Abhik Jana

401 citations
16 papers · 164 indexed · 1 hit paper · h-index 5

Abhik Jana

14 papers receiving 153 citations

Hit Papers

LexGLUE: A Benchmark Dataset for Legal Language Understan...622022202620232024204060

Peers

Abhik Jana
Comparison fields: 5 of 37
  • Law 39
  • Political Science and International Relations 91
  • Artificial Intelligence 112
  • Health Informatics 2
  • General Social Sciences 3
Replace Dirk Hartung with:
Dirk Hartung United States
Matthias Grabmair Germany
Zikun Hu China
Paheli Bhattacharya India
Terence Anderson United States
Llio Humphreys Italy
Vu Tran Japan
Mihaela Vela Germany
Daniela Tiscornia Italy
Zhipeng Guo China
Abhik Jana relative to Dirk Hartung United States Dirk Hartung's profile →
Citations per field
00.5×1.5×
Dirk Hartung · 1×
Citations per year

Countries citing papers authored by Abhik Jana

Since Specialization
Citations

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

Fields of papers citing papers by Abhik Jana

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 17 scholars most cited alongside Abhik Jana, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Abhik Jana Line = papers co-authored together Abhik Jana links everyone, so they are left out of the graph.

All Works

16 of 16 papers shown
#Work
1 20251
2 20240
3 202333
4
LexGLUE: A Benchmark Dataset for Legal Language Understanding in Englishbreakdown →
202262
5 20221
6 20212
7 20216
8
Error Analysis of using BART for Multi-Document Summarization: A Study for English and German Language.
20213
9 202142
10
Using Distributional Thesaurus Embedding for Co-hyponymy Detection
20200
11 20193
12 20192
13
Network Features Based Co-hyponymy Detection
20181
14 20171
15 20143
16
A New Semantic Lexicon and Similarity Measure in Bangla
20124

About Abhik Jana

Abhik Jana is a scholar working on Artificial Intelligence, Cultural Studies and Law, having authored 16 papers that have together received 164 indexed citations. Recurring topics across this work include Topic Modeling (11 papers), Natural Language Processing Techniques (11 papers), Advanced Text Analysis Techniques (5 papers), Artificial Intelligence in Law (3 papers), Language and cultural evolution (2 papers), Legal Language and Interpretation (2 papers), Comparative and International Law Studies (2 papers) and Cryptography and Data Security (1 paper). The work is most often cited by research in Law (39 citations), Political Science and International Relations (91 citations) and Artificial Intelligence (112 citations). Abhik Jana has collaborated with scholars based in India, Germany and United States. Frequent co-authors include Dirk Hartung, Daniel Katz, Michael James Bommarito, Ilias Chalkidis, Ion Androutsopoulos, Νικόλαος Αλέτρας, Chris Biemann, Pawan Goyal, Anupam Basu and Tirthankar Dasgupta. Their work appears in journals such as Expert Systems with Applications, Information Processing & Management and Language Resources and Evaluation.

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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