3 citations · 5 across the 3 of their papers we have counts for
3 papers · 1 filter
MILU: A Multi-task Indic Language Understanding Benchmark
Sshubam Verma, Mohammed Safi Ur Rahman Khan, Vishwajeet Kumar +2
Evaluating Large Language Models (LLMs) in low-resource and linguistically diverse languages remains a significant challenge in NLP, particularly for languages using non-Latin scri…
Airavata: Introducing Hindi Instruction-tuned LLM
Jay Gala, Thanmay Jayakumar, Jaavid Aktar Husain +8
We announce the initial release of "Airavata," an instruction-tuned LLM for Hindi. Airavata was created by fine-tuning OpenHathi with diverse, instruction-tuning Hindi datasets to…
PUB: A Pragmatics Understanding Benchmark for Assessing LLMs' Pragmatics Capabilities
Settaluri Lakshmi Sravanthi, Meet Doshi, Tankala Pavan Kalyan +3
LLMs have demonstrated remarkable capability for understanding semantics, but they often struggle with understanding pragmatics. To demonstrate this fact, we release a Pragmatics U…