12 citations · 29 across the 10 of their papers we have counts for
12 papers
XTREME-UP: A User-Centric Scarce-Data Benchmark for Under-Represented Languages
Sebastian Ruder, Jonathan H. Clark, Alexander Gutkin +24
Data scarcity is a crucial issue for the development of highly multilingual NLP systems. Yet for many under-represented languages (ULs) -- languages for which NLP re-search is part…
CrysGNN : Distilling pre-trained knowledge to enhance property prediction for crystalline materials
Kishalay Das, Bidisha Samanta, Pawan Goyal +3
In recent years, graph neural network (GNN) based approaches have emerged as a powerful technique to encode complex topological structure of crystal materials in an enriched repres…
Bootstrapping Multilingual Semantic Parsers using Large Language Models
Abhijeet Awasthi, Nitish Gupta, Bidisha Samanta +3
Despite cross-lingual generalization demonstrated by pre-trained multilingual models, the translate-train paradigm of transferring English datasets across multiple languages remain…
A Data Bootstrapping Recipe for Low Resource Multilingual Relation Classification
Arijit Nag, Bidisha Samanta, Animesh Mukherjee +2
Relation classification (sometimes called 'extraction') requires trustworthy datasets for fine-tuning large language models, as well as for evaluation. Data collection is challengi…
Few-shot Controllable Style Transfer for Low-Resource Multilingual Settings
Kalpesh Krishna, Deepak Nathani, Xavier Garcia +2
Style transfer is the task of rewriting a sentence into a target style while approximately preserving content. While most prior literature assumes access to a large style-labelled…
CrysXPP:An Explainable Property Predictor for Crystalline Materials
Kishalay Das, Bidisha Samanta, Pawan Goyal +3
We present a deep-learning framework, CrysXPP, to allow rapid prediction of electronic, magnetic and elastic properties of a wide range of materials with reasonable precision. Alth…