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The Lean 4 kernel establishes proof soundness, but, as Section 3 notes, it does not establish that the formal statement is the one the researcher meant to prove: the kernel accepts a theorem whose hypotheses are contradictory, a definition that unfolds to True, or a lemma asserted as an axiom in place of a proof
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https://arxiv.org/html/2607.22511v2
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https://arxiv.org/html/2608.03452v1
These models and human speakers also make opposite errors, the models apply the alternation to verbs where it does not belong, whereas speakers apply it less often than the pattern would license (Kakolu Ramarao et al
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
https://arxiv.org/html/2607.28847v1
3 Research Question 1: Does Masked Inequality Exist
https://arxiv.org/html/2407.00575v3
Gradient play converges to a unique Nash equilibrium (NE) that does not optimize the global objective
https://arxiv.org/html/2508.08980v3
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https://arxiv.org/html/2608.02943v1
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https://arxiv.org/html/2604.05327v4
This version:
I would like to thank Xu Cheng, Frank Diebold, Wayne Gao, George Mailath, and seminar participants at Chicago Booth, Paris Econometrics Seminar, Toulouse School of Economics, and the University of Pennsylvania for valuable discussions and comments that substantially improved this article
https://arxiv.org/html/2608.03703v1
begun on July 20, 2026; the present version is dated August 4, 2026. Claude Opus 5 and Fable 5 provided research assistance throughout, spanning code development, data construction and empirical analysis, and the drafting of the manuscript.
https://arxiv.org/html/2608.02909v1
This approach is theoretically valid, easy to implement, and does not require new data
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/2607.27099v1
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https://arxiv.org/html/2309.08431v3
Existing research characterises the losses of LPs, but does not offer tools for strategic liquidity provision
https://arxiv.org/pdf/1811.12628
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A core calculus gives an effect-confinement lemma and six safety properties
https://arxiv.org/html/2205.01882v5
2 Details of the DVD Dataset
M Additional Empirical Application: Fishing-site Choice
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https://arxiv.org/html/2508.20108v2
, 2023) reduces the distribution difference; however, it does not fully align the distributions
https://arxiv.org/html/2407.10811v1
Recently, employing reinforcement learning (RL) to solve TSC has become a research hotspot since it does not require too much artificial priori and can improve performance significantly through the paradigm of trial and error
https://arxiv.org/pdf/2006.02318
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The mixed anomaly between these is accommodated by the not-on-site action of the symmetries
https://arxiv.org/html/2608.02609v1
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https://arxiv.org/html/2607.26405v1
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https://arxiv.org/html/2407.18010v2
Since acting at each available opportunity would accumulate prohibitively large costs, the resulting decision problem is one in which players must make strategic decisions about when to execute actions in addition to their choice of action
https://arxiv.org/html/2608.03504v1
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https://arxiv.org/pdf/2608.02122
) /Title (DEFT: Joint Task Placement and DVFS for Energy-Efficient Multi-GPU Runtimes) /Trapped /False /arXivID (https://arxiv
https://arxiv.org/pdf/2608.01785
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