14 citations · 18 across the 18 of their papers we have counts for
3 papers · 1 filter
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…