313 citations · 922 across the 48 of their papers we have counts for
43 papers · 1 filter
Large Language Model Augmented Narrative Driven Recommendations
Sheshera Mysore, Andrew McCallum, Hamed Zamani
Narrative-driven recommendation (NDR) presents an information access problem where users solicit recommendations with verbose descriptions of their preferences and context, for exa…
Pre-Training Multi-Modal Dense Retrievers for Outside-Knowledge Visual Question Answering
Alireza Salemi, Mahta Rafiee, Hamed Zamani
This paper studies a category of visual question answering tasks, in which accessing external knowledge is necessary for answering the questions. This category is called outside-kn…
Soft Prompt Decoding for Multilingual Dense Retrieval
Zhiqi Huang, Hansi Zeng, Hamed Zamani +1
In this work, we explore a Multilingual Information Retrieval (MLIR) task, where the collection includes documents in multiple languages. We demonstrate that applying state-of-the-…
Multivariate Representation Learning for Information Retrieval
Hamed Zamani, Michael Bendersky
Dense retrieval models use bi-encoder network architectures for learning query and document representations. These representations are often in the form of a vector representation…
A Personalized Dense Retrieval Framework for Unified Information Access
Hansi Zeng, Surya Kallumadi, Zaid Alibadi +2
Developing a universal model that can efficiently and effectively respond to a wide range of information access requests -- from retrieval to recommendation to question answering -…
Generalized Weak Supervision for Neural Information Retrieval
Yen-Chieh Lien, Hamed Zamani, W. Bruce Croft
Neural ranking models (NRMs) have demonstrated effective performance in several information retrieval (IR) tasks. However, training NRMs often requires large-scale training data, w…
Editable User Profiles for Controllable Text Recommendation
Sheshera Mysore, Mahmood Jasim, Andrew McCallum +1
Methods for making high-quality recommendations often rely on learning latent representations from interaction data. These methods, while performant, do not provide ready mechanism…
Learning List-Level Domain-Invariant Representations for Ranking
Ruicheng Xian, Honglei Zhuang, Zhen Qin +7
Domain adaptation aims to transfer the knowledge learned on (data-rich) source domains to (low-resource) target domains, and a popular method is invariant representation learning,…
Are We There Yet? A Decision Framework for Replacing Term Based Retrieval with Dense Retrieval Systems
Sebastian Hofstätter, Nick Craswell, Bhaskar Mitra +2
Recently, several dense retrieval (DR) models have demonstrated competitive performance to term-based retrieval that are ubiquitous in search systems. In contrast to term-based mat…
MIMICS-Duo: Offline & Online Evaluation of Search Clarification
Leila Tavakoli, Johanne R. Trippas, Hamed Zamani +2
Asking clarification questions is an active area of research; however, resources for training and evaluating search clarification methods are not sufficient. To address this issue,…
Curriculum Learning for Dense Retrieval Distillation
Hansi Zeng, Hamed Zamani, Vishwa Vinay
Recent work has shown that more effective dense retrieval models can be obtained by distilling ranking knowledge from an existing base re-ranking model. In this paper, we propose a…
Conversational Information Seeking
Hamed Zamani, Johanne R. Trippas, Jeff Dalton +1
Conversational information seeking (CIS) is concerned with a sequence of interactions between one or more users and an information system. Interactions in CIS are primarily based o…
Explaining Documents' Relevance to Search Queries
Razieh Rahimi, Youngwoo Kim, Hamed Zamani +1
We present GenEx, a generative model to explain search results to users beyond just showing matches between query and document words. Adding GenEx explanations to search results gr…
Analysing Mixed Initiatives and Search Strategies during Conversational Search
Mohammad Aliannejadi, Leif Azzopardi, Hamed Zamani +3
Information seeking conversations between users and Conversational Search Agents (CSAs) consist of multiple turns of interaction. While users initiate a search session, ideally a C…
Current Challenges and Future Directions in Podcast Information Access
Rosie Jones, Hamed Zamani, Markus Schedl +11
Podcasts are spoken documents across a wide-range of genres and styles, with growing listenership across the world, and a rapidly lowering barrier to entry for both listeners and c…
Intra-Document Cascading: Learning to Select Passages for Neural Document Ranking
Sebastian Hofstätter, Bhaskar Mitra, Hamed Zamani +2
An emerging recipe for achieving state-of-the-art effectiveness in neural document re-ranking involves utilizing large pre-trained language models - e.g., BERT - to evaluate all in…
Passage Retrieval for Outside-Knowledge Visual Question Answering
Chen Qu, Hamed Zamani, Liu Yang +2
In this work, we address multi-modal information needs that contain text questions and images by focusing on passage retrieval for outside-knowledge visual question answering. This…
Improving Transformer-Kernel Ranking Model Using Conformer and Query Term Independence
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 e…
CSFCube -- A Test Collection of Computer Science Research Articles for Faceted Query by Example
Sheshera Mysore, Tim O'Gorman, Andrew McCallum +1
Query by Example is a well-known information retrieval task in which a document is chosen by the user as the search query and the goal is to retrieve relevant documents from a larg…
Tip of the Tongue Known-Item Retrieval: A Case Study in Movie Identification
Jaime Arguello, Adam Ferguson, Emery Fine +3
While current information retrieval systems are effective for known-item retrieval where the searcher provides a precise name or identifier for the item being sought, systems tend…
Context-Aware Target Apps Selection and Recommendation for Enhancing Personal Mobile Assistants
Mohammad Aliannejadi, Hamed Zamani, Fabio Crestani +1
Users install many apps on their smartphones, raising issues related to information overload for users and resource management for devices. Moreover, the recent increase in the use…
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…