2022). Multitask Instruction-based Prompting for Fallacy Recognition. 8172–8187. 7 indexed citations

6.

Chakrabarty, Tuhin, et al.. (2022). A Report on the FigLang 2022 Shared Task on Understanding Figurative Language. 178–183. 1 indexed citations

7.

Chakrabarty, Tuhin, Smaranda Muresan, & Nanyun Peng. (2020). Generating similes effortlessly like a Pro: A Style Transfer Approach for Simile Generation. 6455–6469. 27 indexed citations

8.

Eskander, Ramy, Smaranda Muresan, & Michael Collins. (2020). Unsupervised Cross-Lingual Part-of-Speech Tagging for Truly Low-Resource Scenarios. 4820–4831. 12 indexed citations

9.

Anand, Vishal, et al.. (2020). MultiSeg: Parallel Data and Subword Information for Learning Bilingual Embeddings in Low Resource Scenarios. 97–105. 2 indexed citations

10.

Eskander, Ramy, et al.. (2020). MorphAGram, Evaluation and Framework for Unsupervised Morphological Segmentation. Language Resources and Evaluation. 7112–7122. 13 indexed citations

11.

Gao, Yanjun, et al.. (2019). Rubric Reliability and Annotation of Content and Argument in Source-Based Argument Essays. 507–518. 5 indexed citations

12.

Petridis, Savvas, et al.. (2018). Where is Your Evidence: Improving Fact-checking by Justification Modeling. 85–90. 67 indexed citations

13.

Passonneau, Rebecca J., Danielle S. McNamara, Smaranda Muresan, & Dolores Perin. (2017). Preface: Special Issue on Multidisciplinary Approaches to AI and Education for Reading and Writing. International Journal of Artificial Intelligence in Education. 27(4). 665–670. 13 indexed citations

14.

Aakhus, Mark, Smaranda Muresan, & Nina Wacholder. (2016). An Argument-Ontology for a Response-Centered Approach to Argumentation Mining.. International Joint Conference on Artificial Intelligence. 40–42. 2 indexed citations

15.

Muresan, Smaranda, et al.. (2012). Computational Analysis of Referring Expressions in Narratives of Picture Books. North American Chapter of the Association for Computational Linguistics. 1–7. 2 indexed citations

16.

Ghosh, Debanjan & Smaranda Muresan. (2012). Relation Classification using Entity Sequence Kernels. International Conference on Computational Linguistics. 391–400. 2 indexed citations

17.

Muresan, Smaranda. (2011). Learning for deep language understanding. International Joint Conference on Artificial Intelligence. 1858–1865. 9 indexed citations

18.

Muresan, Smaranda. (2010). A Learnable Constraint-based Grammar Formalism. International Conference on Computational Linguistics. 885–893. 3 indexed citations

19.

Muresan, Smaranda, et al.. (2003). Building a terminological database from heterogeneous definitional sources. International Conference on Digital Government Research. 1–4. 2 indexed citations

20.

Tzoukermann, Evelyne, Smaranda Muresan, & Judith L. Klavans. (2001). GIST-IT: Combining Linguistic and Machine Learning Techniques for Email Summarization. Meeting of the Association for Computational Linguistics.

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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