60 citations · 141 across the 7 of their papers we have counts for
8 papers
Towards Axiomatic Explanations for Neural Ranking Models
Michael Völske, Alexander Bondarenko, Maik Fröbe +4
Recently, neural networks have been successfully employed to improve upon state-of-the-art performance in ad-hoc retrieval tasks via machine-learned ranking functions. While neural…
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…
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…
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 paper, we probe BERT spec…
Valid Explanations for Learning to Rank Models
Jaspreet Singh, Zhenye Wang, Megha Khosla +1
Learning-to-rank (LTR) is a class of supervised learning techniques that apply to ranking problems dealing with a large number of features. The popularity and widespread applicatio…
AMUSED: A Multi-Stream Vector Representation Method for Use in Natural Dialogue
Gaurav Kumar, Rishabh Joshi, Jaspreet Singh +1
The problem of building a coherent and non-monotonous conversational agent with proper discourse and coverage is still an area of open research. Current architectures only take car…