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Punjabi datasets
archive 2025-07-28
19 datasets carry the language tag "Punjabi", ordered by the archive's paper count. Page 1 of 1: 19 shown of 19. Facet routes are this site's own (the archive records the tag string, not a page).
The archive holds 12,214 dataset rows; 12,172 are listed. 6 are withheld from every listing and count here as vandalised before snapshot (6 with contact-centre spam in the title, 0 with a spam description on a row that has no homepage, no paper and no papers counted; none with more than 1 paper, 0 with a benchmark), listed in withheld.json; 1 listed row carries a vandalised description, withheld on its page. This gate never withholds a row with a homepage or a paper that resolves, and a clean description; the content rules below withhold a row whose name is spam whatever else it carries. The gate is a phrase list: these are the rows it caught, not a claim that the rest is clean. Before that gate, the site's content rules withhold 36 more rows (invite-code, gambling, travel-booking, contact-centre and similar spam in the name or on a row with nothing real behind it); they have no page and are listed in withheld.json.
Filter 50 language tags shown of 367, by dataset count; the full filter by modality, task and language is on /datasets
Punjabi datasets 1–19 of 19
Common Voice is an audio dataset that consists of a unique MP3 and corresponding text file.
449 papers · 143 benchmarks
This corpus comprises of monolingual data for 100+ languages and also includes data for romanized languages.
115 papers · 0 benchmarks
OSCAR or Open Super-large Crawled ALMAnaCH coRpus is a huge multilingual corpus obtained by language classification and filtering of the Common Crawl corpus using the goclassy architecture.
64 papers · 0 benchmarks
XL-Sum is a comprehensive and diverse dataset for abstractive summarization comprising 1 million professionally annotated article-summary pairs from BBC, extracted using a set of carefully designed heuristics.
64 papers · 0 benchmarks
IndicCorp is a large monolingual corpora with around 9 billion tokens covering 12 of the major Indian languages.
28 papers · 0 benchmarks
IndicGLUE (Indic General Language Understanding Evaluation Benchmark)
We now introduce IndicGLUE, the Indic General Language Understanding Evaluation Benchmark, which is a collection of various NLP tasks as de- scribed below.
16 papers · 4 benchmarks
X-FACT is a large publicly available multilingual dataset for factual verification of naturally existing real-world claims.
16 papers · 0 benchmarks
The Dakshina dataset is a collection of text in both Latin and native scripts for 12 South Asian languages.
14 papers · 0 benchmarks
Naamapadam is a Named Entity Recognition (NER) dataset for the 11 major Indian languages from two language families.
6 papers · 0 benchmarks
The IndicNLP corpus is a large-scale, general-domain corpus containing 2.7 billion words for 10 Indian languages from two language families.
3 papers · 0 benchmarks
A multilingual dataset for the task of multilingual claim span identification.
3 papers · 0 benchmarks
It consists of an extensive collection of a high quality cross-lingual fact-to-text dataset in 11 languages: Assamese (as), Bengali (bn), Gujarati (gu), Hindi (hi), Kannada (kn), Malayalam (ml), Marathi (mr), Oriya (or), Punjabi (pa),…
2 papers · 1 benchmark
EmoSpeech contains keywords with diverse emotions and background sounds, presented to explore new challenges in audio analysis.
1 paper · 0 benchmarks
IRLCov19 is a multilingual Twitter dataset related to Covid-19 collected in the period between February 2020 to July 2020 specifically for regional languages in India.
1 paper · 0 benchmarks
M3LS (Multi-Lingual Multi-Modal Summarization Dataset)
Significant developments in techniques such as encoder-decoder models have enabled us to represent information comprising multiple modalities.
1 paper · 0 benchmarks
MAKED (MultiModal MultiLingual Summarization and Keyword Extraction Dataset)
Keyword extraction is an integral task for many downstream problems like clustering, recommendation, search and classification.
1 paper · 0 benchmarks
MILU (Multi-task Indic Language Understanding Benchmark)
Overview MILU (Multi-task Indic Language Understanding Benchmark) is a comprehensive evaluation dataset designed to assess the performance of Large Language Models (LLMs) across 11 Indic languages.
1 paper · 0 benchmarks
We provide a new data set XWikiRef for the task of Cross-lingual Multi-document Summarization.
1 paper · 0 benchmarks
We present sentence aligned parallel corpora across 10 Indian Languages - Hindi, Telugu, Tamil, Malayalam, Gujarati, Urdu, Bengali, Oriya, Marathi, Punjabi, and English - many of which are categorized as low resource.
0 papers · 0 benchmarks
Paper counts and descriptions are the archive's, frozen 2025-07-28; no citation counts, no stars, no trending. Sorting by "most cited" or "newest" was a live-site feature the archive does not carry.