117 citations · 394 across the 32 of their papers we have counts for
8 papers · 2 filters
Conformer-Kernel with Query Term Independence at TREC 2020 Deep Learning Track
Bhaskar Mitra, Sebastian Hofstatter, Hamed Zamani +1
We benchmark Conformer-Kernel models under the strict blind evaluation setting of the TREC 2020 Deep Learning track. In particular, we study the impact of incorporating: (i) Explic…
Conformer-Kernel with Query Term Independence for Document Retrieval
Bhaskar Mitra, Sebastian Hofstatter, Hamed Zamani +1
The Transformer-Kernel (TK) model has demonstrated strong reranking performance on the TREC Deep Learning benchmark---and can be considered to be an efficient (but slightly less ef…
MIMICS: A Large-Scale Data Collection for Search Clarification
Hamed Zamani, Gord Lueck, Everest Chen +3
Search clarification has recently attracted much attention due to its applications in search engines. It has also been recognized as a major component in conversational information…
ORCAS: 18 Million Clicked Query-Document Pairs for Analyzing Search
Nick Craswell, Daniel Campos, Bhaskar Mitra +2
Users of Web search engines reveal their information needs through queries and clicks, making click logs a useful asset for information retrieval. However, click logs have not been…
Analyzing and Learning from User Interactions for Search Clarification
Hamed Zamani, Bhaskar Mitra, Everest Chen +5
Asking clarifying questions in response to search queries has been recognized as a useful technique for revealing the underlying intent of the query. Clarification has applications…
Local Self-Attention over Long Text for Efficient Document Retrieval
Sebastian Hofstätter, Hamed Zamani, Bhaskar Mitra +2
Neural networks, particularly Transformer-based architectures, have achieved significant performance improvements on several retrieval benchmarks. When the items being retrieved ar…