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Maximizing utility in multi-agent environments by anticipating the

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

Condensed Matter

https://arxiv.org/list/cond-mat/new
The mixed anomaly between these is accommodated by the not-on-site action of the symmetries

Mitigating Distribution Shift in Stock Price Data via Return-Volatility

https://arxiv.org/html/2508.20108v2
Extensive experiments on real-world datasets demonstrate that ReVol enhances the performance of the state-of-the-art backbone models in most cases, achieving an average improvement of more than 0

Report GitHub Issue

https://arxiv.org/html/2608.02942v1
Diffusion language models (dLLMs) generate text by iteratively replacing masked positions with predicted tokens (Nie et al

Stochastic Choice with Advertising

https://arxiv.org/html/2608.03504v1
com/wp-content/uploads/2025/04/IAB_PwC-Internet-Ad-Revenue-Report-Full-Year-2024

Existence of Richter–Peleg representation for general preferences

https://arxiv.org/html/2508.08980v3
111Majumdar and Sen (1976) work with an asymmetric relation PP

Raising Rivals’ Costs on Hybrid Platforms: The Complementarity of Fees

https://arxiv.org/html/2608.02800v1
com in China, Walmart Marketplace and Target Plus in the United States, Otto in Germany, Flipkart in India, and Rakuten in Japan

A Heterogeneous Spatiotemporal GARCH Model: A Predictive Framework for

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

[2608.03883] DS@GT-ARC at eRisk 2026 Task 3: Sparse, Semantic, and LLM

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

[2104.08663] BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of

https://arxiv.org/abs/2104.08663
We leverage a careful selection of 18 publicly available datasets from diverse text retrieval tasks and domains and evaluate 10 state-of-the-art retrieval systems including lexical, sparse, dense, late-interaction and re-ranking architectures on the BEIR benchmark

[2608.03860] SciRet: A Compute-Aware Empirical Study of Retrieval and

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

Mathematical Finance Apr 2021

https://arxiv.org/list/q-fin.MF/2021-04
A lacuna in the proof of the old Lemma 3

Asymptotic Equivalence of Immediate and Deferred Acceptance

https://arxiv.org/html/2607.24970v2
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 arXiv Why HTML? Report Issue Back to

Stabilization of First-Order Partial Integro-Differential Equations with

https://arxiv.org/html/2608.02851v1
Concurrent Input and State Delays 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 arXiv

Microstructural Foundations of Rough Noise1footnote

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

Machine Learning Dec 2022

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

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of

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

[2203.08771] Searches for Baryon Number Violation in Neutrino

https://arxiv.org/abs/2203.08771
Dev and 37 other authors View PDF HTML (experimental) Abstract:Baryon number conservation is not guaranteed by any fundamental symmetry within the Standard Model, and therefore has been a subject of experimental and theoretical scrutiny for decades

Bandwidth-Free Inference for Recursive Nonlinear Impulse Response

https://arxiv.org/html/2608.02943v1
Functions 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 arXiv Why HTML? Report Issue

Information Theory

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

Learning Equilibrium with Estimated Payoffs in Population Games

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

Finite-Time Analysis of Asynchronous Multi-Agent TD Learning

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]

1 Introduction

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

Information Retrieval

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

Computational Geometry

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 $1+\varepsilon$

Information Retrieval

https://arxiv.org/list/cs.IR/new
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Data Structures and Algorithms

https://arxiv.org/list/cs.DS/new
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Hardware Architecture

https://arxiv.org/list/cs.AR/new
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Systems and Control

https://arxiv.org/list/cs.SY/new
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Cryptography and Security

https://arxiv.org/list/cs.CR/new
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