Zobrazeno 1 - 10
of 937
pro vyhledávání: '"Goharian A"'
Autor:
Sotudeh, Sajad, Goharian, Nazli
This study examines the potential of integrating Learning-to-Rank (LTR) with Query-focused Summarization (QFS) to enhance the summary relevance via content prioritization. Using a shared secondary decoder with the summarization decoder, we carry out
Externí odkaz:
http://arxiv.org/abs/2411.00324
Publikováno v:
ACM Symposium on Document Engineering 2024 (DocEng '24), August 20-23, 2024, San Jose, CA, USA. ACM, New York, NY, USA
Sparse retrieval methods like BM25 are based on lexical overlap, focusing on the surface form of the terms that appear in the query and the document. The use of inverted indices in these methods leads to high retrieval efficiency. On the other hand,
Externí odkaz:
http://arxiv.org/abs/2409.05882
Publikováno v:
The Second Workshop on Generative Information Retrieval at ACM SIGIR 2024
Generative language models hallucinate. That is, at times, they generate factually flawed responses. These inaccuracies are particularly insidious because the responses are fluent and well-articulated. We focus on the task of Grounded Answer Generati
Externí odkaz:
http://arxiv.org/abs/2409.00085
Gastrointestinal mucosal changes can cause cancers after some years and early diagnosing them can be very useful to prevent cancers and early treatment. In this article, 8 classes of mucosal changes and anatomical landmarks including Polyps, Ulcerati
Externí odkaz:
http://arxiv.org/abs/2307.16198
Autor:
Chang, Shuyu Y, Ghahremani, Zahra, Manuel, Laura, Erfani, Mohammad, Shen, Chaopeng, Cohen, Sagy, Van Meter, Kimberly, Pierce, Jennifer L, Meselhe, Ehab A, Goharian, Erfan
Hydraulic geometry parameters describing river hydrogeomorphic is important for flood forecasting. Although well-established, power-law hydraulic geometry curves have been widely used to understand riverine systems and mapping flooding inundation wor
Externí odkaz:
http://arxiv.org/abs/2312.11476
Retrieval approaches that score documents based on learned dense vectors (i.e., dense retrieval) rather than lexical signals (i.e., conventional retrieval) are increasingly popular. Their ability to identify related documents that do not necessarily
Externí odkaz:
http://arxiv.org/abs/2307.16779
Autor:
Sotudeh, Sajad, Goharian, Nazli
Query-focused summarization (QFS) is a challenging task in natural language processing that generates summaries to address specific queries. The broader field of Generative Information Retrieval (Gen-IR) aims to revolutionize information extraction f
Externí odkaz:
http://arxiv.org/abs/2307.07586
Recent Transformer-based summarization models have provided a promising approach to abstractive summarization. They go beyond sentence selection and extractive strategies to deal with more complicated tasks such as novel word generation and sentence
Externí odkaz:
http://arxiv.org/abs/2302.01342
Automatically generating short summaries from users' online mental health posts could save counselors' reading time and reduce their fatigue so that they can provide timely responses to those seeking help for improving their mental state. Recent Tran
Externí odkaz:
http://arxiv.org/abs/2302.00954
Mental health remains a significant challenge of public health worldwide. With increasing popularity of online platforms, many use the platforms to share their mental health conditions, express their feelings, and seek help from the community and cou
Externí odkaz:
http://arxiv.org/abs/2206.00856