3 citations · 4 across the 4 of their papers we have counts for
4 papers · 1 filter
How Good is Zero-Shot MT Evaluation for Low Resource Indian Languages?
Anushka Singh, Ananya B. Sai, Raj Dabre +3
While machine translation evaluation has been studied primarily for high-resource languages, there has been a recent interest in evaluation for low-resource languages due to the in…
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…
A Comprehensive Analysis of Adapter Efficiency
Nandini Mundra, Sumanth Doddapaneni, Raj Dabre +3
Adapters have been positioned as a parameter-efficient fine-tuning (PEFT) approach, whereby a minimal number of parameters are added to the model and fine-tuned. However, adapters…
Transition-Based Deep Input Linearization
Ratish Puduppully, Yue Zhang, Manish Shrivastava
Traditional methods for deep NLG adopt pipeline approaches comprising stages such as constructing syntactic input, predicting function words, linearizing the syntactic input and ge…