Maria Maistro
7 papers in the PaperMetrix corpus
Papers by this author
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A preliminary comparison of job, talent, and web search
2018 · CEUR Workshop Proceedings
Copyright held by the author(s). This paper presents an initial comparison of user behavior in job, talent, and web search using query and click logs from a popular employment marketplace. The observations suggest that the …
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Continuation Methods and Curriculum Learning for Learning to Rank
2018
In this paper we explore the use of Continuation Methods and Curriculum Learning techniques in the area of Learning to Rank. The basic idea is to design the training process as a learning path across …
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Multi-Head Self-Attention with Role-Guided Masks
2020 · arXiv (Cornell University)
The state of the art in learning meaningful semantic representations of words is the Transformer model and its attention mechanisms. Simply put, the attention mechanisms learn to attend to specific parts of the input dispensing …
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University of Copenhagen Participation in TREC Health Misinformation Track 2020
2021 · VBN Forskningsportal (Aalborg Universitet)
In this paper, we describe our participation in the TREC Health Misinformation Track 2020. We submitted $11$ runs to the Total Recall Task and 13 runs to the Ad Hoc task. Our approach consists of …
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Principled Multi-Aspect Evaluation Measures of Rankings
2021
Information Retrieval evaluation has traditionally focused on defining principled ways of assessing the relevance of a ranked list of documents with respect to a query. Several methods extend this type of evaluation beyond relevance, making …
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Joint Evaluation of Fairness and Relevance in Recommender Systems with Pareto Frontier
2025
Fairness and relevance are two important aspects of recommender systems (RSs). Typically, they are evaluated either (i) separately by individual measures of fairness and relevance, or (ii) jointly using a single measure that accounts for …
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As easy as PIE: understanding when pruning causes language models to disagree
2025 · arXiv (Cornell University)
Language Model (LM) pruning compresses the model by removing weights, nodes, or other parts of its architecture. Typically, pruning focuses on the resulting efficiency gains at the cost of effectiveness. However, when looking at how …