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GLUECoS: An Evaluation Benchmark for Code-Switched NLP paper by Independent / Community
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Paper

GLUECoS: An Evaluation Benchmark for Code-Switched NLP

by Independent / Community 00cd2650a89734105fa0c0aba3bf07935b318290
Free2AITools Nexus Index
71.0
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 88
P: Popularity 66
R: Recency 100
Q: Quality 65
Tech Context
Vital Performance —

Code-switching is the use of more than one language in the same conversation or utterance. Recently, multilingual contextual embedding models, trained on multiple monolingual corpora, have shown promising results on cross-lingual and multilingual tasks. We present an evaluation benchmark, GLUECoS, for code-switched languages, that spans several NLP tasks in English-Hindi and English-Spanish. Specifically, our evaluation benchmark includes Language Identification from text, POS tagging, Named ...

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Semantic Scholar 190 Citations
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Registry ID 00cd2650a89734105fa0c0aba3bf07935b318290
License ArXiv
Provider semantic_scholar
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BibTeX 
@misc{00cd2650a89734105fa0c0aba3bf07935b318290,
  author = {Unknown},
  title = {GLUECoS: An Evaluation Benchmark for Code-Switched NLP Paper},
  year = {2026},
  howpublished = {\url{https://api.semanticscholar.org/00cd2650a89734105fa0c0aba3bf07935b318290}},
  note = {Accessed via Free2AITools.}
}
APA Style
Unknown. (2026). GLUECoS: An Evaluation Benchmark for Code-Switched NLP [Paper]. Free2AITools. https://api.semanticscholar.org/00cd2650a89734105fa0c0aba3bf07935b318290

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βš–οΈ Free2AITools Nexus Index V2.0

Methodology How FNI works
Semantic (S) 50

Query-time baseline · scored live at search

Authority (A) 88
Popularity (P) 66
Recency (R) 100
Quality (Q) 65

πŸ’¬ Index Insight

FNI V2.0 for GLUECoS: An Evaluation Benchmark for Code-Switched NLP: Authority (A:88), Popularity (P:66), Recency (R:100), Quality (Q:65). Semantic (S) is a query-time baseline scored live at search.

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HuggingFace API GitHub Metadata Arxiv Citation DB Methodology
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πŸ“ Executive Summary

"Code-switching is the use of more than one language in the same conversation or utterance. Recently, multilingual contextual embedding models, trained on multiple monolingual corpora, have shown promising results on cross-lingual and multilingual tasks. We present an evaluation benchmark, GLUECoS, for code-switched languages, that spans several NLP tasks in English-Hindi and English-Spanish. Specifically, our evaluation benchmark includes Language Identification from text, POS tagging, Named ..."

❝ Cite Node 

@article{Unknown2026GLUECoS:,
  title={GLUECoS: An Evaluation Benchmark for Code-Switched NLP},
  author={},
  note={Indexed by Free2AITools},
  year={2026}
}

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πŸ“Š Research Signals

πŸ“ˆ190CitationsSemantic Scholar
πŸ›οΈ88AuthorityFNI pillar
⏱️100RecencyFNI pillar
βœ…65QualityFNI pillar
πŸ—‚οΈtext generationField

🏷️ Research Topics

embeddings
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