Zobrazeno 1 - 10
of 49
pro vyhledávání: '"Arabzadeh, Negar"'
Text-to-Image (TTI) systems often support people during ideation, the early stages of a creative process when exposure to a broad set of relevant images can help explore the design space. Since ideation is an important subclass of TTI tasks, understa
Externí odkaz:
http://arxiv.org/abs/2410.17331
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
Autor:
Arabzadeh, Negar, Huo, Siqing, Mehta, Nikhil, Wu, Qinqyun, Wang, Chi, Awadallah, Ahmed, Clarke, Charles L. A., Kiseleva, Julia
The rapid development of Large Language Models (LLMs) has led to a surge in applications that facilitate collaboration among multiple agents, assisting humans in their daily tasks. However, a significant gap remains in assessing to what extent LLM-po
Externí odkaz:
http://arxiv.org/abs/2405.02178
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
Information retrieval systems increasingly incorporate generative components. For example, in a retrieval augmented generation (RAG) system, a retrieval component might provide a source of ground truth, while a generative component summarizes and aug
Externí odkaz:
http://arxiv.org/abs/2404.04044
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
Autor:
Arabzadeh, Negar, Kiseleva, Julia, Wu, Qingyun, Wang, Chi, Awadallah, Ahmed, Dibia, Victor, Fourney, Adam, Clarke, Charles
The rapid development in the field of Large Language Models (LLMs) has led to a surge in applications that facilitate collaboration among multiple agents to assist humans in their daily tasks. However, a significant gap remains in assessing whether L
Externí odkaz:
http://arxiv.org/abs/2402.09015
The rapid advancement of natural language processing, information retrieval (IR), computer vision, and other technologies has presented significant challenges in evaluating the performance of these systems. One of the main challenges is the scarcity
Externí odkaz:
http://arxiv.org/abs/2401.17543
Large language models can now directly generate answers to many factual questions without referencing external sources. Unfortunately, relatively little attention has been paid to methods for evaluating the quality and correctness of these answers, f
Externí odkaz:
http://arxiv.org/abs/2401.04842