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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.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/list/q-fin.MF/2021-04
A lacuna in the proof of the old Lemma 3
https://arxiv.org/list/cs.DS/new
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Data Structures and Algorithms
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https://arxiv.org/list/cs.AR/new
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Hardware Architecture
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Systems and Control
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https://arxiv.org/list/cs.DB/new
DB)
Large language models have made natural language interfaces to databases (NLIDB) newly credible, but LLM text-to-SQL systems fail in a way that matters for deployment: a hallucinated column or a mis-aggregated total yields a fluent wrong answer, indistinguishable at the point of use from a right one
https://arxiv.org/list/cs.CR/new
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Cryptography and Security
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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/list/cs.PF/new
In response, we see several efforts to tackle CSP in various stages of the Collect-Transmit-Store-Analyze data lifecycle; such as approximate query processing in databases or sketches in network routers
https://arxiv.org/archive/cs.AI
Recognition Computers and Society Databases Distributed, Parallel, and Cluster Computing Digital Libraries Discrete Mathematics Data Structures and Algorithms Emerging Technologies Formal Languages and Automata Theory General Literature Graphics Computer Science and Game Theory Human-Computer Interaction Information
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/list/cs.LG/2022-11
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Machine Learning
Authors and titles for November 2022
Total of 2761 entries : 1
https://arxiv.org/list/cs.DC/2020-06
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Distributed, Parallel, and Cluster Computing
Authors and titles for June 2020
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/list/cs.DC/new
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https://arxiv.org/pdf/1811.12628
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https://arxiv.org/html/2407.18010v2
1 Introduction
2 Formulation
3 Existence of a Value and Saddle Point Equilibrium
4 Learning in Unknown Environments
4.1 Convergence using Linear Function Approximators
5 Intervention Budget Constraints
6 Discussion on Subcases
7 Related
https://arxiv.org/html/2407.05763v1
1 Introduction
2 Preliminaries
2.1 Graph Theory
2.2 Generalized Homogeneity
3 Problem Statement
4 Basic Idea of the Observer Design
5 Homogeneous Observer Design
5.1 Globally Homogeneous Distributed Observer
5.2 Locally Homogeneous