Christopher Akiki

736 total citations · 1 hit paper
10 papers, 201 citations indexed

About

Christopher Akiki is a scholar working on Artificial Intelligence, Information Systems and Signal Processing. According to data from OpenAlex, Christopher Akiki has authored 10 papers receiving a total of 201 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Artificial Intelligence, 4 papers in Information Systems and 2 papers in Signal Processing. Recurrent topics in Christopher Akiki's work include Topic Modeling (4 papers), Natural Language Processing Techniques (4 papers) and Semantic Web and Ontologies (3 papers). Christopher Akiki is often cited by papers focused on Topic Modeling (4 papers), Natural Language Processing Techniques (4 papers) and Semantic Web and Ontologies (3 papers). Christopher Akiki collaborates with scholars based in Germany, Italy and Canada. Christopher Akiki's co-authors include Angela Fan, Teven Le Scao, Daniel Hesslow, Suzana Ilić, Ellie Pavlick, Manuel Burghardt, Sebastian Simon, Martin Potthast, Benno Stein and Norbert Siegmund and has published in prestigious journals such as SHILAP Revista de lepidopterología, ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam) and arXiv (Cornell University).

In The Last Decade

Christopher Akiki

7 papers receiving 190 citations

Hit Papers

BLOOM: A 176B-Parameter Open-Access Multilingual Language... 2022 2026 2023 2024 2022 50 100 150

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Christopher Akiki Germany 4 133 25 21 14 12 10 201
Daniel Hesslow France 2 139 1.0× 23 0.9× 24 1.1× 13 0.9× 12 1.0× 4 194
Wenxiong Liao China 8 197 1.5× 29 1.2× 27 1.3× 28 2.0× 5 0.4× 16 271
Jan Trienes Germany 4 190 1.4× 44 1.8× 21 1.0× 6 0.4× 14 1.2× 6 250
Xiangru Tang United States 7 234 1.8× 16 0.6× 31 1.5× 18 1.3× 32 2.7× 22 317
Lennart Heim Canada 5 79 0.6× 10 0.4× 18 0.9× 10 0.7× 4 0.3× 8 199
Niklas Muennighoff United States 6 302 2.3× 15 0.6× 55 2.6× 37 2.6× 9 0.8× 8 379
Md Tahmid Rahman Laskar Canada 11 258 1.9× 41 1.6× 15 0.7× 41 2.9× 25 2.1× 24 352
Aman Chadha United States 8 83 0.6× 10 0.4× 49 2.3× 15 1.1× 3 0.3× 33 184
Samuel Weinbach United States 2 176 1.3× 15 0.6× 31 1.5× 42 3.0× 8 0.7× 2 236
Ori Ram Israel 6 235 1.8× 10 0.4× 73 3.5× 31 2.2× 9 0.8× 7 319

Countries citing papers authored by Christopher Akiki

Since Specialization
Citations

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

Fields of papers citing papers by Christopher Akiki

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Christopher Akiki

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

All Works

10 of 10 papers shown
1.
Fröbe, Maik, Harrisen Scells, Christopher Akiki, et al.. (2024). Resources for Combining Teaching and Research in Information Retrieval Coursework. ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam). 1115–1125.
2.
Piktus, Aleksandra, et al.. (2023). GAIA Search: Hugging Face and Pyserini Interoperability for NLP Training Data Exploration. IRIS Research product catalog (Sapienza University of Rome). 588–598.
3.
Loebe, Frank, Yamen Ajjour, Christopher Akiki, et al.. (2023). Shared Tasks as Tutorials: A Methodical Approach. Proceedings of the AAAI Conference on Artificial Intelligence. 37(13). 15807–15815. 1 indexed citations
4.
Piktus, Aleksandra, et al.. (2023). The ROOTS Search Tool: Data Transparency for LLMs. IRIS Research product catalog (Sapienza University of Rome). 304–314. 10 indexed citations
5.
Akiki, Christopher, et al.. (2023). Spacerini: Plug-and-play Search Engines with Pyserini and Hugging Face. IRIS Research product catalog (Sapienza University of Rome). 140–148. 1 indexed citations
6.
Simon, Sebastian, et al.. (2023). Exploring Hyperparameter Usage and Tuning in Machine Learning Research. 68–79. 9 indexed citations
7.
Scao, Teven Le, Angela Fan, Christopher Akiki, et al.. (2022). BLOOM: A 176B-Parameter Open-Access Multilingual Language Model. arXiv (Cornell University). 174 indexed citations breakdown →
8.
Akiki, Christopher & Manuel Burghardt. (2021). MuSe: The Musical Sentiment Dataset. SHILAP Revista de lepidopterología. 7. 5 indexed citations
9.
Akiki, Christopher & Martin Potthast. (2020). Exploring Argument Retrieval with Transformers.. CLEF (Working Notes).
10.
Akiki, Christopher & Manuel Burghardt. (2020). Toward a Musical Sentiment (MuSe) Dataset for Affective Distant Hearing.. Qucosa (Saxon State and University Library Dresden). 225–235. 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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