Search Results for author:
Found 8 papers, 3 papers with code
On the low-shot transferability of [V]-Mamba
The strength of modern large-scale neural networks lies in their ability to efficiently adapt to new tasks with few examples.
Airavata: Introducing Hindi Instruction-tuned LLM
We announce the initial release of "Airavata," an instruction-tuned LLM for Hindi.
RomanSetu: Efficiently unlocking multilingual capabilities of Large Language Models models via Romanization
This study addresses the challenge of extending Large Language Models (LLMs) to non-English languages using non-Roman scripts.
An Empirical Study of In-context Learning in LLMs for Machine Translation
While we establish the significance of the quality of the target distribution over the source distribution of demonstrations, we further observe that perturbations sometimes act as regularizers, resulting in performance improvements.
Adaptive-Labeling for Enhancing Remote Sensing Cloud Understanding
Cloud analysis is a critical component of weather and climate science, impacting various sectors like disaster management.
IndicTrans2: Towards High-Quality and Accessible Machine Translation Models for all 22 Scheduled Indian Languages
Prior to this work, there was (i) no parallel training data spanning all 22 languages, (ii) no robust benchmarks covering all these languages and containing content relevant to India, and (iii) no existing translation models which support all the 22 scheduled languages of India.
A Federated Approach for Hate Speech Detection
Hate speech detection has been the subject of high research attention, due to the scale of content created on social media.
Learning from Mistakes based on Class Weighting with Application to Neural Architecture Search
In this work, we aim to investigate how effectively we can leverage this exceptional learning ability to improve machine learning models.
