1 citations · 1 across the 4 of their papers we have counts for
4 papers
All Should Be Equal in the Eyes of Language Models: Counterfactually Aware Fair Text Generation
Pragyan Banerjee, Abhinav Java, Surgan Jandial +4
Fairness in Language Models (LMs) remains a longstanding challenge, given the inherent biases in training data that can be perpetuated by models and affect the downstream tasks. Re…
HyHTM: Hyperbolic Geometry based Hierarchical Topic Models
Simra Shahid, Tanay Anand, Nikitha Srikanth +3
Hierarchical Topic Models (HTMs) are useful for discovering topic hierarchies in a collection of documents. However, traditional HTMs often produce hierarchies where lowerlevel top…
Explain like I am BM25: Interpreting a Dense Model's Ranked-List with a Sparse Approximation
Michael Llordes, Debasis Ganguly, Sumit Bhatia +1
Neural retrieval models (NRMs) have been shown to outperform their statistical counterparts owing to their ability to capture semantic meaning via dense document representations. T…
LM-CORE: Language Models with Contextually Relevant External Knowledge
Jivat Neet Kaur, Sumit Bhatia, Milan Aggarwal +2
Large transformer-based pre-trained language models have achieved impressive performance on a variety of knowledge-intensive tasks and can capture factual knowledge in their parame…