5 citations · 7 across the 4 of their papers we have counts for
6 papers
On the Calibration of Massively Multilingual Language Models
Kabir Ahuja, Sunayana Sitaram, Sandipan Dandapat +1
Massively Multilingual Language Models (MMLMs) have recently gained popularity due to their surprising effectiveness in cross-lingual transfer. While there has been much work in ev…
Multi Task Learning For Zero Shot Performance Prediction of Multilingual Models
Kabir Ahuja, Shanu Kumar, Sandipan Dandapat +1
Massively Multilingual Transformer based Language Models have been observed to be surprisingly effective on zero-shot transfer across languages, though the performance varies from…
Global Readiness of Language Technology for Healthcare: What would it Take to Combat the Next Pandemic?
Ishani Mondal, Kabir Ahuja, Mohit Jain +3
The COVID-19 pandemic has brought out both the best and worst of language technology (LT). On one hand, conversational agents for information dissemination and basic diagnosis have…
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…
Syntax-guided Controlled Generation of Paraphrases
Ashutosh Kumar, Kabir Ahuja, Raghuram Vadapalli +1
Given a sentence (e.g., "I like mangoes") and a constraint (e.g., sentiment flip), the goal of controlled text generation is to produce a sentence that adapts the input sentence to…