326 citations · 717 across the 90 of their papers we have counts for
8 papers · 1 filter
Towards Building ASR Systems for the Next Billion Users
Tahir Javed, Sumanth Doddapaneni, Abhigyan Raman +5
Recent methods in speech and language technology pretrain very LARGE models which are fine-tuned for specific tasks. However, the benefits of such LARGE models are often limited to…
OpenHands: Making Sign Language Recognition Accessible with Pose-based Pretrained Models across Languages
Prem Selvaraj, Gokul NC, Pratyush Kumar +1
AI technologies for Natural Languages have made tremendous progress recently. However, commensurate progress has not been made on Sign Languages, in particular, in recognizing sign…
A Framework for Rationale Extraction for Deep QA models
Sahana Ramnath, Preksha Nema, Deep Sahni +1
As neural-network-based QA models become deeper and more complex, there is a demand for robust frameworks which can access a model's rationale for its prediction. Current technique…
On the Prunability of Attention Heads in Multilingual BERT
Aakriti Budhraja, Madhura Pande, Pratyush Kumar +1
Large multilingual models, such as mBERT, have shown promise in crosslingual transfer. In this work, we employ pruning to quantify the robustness and interpret layer-wise importanc…
Perturbation CheckLists for Evaluating NLG Evaluation Metrics
Ananya B. Sai, Tanay Dixit, Dev Yashpal Sheth +2
Natural Language Generation (NLG) evaluation is a multifaceted task requiring assessment of multiple desirable criteria, e.g., fluency, coherency, coverage, relevance, adequacy, ov…
IndicBART: A Pre-trained Model for Indic Natural Language Generation
Raj Dabre, Himani Shrotriya, Anoop Kunchukuttan +3
In this paper, we study pre-trained sequence-to-sequence models for a group of related languages, with a focus on Indic languages. We present IndicBART, a multilingual, sequence-to…
A Primer on Pretrained Multilingual Language Models
Sumanth Doddapaneni, Gowtham Ramesh, Mitesh M. Khapra +2
Multilingual Language Models (\MLLMs) such as mBERT, XLM, XLM-R, \textit{etc.} have emerged as a viable option for bringing the power of pretraining to a large number of languages.…
The heads hypothesis: A unifying statistical approach towards understanding multi-headed attention in BERT
Madhura Pande, Aakriti Budhraja, Preksha Nema +2
Multi-headed attention heads are a mainstay in transformer-based models. Different methods have been proposed to classify the role of each attention head based on the relations bet…