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Finance-Informed Neural Network: Learning the Geometry of Option Pricing

https://arxiv.org/html/2412.12213v2
Importantly, FINN extends beyond liquid option markets: it can be trained directly on historical spot prices to construct coherent option prices and Greeks for assets with no listed options

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https://arxiv.org/pdf/2607.27188v1
) /Title (Inverse Learning of Latent Risk-Neutral Densities from Irregular Option Quotes) /Trapped /False /arXivID (https://arxiv

%PDF-1.7 %¿÷¢þ 1 0 obj > >> endobj 2 0 obj Surveys and overviews.

https://arxiv.org/pdf/2407.00125
) /Title (A Survey on Failure Analysis and Fault Injection in AI Systems) /Trapped /False /arXivID (https://arxiv

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https://arxiv.org/pdf/2508.11152
com three Proceedings of ACM Conference (Conference'17) book 1 1 9 9 Tianjiao ZhaoJingrao LyuStokes JonesHarrison GarberStefano PasqualiDhagash Mehtahttp://arxiv

Information Retrieval

https://arxiv.org/list/cs.IR/new
However, skills are naturally structured, multi-field objects, where each field provides different information about when and how the skill should be used

1 Introduction

https://arxiv.org/html/2407.16741v3
com/All-Hands-AI/OpenHands Slack http://bit

Probing Character-level Transformers for the Spanish L-shaped Morphome

https://arxiv.org/html/2608.03452v1
Can such a complex pattern be learned from exposure to inflected forms alone

Inverse Learning of Latent Risk-Neutral Densities from Irregular Option

https://arxiv.org/html/2607.27188v1
5 Real NIFTY data: adaptation helps but does not close the gap 6 Discussion 6

Every Wrong Answer Counts: Option-Level Psychometrics for LLM Multiple

https://arxiv.org/html/2608.02966v1
(c) Because these distractor preferences vary with ability, their identities provide Fisher information that correctness does not retain

Activation-Guided Neuron Intervention to Induce Alzheimer’s-Related

https://arxiv.org/html/2608.03067v1
Unlike many biological markers, speech and language can be sampled repeatedly, remotely, and at relatively low cost, making them promising digital markers (Robin et al

MDGAM-Based Cooperative Task Scheduling for Communication-Constrained

https://arxiv.org/html/2608.00648v1
The framework is suitable for a broad range of distributed task-planning applications and can be flexibly transferred to related scenarios with different practical constraints and settings

Report GitHub Issue

https://arxiv.org/html/2609.03027v1
Report GitHub Issue Description: arXiv is now an independent nonprofit

Herding, Momentum, and Reversal in China’s A-Share Market: An Agent

https://arxiv.org/html/2607.27063v1
A separate information process updates investor beliefs through a finite-speed diffusion mechanism, allowing informational adjustment to be distinguished from behavioral imitation

Train Often, Deploy Selectively: Forward-Gated Model Replacement in

https://arxiv.org/html/2607.28577v1
org perpetual non-exclusive license arXiv:2607

Report GitHub Issue

https://arxiv.org/html/2608.03358v1
org perpetual non-exclusive license arXiv:2608

Multi-agent Off-policy Actor-Critic Reinforcement Learning for Partially

https://arxiv.org/html/2407.04974v1
Unlike many existing dec-POMDP-based RL approaches, the proposed algorithm is suitable for model-free multi-agent reinforcement learning as it does not require knowledge of a transition model

Optimal Execution with Passive Market Impact

https://arxiv.org/html/2607.28323v1
Passive execution is often introduced through a fill intensity term: a limit order posted farther from the midprice earns a better price conditional on execution but is less likely to be filled

Efficient Multilingual Neural Machine Translation via Corpus-Driven

https://arxiv.org/html/2608.03480v1
com Arabic Institute for Translation, Algiers, Algeria CERIST, Algeria Nasredine Semmar CEA LIST, Paris-Saclay, France Hassina Aliane CERIST, Algeria Abstract The adoption of large pre-trained multilingual models for neural machine translation (MNMT) faces a major challenge: excessive memory and computational

Optimizing Age of Information in Vehicular Edge Computing with Federated

https://arxiv.org/html/2407.02342v1
com/qiongwu86/Optimizing-AoI-in-VEC-with-Federated-Graph-Neural-Network-Multi-Agent-Reinforcement-Learnin

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https://arxiv.org/pdf/2607.27070v1
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https://arxiv.org/pdf/2608.02758
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https://arxiv.org/pdf/2005.14165
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https://arxiv.org/pdf/2402.03300
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https://arxiv.org/pdf/2608.03118
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https://arxiv.org/pdf/2407.02510
JäŒX¦H…¯'¿>ø4EQM—/j4úÁ~ �è–÷zçß}ÿ•¯é7O_ýå}jîvÞ. “»§—;“iîÒ(òüÝÝSq÷¼9�C>Tm“×÷±mÊû Þü~.›¾ì…3™÷†œÙTÍеÅx(=)ýg;äûúí>‰7ÛK}&úê4ÖÜùýç§¿Ó�‚ÀÛʼn|¸ÏïCó[Õ¼Þ?˜ Øte^Wÿ+ Éíß$åÎ@üðñéGPþ&‡¶lmQvZ§�z8…Ì%Ùe^üõÕÇcùø¡Å”~ÃOÙå¯ô�0N7uyZn V²©z) "ÉçM!

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https://arxiv.org/src/2006.01048
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https://arxiv.org/src/2303.12712
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https://arxiv.org/pdf/2006.04122
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Coordinated Primary Frequency Regulation and Grid-Forming Control for

https://arxiv.org/html/2608.02813v1
Existing approaches can be broadly classified into trajectory-based [6] and feedback-based methods [7]

Consensus Measures for Unstructured Biomedical Text Annotations

https://arxiv.org/html/2608.03529v1
Synthetic experiments show that soft reliability can be quantified using a variety of semantic equivalence measures, and that the choice of measure affects failure modes of the estimation