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Computer Science Preprint PDF DOI

Computing Equilibrium beyond Unilateral Deviation

Mingyang Liu, Gabriele Farina, Asuman Ozdaglar · 2026

Most familiar equilibrium concepts, such as Nash and correlated equilibrium, guarantee only that no single player can improve their utility by deviating unilaterally. They offer no guarantees against …

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AI & Data Science Preprint PDF DOI

PRISM: Pre-alignment via Black-box On-policy Distillation for Multimodal Reinforcement Learning

Sudong Wang, Weiquan Huang, Xiaomin Yu, Zuhao Yang, Hehai Lin, Keming Wu, Chaojun Xiao, Chen Chen, Wenxuan Wang, Beier Zhu, Yunjian Zhang, Chengwei Qin · 2026

The standard post-training recipe for large multimodal models (LMMs) applies supervised fine-tuning (SFT) on curated demonstrations followed by reinforcement learning with verifiable rewards (RLVR). H…

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AI & Data Science Preprint PDF DOI

Stable Behavior, Limited Variation: Persona Validity in LLM Agents for Urban Sentiment Perception

Neemias B da Silva, Rodrigo Minetto, Daniel Silver, Thiago H Silva · 2026

Large Language Models (LLMs) are increasingly used as proxies for human perception in urban analysis, yet it remains unclear whether persona prompting produces meaningful and reproducible behavioral d…

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AI & Data Science Preprint PDF DOI

ResiHMR: Residual-Limb Aware Single-Image 3D Human Mesh Recovery for Individuals with Limb Loss

Jiaying Ying, Heming Du, Kaihao Zhang, Sean M. Tweedy, Xin Yu · 2026

Single-image human mesh recovery provides a compact 3D, person-centric representation that supports analysis, animation, AR and VR, rehabilitation, and human-computer interaction. However, prevailing …

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AI & Data Science Preprint PDF DOI

Knowledge Graph Representations for LLM-Based Policy Compliance Reasoning

Wilder Baldwin, Sepideh Ghanavati · 2026

The risks posed by AI features are increasing as they are rapidly integrated into software applications. In response, regulations and standards for safe and secure AI have been proposed. In this paper…

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Mathematics Preprint PDF DOI

The Bernstein-von Mises theorem for Bayesian one-pass online learning

Jeyong Lee, Junhyeok Choi, Dongguen Kim, Minwoo Chae · 2026

Bayesian online learning provides a coherent framework for sequential inference. However, its theoretical understanding remains limited, particularly in the one-pass setting. Existing theoretical guar…

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Physics Preprint PDF DOI

A benchmark for binary star interaction with a supermassive black hole in general relativity

Megha Sharma, Alexander Heger, Daniel J. Price, Emilio Tejeda, Evgeni Grishin, Luis A. Manzaneda, Alessandro A. Trani · 2026

Most galaxies have supermassive black holes (SMBH) at their centres, surrounded by stars with binary systems also present in this environment. We use two schemes - post-Newtonian (PN) and a scalar per…

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Mathematics Preprint PDF DOI

A Shifted Cohesive-Zone Method for Non-Interface-Fitted Meshes with Applications to Crystal Plasticity

Cheng-Hau Yang, Mark C. Messner, Tianchen Hu · 2026

The accurate simulation of interface-dominated solid mechanics problems on complex microstructures remains challenging, particularly when interface-fitted quadrilateral or hexahedral meshes are diffic…

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Computer Science Preprint PDF DOI

NuggetIndex: Governed Atomic Retrieval for Maintainable RAG

Saber Zerhoudi, Michael Granitzer, Jelena Mitrovic · 2026

Retrieval-augmented generation (RAG) systems are frequently evaluated via fact-based metrics, yet standard implementations retrieve passages or static propositions. This unit mismatch between evaluati…

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Computer Science Preprint PDF DOI

To Diff or Not to Diff? Structure-Aware and Adaptive Output Formats for Efficient LLM-based Code Editing

Wei Cheng, Yongchang Cao, Chen Shen, Binhua Li, Jue Chen, Yongbin Li, Wei Hu · 2026

Large Language Models (LLMs) are increasingly used for code editing, yet the prevalent full-code generation paradigm suffers from severe efficiency bottlenecks, posing challenges for interactive codin…

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AI & Data Science Preprint PDF DOI

Instruction Complexity Induces Positional Collapse in Adversarial LLM Evaluation

Jon-Paul Cacioli · 2026

When instructed to underperform on multiple-choice evaluations, do language models engage with question content or fall back on positional shortcuts? We map the boundary between these regimes using a …

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AI & Data Science Preprint PDF DOI

How to Guide Your Flow: Few-Step Alignment via Flow Map Reward Guidance

Jerry Y. Huang, Justin Lin, Sheel Shah, Kartik Nair, Nicholas M. Boffi · 2026

In generative modeling, we often wish to produce samples that maximize a user-specified reward such as aesthetic quality or alignment with human preferences, a problem known as guidance. Despite their…

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Computer Science Preprint PDF DOI

Improved Approximation Algorithm for Maximum Balanced Biclique

Pasin Manurangsi · 2026

We study the Maximum Balanced Biclique (MBB) problem: Given a bipartite graph $G$ with $n$ vertices on each side, find a balanced biclique in $G$ with maximum size. We give a polynomial-time $\left(\f…

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Physics Preprint PDF DOI

On matrix Lax representations for (1+1)-dimensional evolutionary differential-difference equations

Sergei Igonin · 2026

Differential-difference matrix Lax representations (Lax pairs), gauge transformations, and discrete Miura-type transformations (MTs) belong to the main tools in the theory of (nonlinear) integrable di…

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Mathematics Preprint PDF DOI

Function-free Optimization via Comparison Oracles

Katya Scheinberg, Zikai Xiong · 2026

In this work, we study optimization specified only through a comparison oracle: given two points, it reports which one is preferred. We call it function-free optimization because we do not assume acce…

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Economics & Finance Preprint PDF DOI

Doubly robust local projections difference-in-differences

Daniel de Abreu Pereira Uhr, Guilherme Valle Moura · 2026

This paper develops a doubly robust extension of local-projections difference-in-differences (LP-DiD) for staggered absorbing treatments. The resulting estimator, DRLPDID, preserves the LP-DiD local-s…

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AI & Data Science Preprint PDF DOI

Random Cloud: Finding Minimal Neural Architectures Without Training

Javier Gil Blazquez · 2026

I propose the \emph{Random Cloud} method, a training-free approach to neural architecture search that discovers minimal feedforward network topologies through stochastic exploration and progressive st…

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AI & Data Science Preprint PDF DOI

A Multi-Dataset Benchmark of Multiple Instance Learning for 3D Neuroimage Classification

Ethan Harvey, Dennis Johan Loevlie, Amir Ali Satani, Wansu Chen, David M. Kent, Michael C. Hughes · 2026

Despite being resource-intensive to train, 3D convolutional neural networks (CNNs) have been the standard approach to classify CT and MRI scans. Recent work suggests that deep multiple instance learni…

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AI & Data Science Preprint PDF DOI

Laplace Approximation for Bayesian Tensor Network Kernel Machines

Albert Saiapin, Kim Batselier · 2026

Uncertainty estimation is essential for robust decision-making in the presence of ambiguous or out-of-distribution inputs. Gaussian Processes (GPs) are classical kernel-based models that offer princip…

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Computer Science Preprint PDF DOI

FACT: Compositional Kernel Synthesis with a Three-Stage Agentic Workflow

Sina Heidari, Dimitrios S. Nikolopoulos · 2026

Deep learning compilers and vendor libraries deliver strong baseline performance but are bounded by finite, engineer-curated catalogs. When these omit needed optimizations, practitioners substitute ha…

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