Search Results for author:
Found 18 papers, 9 papers with code
DoSSIER at MedVidQA 2022: Text-based Approaches to Medical Video Answer Localization Problem
We propose two answer localization approaches that use only textual information extracted from the video.
IR like a SIR: Sense-enhanced Information Retrieval for Multiple Languages
With the advent of contextualized embeddings, attention towards neural ranking approaches for Information Retrieval increased considerably.
Benchmark for Research Theme Classification of Scholarly Documents
We present a new gold-standard dataset and a benchmark for the Research Theme Identification task, a sub-task of the Scholarly Knowledge Graph Generation shared task, at the 3rd Workshop on Scholarly Document Processing.
DESIRE-ME: Domain-Enhanced Supervised Information REtrieval using Mixture-of-Experts
Open-domain question answering requires retrieval systems able to cope with the diverse and varied nature of questions, providing accurate answers across a broad spectrum of query types and topics.
SE-PEF: a Resource for Personalized Expert Finding
The problem of personalization in Information Retrieval has been under study for a long time.
Denoising Attention for Query-aware User Modeling in Personalized Search
This approach allows taking into account the diversity of the user's interests by giving more importance to those related to the current search performed by the user.
Fuzzy order-sorted feature logic
Based on this definition we define a fuzzy semantics of OSF logic where sort symbols and OSF terms denote fuzzy sets.
Effective Matching of Patients to Clinical Trials using Entity Extraction and Neural Re-ranking
Our approach involves two key components in a pipeline-based model: (i) a data enrichment technique for enhancing both queries and documents during the first retrieval stage, and (ii) a novel re-ranking schema that uses a Transformer network in a setup adapted to this task by leveraging the structure of the CT documents.
SE-PQA: Personalized Community Question Answering
Personalization in Information Retrieval is a topic studied for a long time.
Enhancing Documents with Multidimensional Relevance Statements in Cross-encoder Re-ranking
In this paper, we propose a novel approach to consider multiple dimensions of relevance beyond topicality in cross-encoder re-ranking.
Utilizing ChatGPT to Enhance Clinical Trial Enrollment
Clinical trials are a critical component of evaluating the effectiveness of new medical interventions and driving advancements in medical research.
Retrieval for Extremely Long Queries and Documents with RPRS: a Highly Efficient and Effective Transformer-based Re-Ranker
Furthermore, our method solves the problem of the low-resource training in QBD retrieval tasks as it does not need large amounts of training data, and has only three parameters with a limited range that can be optimized with a grid search even if a small amount of labeled data is available.
Injecting the BM25 Score as Text Improves BERT-Based Re-rankers
In this paper we propose a novel approach for combining first-stage lexical retrieval models and Transformer-based re-rankers: we inject the relevance score of the lexical model as a token in the middle of the input of the cross-encoder re-ranker.
UNIMIB at TREC 2021 Clinical Trials Track
We have investigated the effect of different query representations combined with several retrieval models on the retrieval performance.
LeiBi@COLIEE 2022: Aggregating Tuned Lexical Models with a Cluster-driven BERT-based Model for Case Law Retrieval
Our methodology consists of four steps; in detail, given a legal case as a query, we reformulate it by extracting various meaningful sentences or n-grams.
Responsible AI in Healthcare
This article discusses open problems, implemented solutions, and future research in the area of responsible AI in healthcare.
Expert Finding in Legal Community Question Answering
In the legal domain, there is a large knowledge gap between the experts and the searchers, and the content on the legal QA websites consist of a combination formal and informal communication.
Answering Fuzzy Queries over Fuzzy DL-Lite Ontologies
In this paper we study the problem of answering conjunctive queries and threshold queries w. r. t.
