Web This site Trusted
30 result(s) for “okapi bm25 site terms com pp site github com site lemma world site map directory site:arxiv.org” of 62 matched · page 2 · 844 ms
Scope: Nishi’s own index (our crawl + Common Crawl) — not the whole live web. Some sites block all automated crawlers (anti-bot walls), so their pages may be absent here even though we never filter lawful content.
Did you mean okapi bm25 site terms com pp site github com site lemmy world site map directory site:arxiv.org?
Freshness: no result on this page carries a fetch time yet (indexed before the fetch epoch was stored beside the doc)
https://arxiv.org/html/2608.03504v1
com/wp-content/uploads/2025/04/IAB_PwC-Internet-Ad-Revenue-Report-Full-Year-2024
https://arxiv.org/html/2508.08980v3
111Majumdar and Sen (1976) work with an asymmetric relation PP
https://arxiv.org/html/2607.24970v2
Although IA is Pareto-efficient and DA is not, conditional on truth-telling, we do not know how much better IA’s placement is in quantitative terms
https://arxiv.org/html/2608.02851v1
The design relies on two affine Volterra transformations involving both Fredholm- and Volterra-type integral terms, which results in a four-PIDE kernel equations
https://arxiv.org/html/2508.20101v1
The model combines classical GARCH(pp, qq) dynamics with spatially correlated innovations and spatially varying parameters, estimated using local likelihood methods
https://arxiv.org/list/cs.LG/2022-12
Skip to main content
System maintenance August 4th and 5th Learn more ×
Search Submit Donate Log in
Search arXiv
Press Enter to search · Advanced search
Machine Learning
Authors and titles for December 2022
Total of 2004 entries : 1
https://arxiv.org/list/cs.IT/new
The physical world is not changed by a reconfiguration of the observer, but its complex representation in the observation world is
https://arxiv.org/list/cs.CG/new
PR)
The Johnson--Lindenstrauss lemma asserts that every set of $n$ points in $d$-dimensional Euclidean space embeds into $O(\varepsilon^{-2}\log n)$-dimensional Euclidean space with distortion at most $1+\varepsilon$
https://arxiv.org/html/2608.02942v1
×
Title:
Content selection saved. Describe the issue below:
Description:
Submit without GitHub Submit in GitHub
arXiv is now an independent nonprofit! Learn more ×
Back to arXiv
Why HTML? Report Issue Back to Abstract Download PDF
https://arxiv.org/html/2607.29442v2
1footnoteFootnotefootnotesFootnotes1footnote 1We are grateful to Carsten Chong for fruitful discussions on rough noise. We benefitted from comments by and discussions with Kim Christensen, Mikko Pakkanen, Bent Jesper Christensen, and Mikkel
https://arxiv.org/html/2608.03573v1
Multi-Task Learning Paradigms for LLMs
Report GitHub Issue
×
Title:
Content selection saved. Describe the issue below:
Description:
Submit without GitHub Submit in GitHub
arXiv is now an independent nonprofit! Learn more ×
Back to
https://arxiv.org/html/2407.00419v1
nl
Abstract
Artificially intelligent agents deployed in the real-world will require the ability to reliably cooperate with humans (as well as other, heterogeneous AI agents)
https://arxiv.org/html/2407.08254v2
Results suggest that, in the presence of frequent failures, our solution improves substantially over the best existing approaches in terms of global utility and scalability
https://arxiv.org/html/2407.20441v1
However, in real-world multi-agent systems, inter-node communication imposes strong constraints, such as limited link capacity and transmission delays [4, 5, 6]
https://arxiv.org/html/2407.15077v2
2 Problem Definition
3 Method
3.1 Monotonic Improvement of B2MAPO scheme
3.2 B2MAPO Framework
3.2.1 Batch Sequence Generation Layer
3.2.2 Batch by Batch Policy Optimization Layer
4 DAG-based B2MAPO Algorithm
4.1 Hierarchical DAG
https://arxiv.org/abs/2608.03883
Our systems combine sparse BM25 retrieval, evidence-aware rescoring for self-referential symptom reports, embedding-based reranking, query-prototype expansion, and LLM-based reranking
https://arxiv.org/abs/2104.08663
Our results show BM25 is a robust baseline and re-ranking and late-interaction-based models on average achieve the best zero-shot performances, however, at high computational costs
https://arxiv.org/abs/2608.03860
The pipeline combines sentence-window chunking, BM25, BGE-M3 dense retrieval, reciprocal rank fusion, optional cross-encoder reranking, and grounded answer generation
https://arxiv.org/list/cs.IR/recent
Skip to main content
System maintenance August 4th and 5th Learn more ×
Search Submit Donate Log in
Search arXiv
Press Enter to search · Advanced search
Information Retrieval
Authors and titles for recent submissions
Wed, 5 Aug 2026
https://arxiv.org/list/cs.IR/new
Skip to main content
System maintenance August 4th and 5th Learn more ×
Search Submit Donate Log in
Search arXiv
Press Enter to search · Advanced search
Information Retrieval
New submissions
Cross-lists
Replacements
See recent
https://arxiv.org/list/q-fin.MF/2021-04
A lacuna in the proof of the old Lemma 3
https://arxiv.org/list/cs.DS/new
Skip to main content Search Submit Donate Log in
Search arXiv
Press Enter to search · Advanced search
Data Structures and Algorithms
New submissions
Cross-lists
Replacements
See recent articles
Showing new listings for Monday, 17 August
https://arxiv.org/list/cs.AR/new
Skip to main content Search Submit Donate Log in
Search arXiv
Press Enter to search · Advanced search
Hardware Architecture
New submissions
Cross-lists
Replacements
See recent articles
Showing new listings for Monday, 17 August 2026
https://arxiv.org/list/cs.SY/new
Skip to main content Search Submit Donate Log in
Search arXiv
Press Enter to search · Advanced search
Systems and Control
New submissions
Cross-lists
Replacements
See recent articles
Showing new listings for Monday, 17 August 2026
Total
https://arxiv.org/list/cs.CR/new
Skip to main content Search Submit Donate Log in
Search arXiv
Press Enter to search · Advanced search
Cryptography and Security
New submissions
Cross-lists
Replacements
See recent articles
Showing new listings for Friday, 7 August 2026
https://arxiv.org/html/2407.06328v2
I Introduction
II Preliminaries and Problem Description
II-A Task Allocation Game Model
II-B Learning Rule, Stochastic Alarm Clock, and Evolutionary Dynamics Model
II-C Payoff Vector Estimation
III Convergence Analysis and Revision Rate
https://arxiv.org/html/2309.08431v3
Finance and Automated Market Making: Predictable Loss and Optimal Liquidity Provision
1 Introduction
2 Constant function markets and concentrated liquidity
2.1 Constant function markets
2.2 Concentrated liquidity markets
3 The wealth of
https://arxiv.org/html/2407.20187v1
1 Introduction
1.1 The Illusion Elimination Problem
1.2 Our Contributions.
1.3 Related Work.
2 Preliminaries
3 Majority Illusion Addition Elimination (MIAE)
3.1 A First Attempt
3.2 A Second Attempt
3.3 A TDI System
3.4 A Polynomial Time
https://arxiv.org/html/2407.04889v1
behavior of other learners
1 Introduction
Setting.
Zero-sum games.
General-sum games.
1.1 Preliminaries
1.2 Algorithms for the learner
1.3 Our results
1.3.1 Zero sum games
Continuous-time games.
Discrete-time games.
1.3.2 A lower bound
https://arxiv.org/pdf/1811.12628
ioAJyU# LFg¡C}zO7tXW,۽ݭDZbn; ] ,= h粂7'6m.>tv }u/|8 pqMP7f3E( )ֽa\dYD3,V:A3 K+r :t4!4}wLod#౭6?q2UdQL %ʔc7_Vo1qo