# Itihasa: A large-scale corpus for Sanskrit to English translation

arXiv: https://arxiv.org/abs/2106.03269 · HTML: https://mlsanity.com/paper/2106.03269/

## Key facts

- Cited by 13 papers in the map (data through 14 Oct 2026).
- Builds on 9 of its 32 references that are in the map.
- First posted on arXiv 6 Jun 2021.

## Builds on (most cited first, 9 of 9)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [Adam: A Method for Stochastic Optimization](https://mlsanity.com/paper/1412.6980/) (2014)
- [Neural Machine Translation of Rare Words with Subword Units](https://mlsanity.com/paper/1508.07909/) (2015)
- [MuRIL: Multilingual Representations for Indian Languages](https://mlsanity.com/paper/2103.10730/) (2021)
- [On the Limitations of Unsupervised Bilingual Dictionary Induction](https://mlsanity.com/paper/1805.03620/) (2018)
- [PMIndia -- A Collection of Parallel Corpora of Languages of India](https://mlsanity.com/paper/2001.09907/) (2020)
- [Validation and Normalization of DCS corpus using Sanskrit Heritage tools to build a tagged Gold Corpus](https://mlsanity.com/paper/2005.06545/) (2020)
- [Sanskrit Sandhi Splitting using seq2(seq)^2](https://mlsanity.com/paper/1801.00428/) (2018)
- [Sanskrit Segmentation Revisited](https://mlsanity.com/paper/2005.06383/) (2020)

## Built on by (most cited first, 13 of 13)

- [A Novel Multi-Task Learning Approach for Context-Sensitive Compound Type Identification in Sanskrit](https://mlsanity.com/paper/2208.10310/) (2022)
- [S=amayik: A Benchmark and Dataset for English-Sanskrit Translation](https://mlsanity.com/paper/2305.14004/) (2023)
- [NLPineers@ NLU of Devanagari Script Languages 2025: Hate Speech Detection using Ensembling of BERT-based models](https://mlsanity.com/paper/2412.08163/) (2024)
- [Mitrasamgraha: A Comprehensive Classical Sanskrit Machine Translation Dataset](https://mlsanity.com/paper/2601.07314/) (2026)
- [DepNeCTI: Dependency-based Nested Compound Type Identification for Sanskrit](https://mlsanity.com/paper/2310.09501/) (2023)
- [Samas=amayik: A Parallel Dataset for Hindi-Sanskrit Machine Translation](https://mlsanity.com/paper/2603.24307/) (2026)
- [Can We Triage LLM Translation Errors in Classical Texts Without Human References? Source Novelty, GEMBA Scoring, and Budgeted Review through Pali-to-English Translation](https://mlsanity.com/paper/2609.14963/) (2026)
- [1-800-SHARED-TASKS @ NLU of Devanagari Script Languages: Detection of Language, Hate Speech, and Targets using LLMs](https://mlsanity.com/paper/2411.06850/) (2024)
- [IITR-CIOL@NLU of Devanagari Script Languages 2025: Multilingual Hate Speech Detection and Target Identification in Devanagari-Scripted Languages](https://mlsanity.com/paper/2412.17947/) (2024)
- [Mah=an=ama: A Unique Testbed for Literary Entity Discovery and Linking](https://mlsanity.com/paper/2509.19844/) (2025)
- [Padamitra: Grounded Glossary Generation for Classical Sanskrit](https://mlsanity.com/paper/2608.25038/) (2026)
- [Fewer Words, Not Fewer Tokens: Measuring the Sanskrit Tokenization Penalty per Proposition](https://mlsanity.com/paper/2609.12960/) (2026)
- [When Do Agents Help? Embedding, LLM and Agentic Alignment of Classical Texts and Their Translations](https://mlsanity.com/paper/2609.33691/) (2026)

## Abstract (arXiv)

This work introduces Itihasa, a large-scale translation dataset containing 93,000 pairs of Sanskrit shlokas and their English translations. The shlokas are extracted from two Indian epics viz., The Ramayana and The Mahabharata. We first describe the motivation behind the curation of such a dataset and follow up with empirical analysis to bring out its nuances. We then benchmark the performance of standard translation models on this corpus and show that even state-of-the-art transformer architectures perform poorly, emphasizing the complexity of the dataset.