14 citations · 14 across the 3 of their papers we have counts for
6 papers
Revisiting the Compositional Generalization Abilities of Neural Sequence Models
Arkil Patel, Satwik Bhattamishra, Phil Blunsom +1
Compositional generalization is a fundamental trait in humans, allowing us to effortlessly combine known phrases to form novel sentences. Recent works have claimed that standard se…
Are NLP Models really able to Solve Simple Math Word Problems?
Arkil Patel, Satwik Bhattamishra, Navin Goyal
The problem of designing NLP solvers for math word problems (MWP) has seen sustained research activity and steady gains in the test accuracy. Since existing solvers achieve high pe…
On the Practical Ability of Recurrent Neural Networks to Recognize Hierarchical Languages
Satwik Bhattamishra, Kabir Ahuja, Navin Goyal
While recurrent models have been effective in NLP tasks, their performance on context-free languages (CFLs) has been found to be quite weak. Given that CFLs are believed to capture…
On the Ability and Limitations of Transformers to Recognize Formal Languages
Satwik Bhattamishra, Kabir Ahuja, Navin Goyal
Transformers have supplanted recurrent models in a large number of NLP tasks. However, the differences in their abilities to model different syntactic properties remain largely unk…
On the Computational Power of Transformers and its Implications in Sequence Modeling
Satwik Bhattamishra, Arkil Patel, Navin Goyal
Transformers are being used extensively across several sequence modeling tasks. Significant research effort has been devoted to experimentally probe the inner workings of Transform…
Unsung Challenges of Building and Deploying Language Technologies for Low Resource Language Communities
Pratik Joshi, Christain Barnes, Sebastin Santy +7
In this paper, we examine and analyze the challenges associated with developing and introducing language technologies to low-resource language communities. While doing so, we bring…