Towards a Search Engine for Machines: Unified Ranking for Multiple Retrieval-Augmented Large Language Models
- Award ID(s):
- 2143434
- PAR ID:
- 10580776
- Publisher / Repository:
- Proceedings of The 47th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2024)
- Date Published:
- ISBN:
- 9798400704314
- Page Range / eLocation ID:
- 741 to 751
- Format(s):
- Medium: X
- Location:
- Washington DC USA
- Sponsoring Org:
- National Science Foundation
More Like this
-
Beyersdorff, Olaf; Kanté, Mamadou Moustapha; Kupferman, Orna; Lokshtanov, Daniel (Ed.)Given a set P of n points and a set S of n segments in the plane, we consider the problem of computing for each segment of S its closest point in P. The previously best algorithm solves the problem in n^{4/3}2^{O(log^*n)} time [Bespamyatnikh, 2003] and a lower bound (under a somewhat restricted model) Ω(n^{4/3}) has also been proved. In this paper, we present an O(n^{4/3}) time algorithm and thus solve the problem optimally (under the restricted model). In addition, we also present data structures for solving the online version of the problem, i.e., given a query segment (or a line as a special case), find its closest point in P. Our new results improve the previous work.more » « less
An official website of the United States government

