14 citations · 33 across the 18 of their papers we have counts for
4 papers · 1 filter
Teaching Transformers Causal Reasoning through Axiomatic Training
Aniket Vashishtha, Abhinav Kumar, Atharva Pandey +4
For text-based AI systems to interact in the real world, causal reasoning is an essential skill. Since active interventions are costly, we study to what extent a system can learn c…
Learning Syntax Without Planting Trees: Understanding Hierarchical Generalization in Transformers
Kabir Ahuja, Vidhisha Balachandran, Madhur Panwar +4
Transformers trained on natural language data have been shown to learn its hierarchical structure and generalize to sentences with unseen syntactic structures without explicitly en…
DIALECTBENCH: A NLP Benchmark for Dialects, Varieties, and Closely-Related Languages
Fahim Faisal, Orevaoghene Ahia, Aarohi Srivastava +4
Language technologies should be judged on their usefulness in real-world use cases. An often overlooked aspect in natural language processing (NLP) research and evaluation is langu…
MAFIA: Multi-Adapter Fused Inclusive LanguAge Models
Prachi Jain, Ashutosh Sathe, Varun Gumma +2
Pretrained Language Models (PLMs) are widely used in NLP for various tasks. Recent studies have identified various biases that such models exhibit and have proposed methods to corr…