Zobrazeno 1 - 10
of 1 640
pro vyhledávání: '"A. A. Arabzadeh"'
Autor:
Mohanty, Shrestha, Arabzadeh, Negar, Tupini, Andrea, Sun, Yuxuan, Skrynnik, Alexey, Zholus, Artem, Côté, Marc-Alexandre, Kiseleva, Julia
Seamless interaction between AI agents and humans using natural language remains a key goal in AI research. This paper addresses the challenges of developing interactive agents capable of understanding and executing grounded natural language instruct
Externí odkaz:
http://arxiv.org/abs/2407.08898
We study ranked list truncation (RLT) from a novel "retrieve-then-re-rank" perspective, where we optimize re-ranking by truncating the retrieved list (i.e., trim re-ranking candidates). RLT is crucial for re-ranking as it can improve re-ranking effic
Externí odkaz:
http://arxiv.org/abs/2404.18185
This paper is a draft of a chapter intended to appear in a forthcoming book on generative information retrieval, co-edited by Chirag Shah and Ryen White. In this chapter, we consider generative information retrieval evaluation from two distinct but i
Externí odkaz:
http://arxiv.org/abs/2404.08137
Query performance prediction (QPP) aims to estimate the retrieval quality of a search system for a query without human relevance judgments. Previous QPP methods typically return a single scalar value and do not require the predicted values to approxi
Externí odkaz:
http://arxiv.org/abs/2404.01012
Publikováno v:
Annual International ACM SIGIR Conference on Research and Development in Information Retrieval in the Asia Pacific Region (SIGIR-AP '23), November 26--28, 2023, Beijing, China
Current large language models (LLMs) can exhibit near-human levels of performance on many natural language-based tasks, including open-domain question answering. Unfortunately, at this time, they also convincingly hallucinate incorrect answers, so th
Externí odkaz:
http://arxiv.org/abs/2309.11392
Current large language models (LLMs) can exhibit near-human levels of performance on many natural language tasks, including open-domain question answering. Unfortunately, they also convincingly hallucinate incorrect answers, so that responses to ques
Externí odkaz:
http://arxiv.org/abs/2306.13781
Query performance prediction (QPP) is a core task in information retrieval. The QPP task is to predict the retrieval quality of a search system for a query without relevance judgments. Research has shown the effectiveness and usefulness of QPP for ad
Externí odkaz:
http://arxiv.org/abs/2305.10923
Autor:
Mohanty, Shrestha, Arabzadeh, Negar, Kiseleva, Julia, Zholus, Artem, Teruel, Milagro, Awadallah, Ahmed, Sun, Yuxuan, Srinet, Kavya, Szlam, Arthur
Human intelligence's adaptability is remarkable, allowing us to adjust to new tasks and multi-modal environments swiftly. This skill is evident from a young age as we acquire new abilities and solve problems by imitating others or following natural l
Externí odkaz:
http://arxiv.org/abs/2305.10783
Publikováno v:
راهبرد مدیریت مالی, Vol 12, Iss 3, Pp 1-24 (2024)
AbstractObjective: It is important for investors and traders to be aware of the stock price in listed companies, so it is important to identify the factors affecting Stock price informativeness. The purpose of the current research is to interpret the
Externí odkaz:
https://doaj.org/article/fd919327f3a5464fad8b6c270c99616e
Autor:
Elham Jafari Maskouni, Samaneh Abbasi, Elham Mousavi, Zahra Najafimemar, Ali Mohammad Arabzadeh, Mehrdad Farrokhnia, Saeedeh Ebrahimi
Publikováno v:
Journal of Acute Disease, Vol 13, Iss 3, Pp 111-115 (2024)
Objective: To explore expression level of interferon-stimulated genes PKR, OASI, MX1, and ISG15 in peripheral blood mononuclear cells of COVID-19 patients. Methods: In this study, changes in the expression of four interferon-stimulated genes (ISGs),
Externí odkaz:
https://doaj.org/article/4f0b6ffee6b44588b62f26b1e57d0dce