no code implementations • EMNLP (MRL) 2021 • Megh Thakkar, Vishwa Shah, Ramit Sawhney, Debdoot Mukherjee
There have been efforts in cross-lingual transfer learning for various tasks.
1 code implementation • 22 Apr 2024 • Vishruth Veerendranath, Vishwa Shah, Kshitish Ghate
Quantitative and numerical comprehension in language is an important task in many fields like education and finance, but still remains a challenging task for language models.
no code implementations • 18 Apr 2024 • Abhinav Rao, Akhila Yerukola, Vishwa Shah, Katharina Reinecke, Maarten Sap
We introduce NormAd, a novel dataset, which includes 2. 6k stories that represent social and cultural norms from 75 countries, to assess the ability of LLMs to adapt to different granular levels of socio-cultural contexts such as the country of origin, its associated cultural values, and prevalent social norms.
no code implementations • 31 Jul 2023 • Arnav Hiray, Pratvi Shah, Vishwa Shah, Agam Shah, Sudheer Chava, Mukesh Tiwari
We use novel hourly-resolution data and Kendall's Tau correlation to explore the interconnectedness of the cryptocurrency market.
no code implementations • 19 Sep 2022 • Vishwa Shah, Aditya Sharma, Gautam Shroff, Lovekesh Vig, Tirtharaj Dash, Ashwin Srinivasan
However, connectionist models struggle to include explicit domain knowledge for deductive reasoning.
1 code implementation • 9 May 2018 • Matthew Guzdial, Nicholas Liao, Vishwa Shah, Mark O. Riedl
In this paper we present the Creative Invention Benchmark (CrIB), a 2000-problem benchmark for evaluating a particular facet of computational creativity.