Samasāmayik: A Parallel Dataset for Hindi-Sanskrit Machine Translation
Samasāmayik: A Parallel Dataset for Hindi-Sanskrit Machine Translation explores A new parallel dataset for Hindi-Sanskrit translation, enabling significant performance gains for contemporary language models.. Commercial viability score: 7/10 in Machine Translation.
BUILDER'S SANDBOX
Build This Paper
Use an AI coding agent to implement this research.
OpenAI CodexAI Agent
Lightweight coding agent in your terminal.
Claude CodeAI Agent
Agentic coding tool for terminal workflows.
AntiGravity IDEScaffolding
AI agent mindset installer and workflow scaffolder.
CursorIDE
AI-first code editor built on VS Code.
VS CodeIDE
Free, open-source editor by Microsoft.
Recommended Stack
Startup Essentials
Estimated $9K - $13K over 6-10 weeks.
See exactly what it costs to build this -- with 3 comparable funded startups.
7-day free trial. Cancel anytime.
Discover the researchers behind this paper and find similar experts.
7-day free trial. Cancel anytime.
Related Papers
- Builds On ThisMultilingual TinyStories: A Synthetic Combinatorial Corpus of Indic Children's Stories for Training Small Language ModelsViability: 6.0
- Builds On ThisSiDiaC-v.2.0: Sinhala Diachronic Corpus Version 2.0Viability: 2.0
- Builds On ThisDohaScript: A Large-Scale Multi-Writer Dataset for Continuous Handwritten Hindi TextViability: 4.0
- Builds On ThisRaising Bars, Not Parameters: LilMoo Compact Language Model for HindiViability: 6.0
- Builds On ThisPINGALA: Prosody-Aware Decoding for Sanskrit Poetry Generation