60 citations · 547 across the 40 of their papers we have counts for
6 papers · 1 filter
Efficient Neural Ranking using Forward Indexes
Jurek Leonhardt, Koustav Rudra, Megha Khosla +2
Neural document ranking approaches, specifically transformer models, have achieved impressive gains in ranking performance. However, query processing using such over-parameterized…
Learnt Sparsification for Interpretable Graph Neural Networks
Mandeep Rathee, Zijian Zhang, Thorben Funke +2
Graph neural networks (GNNs) have achieved great success on various tasks and fields that require relational modeling. GNNs aggregate node features using the graph structure as ind…
Extractive Explanations for Interpretable Text Ranking
Jurek Leonhardt, Koustav Rudra, Avishek Anand
Neural document ranking models perform impressively well due to superior language understanding gained from pre-training tasks. However, due to their complexity and large number of…
BERTnesia: Investigating the capture and forgetting of knowledge in BERT
Jonas Wallat, Jaspreet Singh, Avishek Anand
Probing complex language models has recently revealed several insights into linguistic and semantic patterns found in the learned representations. In this article, we probe BERT sp…
Zorro: Valid, Sparse, and Stable Explanations in Graph Neural Networks
Thorben Funke, Megha Khosla, Mandeep Rathee +1
With the ever-increasing popularity and applications of graph neural networks, several proposals have been made to explain and understand the decisions of a graph neural network. E…
Dissonance Between Human and Machine Understanding
Zijian Zhang, Jaspreet Singh, Ujwal Gadiraju +1
Complex machine learning models are deployed in several critical domains including healthcare and autonomous vehicles nowadays, albeit as functional black boxes. Consequently, ther…