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3b5924fb4f5c2634173199ad01818be3721fbbcd64c0d0a1264ad9f63cb8965f
2026-01-01T00:00:00-05:00
Attribution-Guided Distillation of Matryoshka Sparse Autoencoders
arXiv:2512.24975v1 Announce Type: new Abstract: Sparse autoencoders (SAEs) aim to disentangle model activations into monosemantic, human-interpretable features. In practice, learned features are often redundant and vary across training runs and sparsity levels, which makes interpretations difficult to transfer and reus...
https://arxiv.org/abs/2512.24975
Academic Papers
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e07eb8132efae4650cfd797f759ffdedb316703c5d8196aa9e48ad0e43c4a752
2026-01-01T00:00:00-05:00
A Modal Logic for Possibilistic Reasoning with Fuzzy Formal Contexts
arXiv:2512.24980v1 Announce Type: new Abstract: We introduce a two-sort weighted modal logic for possibilistic reasoning with fuzzy formal contexts. The syntax of the logic includes two types of weighted modal operators corresponding to classical necessity ($\Box$) and sufficiency ($\boxminus$) modalities and its formu...
https://arxiv.org/abs/2512.24980
Academic Papers
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7d24bdc6008be802d94f8f5fcd0cd8b05d1e9f92f038c4fb88497002dd0dad24
2026-01-01T00:00:00-05:00
DarkEQA: Benchmarking Vision-Language Models for Embodied Question Answering in Low-Light Indoor Environments
arXiv:2512.24985v1 Announce Type: new Abstract: Vision Language Models (VLMs) are increasingly adopted as central reasoning modules for embodied agents. Existing benchmarks evaluate their capabilities under ideal, well-lit conditions, yet robust 24/7 operation demands performance under a wide range of visual degradatio...
https://arxiv.org/abs/2512.24985
Academic Papers
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4818d305a907e9c88b6c36daef0a782fc33258f859d9cec131ab2d69a5bd37d3
2026-01-01T00:00:00-05:00
PhysTalk: Language-driven Real-time Physics in 3D Gaussian Scenes
arXiv:2512.24986v1 Announce Type: new Abstract: Realistic visual simulations are omnipresent, yet their creation requires computing time, rendering, and expert animation knowledge. Open-vocabulary visual effects generation from text inputs emerges as a promising solution that can unlock immense creative potential. Howe...
https://arxiv.org/abs/2512.24986
Academic Papers
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42e32a87ec3a2a11fb0594cb788f7658656fac2c524fc77f3223ff82b753ab77
2026-01-01T00:00:00-05:00
Efficiently Estimating Data Efficiency for Language Model Fine-tuning
arXiv:2512.24991v1 Announce Type: new Abstract: While large language models (LLMs) demonstrate reasonable zero-shot capability across many downstream tasks, fine-tuning is a common practice to improve their performance. However, a task's data efficiency--i.e., the number of fine-tuning examples needed to achieve a desi...
https://arxiv.org/abs/2512.24991
Academic Papers
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312822a9a80c4ee3c587ec9abc6d60d66472fcbf3c8ee4dca5a8136b096d6c06
2026-01-01T00:00:00-05:00
Classifying long legal documents using short random chunks
arXiv:2512.24997v1 Announce Type: new Abstract: Classifying legal documents is a challenge, besides their specialized vocabulary, sometimes they can be very long. This means that feeding full documents to a Transformers-based models for classification might be impossible, expensive or slow. Thus, we present a legal doc...
https://arxiv.org/abs/2512.24997
Academic Papers
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54b72fe0f5cdd1cef37d8abb54abc9ee08165fc850995e6e524327d7bf287bb1
2026-01-01T00:00:00-05:00
Bi-C2R: Bidirectional Continual Compatible Representation for Re-indexing Free Lifelong Person Re-identification
arXiv:2512.25000v1 Announce Type: new Abstract: Lifelong person Re-IDentification (L-ReID) exploits sequentially collected data to continuously train and update a ReID model, focusing on the overall performance of all data. Its main challenge is to avoid the catastrophic forgetting problem of old knowledge while traini...
https://arxiv.org/abs/2512.25000
Academic Papers
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7eeb4020d026c5a615e3e89fa941378a80365e332d9f45613d4ae57864b49c48
2026-01-01T00:00:00-05:00
FoundationSLAM: Unleashing the Power of Depth Foundation Models for End-to-End Dense Visual SLAM
arXiv:2512.25008v1 Announce Type: new Abstract: We present FoundationSLAM, a learning-based monocular dense SLAM system that addresses the absence of geometric consistency in previous flow-based approaches for accurate and robust tracking and mapping. Our core idea is to bridge flow estimation with geometric reasoning ...
https://arxiv.org/abs/2512.25008
Academic Papers
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da6a3257702305b0324d3287400ed3737c3b3480767523dda92ab32f8b6dad70
2026-01-01T00:00:00-05:00
At the intersection of Numerical Analysis and Spectral Geometry
arXiv:2512.25012v1 Announce Type: new Abstract: How do the geometric properties of a domain impact the spectrum of an operator defined on it? How do we compute accurate and reliable approximations of these spectra? The former question is studied in spectral geometry, and the latter is a central concern in numerical ana...
https://arxiv.org/abs/2512.25012
Academic Papers
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2f802d2e644c9ea55362ee245d44e1b0f5de0d929ee2faac170568f786092eb3
2026-01-01T00:00:00-05:00
Diffusion Language Models are Provably Optimal Parallel Samplers
arXiv:2512.25014v1 Announce Type: new Abstract: Diffusion language models (DLMs) have emerged as a promising alternative to autoregressive models for faster inference via parallel token generation. We provide a rigorous foundation for this advantage by formalizing a model of parallel sampling and showing that DLMs augm...
https://arxiv.org/abs/2512.25014
Academic Papers
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3484aa3d42c69eabb03256e50c82879e4aef72ab7310430a5be56dc368bd3ee1
2026-01-01T00:00:00-05:00
MAMA-Memeia! Multi-Aspect Multi-Agent Collaboration for Depressive Symptoms Identification in Memes
arXiv:2512.25015v1 Announce Type: new Abstract: Over the past years, memes have evolved from being exclusively a medium of humorous exchanges to one that allows users to express a range of emotions freely and easily. With the ever-growing utilization of memes in expressing depressive sentiments, we conduct a study on i...
https://arxiv.org/abs/2512.25015
Academic Papers
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607cd77647ab5f4b3a98bb4ecc0871dcb8c3d99c1a6d1289ba652ad37138c53e
2026-01-01T00:00:00-05:00
Approximations for the Weighted Reversal, Transposition, and Indel Distance Problem with Intergenic Region Information
arXiv:2512.25016v1 Announce Type: new Abstract: Genome rearrangement distances are an established method in genome comparison. Works in this area may include various rearrangement operations representing large-scale mutations, gene orientation information, the number of nucleotides in intergenic regions, and weights re...
https://arxiv.org/abs/2512.25016
Academic Papers
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39bfdcf80141c823007cc76bec4d5ba4fd3503030b07f09e709c3d2aaeb27327
2026-01-01T00:00:00-05:00
Convergence of the generalization error for deep gradient flow methods for PDEs
arXiv:2512.25017v1 Announce Type: new Abstract: The aim of this article is to provide a firm mathematical foundation for the application of deep gradient flow methods (DGFMs) for the solution of (high-dimensional) partial differential equations (PDEs). We decompose the generalization error of DGFMs into an approximatio...
https://arxiv.org/abs/2512.25017
Academic Papers
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1bb390af364a438682e25baeba5a852b605bacf3f1830d2e95bd76974a20534b
2026-01-01T00:00:00-05:00
Approximation Algorithms for Fair Repetitive Scheduling
arXiv:2512.25020v1 Announce Type: new Abstract: We consider a recently introduced fair repetitive scheduling problem involving a set of clients, each asking for their associated job to be daily scheduled on a single machine across a finite planning horizon. The goal is to determine a job processing permutation for each...
https://arxiv.org/abs/2512.25020
Academic Papers
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3e4f44a4725f6e847b86b6f64b1616a4fb8edaed8e29f4f095b764e270ba3845
2026-01-01T00:00:00-05:00
ResponseRank: Data-Efficient Reward Modeling through Preference Strength Learning
arXiv:2512.25023v1 Announce Type: new Abstract: Binary choices, as often used for reinforcement learning from human feedback (RLHF), convey only the direction of a preference. A person may choose apples over oranges and bananas over grapes, but which preference is stronger? Strength is crucial for decision-making under...
https://arxiv.org/abs/2512.25023
Academic Papers
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ad7e973539a1df1ba8ce589a9127479e84bb61713dbe1697e9b2aed69279ed5a
2026-01-01T00:00:00-05:00
Modeling Language as a Sequence of Thoughts
arXiv:2512.25026v1 Announce Type: new Abstract: Transformer language models can generate strikingly natural text by modeling language as a sequence of tokens. Yet, by relying primarily on surface-level co-occurrence statistics, they fail to form globally consistent latent representations of entities and events, lack of...
https://arxiv.org/abs/2512.25026
Academic Papers
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298fb3b41e0d14979da8cb62f455e3fe553c524256184bb7a83d6952cca82eb7
2026-01-01T00:00:00-05:00
EF(X) Orientations: A Parameterized Complexity Perspective
arXiv:2512.25033v1 Announce Type: new Abstract: The concept of fair orientations in graphs was introduced by Christodoulou, Fiat, Koutsoupias, and Sgouritsa in 2023, naturally modeling fair division scenarios in which resources are only contested by neighbors. In this model, vertices represent agents and undirected edg...
https://arxiv.org/abs/2512.25033
Academic Papers
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9efdd867b9e4d18c74430c33464d3cb5fd69e3e4a4a681fa00cfcf49f1005b9d
2026-01-01T00:00:00-05:00
Generative Classifiers Avoid Shortcut Solutions
arXiv:2512.25034v1 Announce Type: new Abstract: Discriminative approaches to classification often learn shortcuts that hold in-distribution but fail even under minor distribution shift. This failure mode stems from an overreliance on features that are spuriously correlated with the label. We show that generative classi...
https://arxiv.org/abs/2512.25034
Academic Papers
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a288fc7af9051a19efa65ce0ebeae5340bbdf14bdcfa9f6f089f62c5a45f8dc8
2026-01-01T00:00:00-05:00
Thin Tree Verification is coNP-Complete
arXiv:2512.25043v1 Announce Type: new Abstract: An $\alpha$-thin tree $T$ of a graph $G$ is a spanning tree such that every cut of $G$ has at most an $\alpha$ proportion of its edges in $T$. The Thin Tree Conjecture proposes that there exists a function $f$ such that for any $\alpha > 0$, every $f(\alpha)$-edge-connect...
https://arxiv.org/abs/2512.25043
Academic Papers
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80414b772cc5aa4bca63d4f9bbc92dd6e358aec3fd7b8564acf4dcc510626073
2026-01-01T00:00:00-05:00
AdaGReS:Adaptive Greedy Context Selection via Redundancy-Aware Scoring for Token-Budgeted RAG
arXiv:2512.25052v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) is highly sensitive to the quality of selected context, yet standard top-k retrieval often returns redundant or near-duplicate chunks that waste token budget and degrade downstream generation. We present AdaGReS, a redundancy-aware con...
https://arxiv.org/abs/2512.25052
Academic Papers
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1241f689d205780985167d921a496ee8d370b9eb9e436cef6045b12cd7f19253
2026-01-01T00:00:00-05:00
Context-aware LLM-based AI Agents for Human-centered Energy Management Systems in Smart Buildings
arXiv:2512.25055v1 Announce Type: new Abstract: This study presents a conceptual framework and a prototype assessment for Large Language Model (LLM)-based Building Energy Management System (BEMS) AI agents to facilitate context-aware energy management in smart buildings through natural language interaction. The propose...
https://arxiv.org/abs/2512.25055
Academic Papers
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f1e67bcbc81a3eeff666c84970e5b7c2f9d20dde5bc4847136cd32fdae05f6d4
2026-01-01T00:00:00-05:00
Reliable and Resilient Collective Communication Library for LLM Training and Serving
arXiv:2512.25059v1 Announce Type: new Abstract: Modern ML training and inference now span tens to tens of thousands of GPUs, where network faults can waste 10--15\% of GPU hours due to slow recovery. Common network errors and link fluctuations trigger timeouts that often terminate entire jobs, forcing expensive checkpo...
https://arxiv.org/abs/2512.25059
Academic Papers
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af2ce11fa5fc65e1cab13a520e50974797d9b623f5fcbed7d018ca8b336d000f
2026-01-01T00:00:00-05:00
On the geometry and topology of representations: the manifolds of modular addition
arXiv:2512.25060v1 Announce Type: new Abstract: The Clock and Pizza interpretations, associated with architectures differing in either uniform or learnable attention, were introduced to argue that different architectural designs can yield distinct circuits for modular addition. In this work, we show that this is not th...
https://arxiv.org/abs/2512.25060
Academic Papers
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b9e060c090a6d070241e91d4c2f0ffc3851ac8160e6a35db548b161f8b49922b
2026-01-01T00:00:00-05:00
Many Minds from One Model: Bayesian Transformers for Population Intelligence
arXiv:2512.25063v1 Announce Type: new Abstract: Despite their scale and success, modern transformers are almost universally trained as single-minded systems: optimization produces one deterministic set of parameters, representing a single functional hypothesis about the data. Motivated by the idea that intelligence eme...
https://arxiv.org/abs/2512.25063
Academic Papers
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d3cd3a380254cc683050ac297eaba230c0e539bfa359fb008a005fe58d3f40a2
2026-01-01T00:00:00-05:00
Vulcan: Instance-Optimal Systems Heuristics Through LLM-Driven Search
arXiv:2512.25065v1 Announce Type: new Abstract: Resource-management tasks in modern operating and distributed systems continue to rely primarily on hand-designed heuristics for tasks such as scheduling, caching, or active queue management. Designing performant heuristics is an expensive, time-consuming process that we ...
https://arxiv.org/abs/2512.25065
Academic Papers
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a6243e8019ac57e06130ae83db868b3cc816857b1c888cb92648c174476d7d26
2026-01-01T00:00:00-05:00
From Inpainting to Editing: A Self-Bootstrapping Framework for Context-Rich Visual Dubbing
arXiv:2512.25066v1 Announce Type: new Abstract: Audio-driven visual dubbing aims to synchronize a video's lip movements with new speech, but is fundamentally challenged by the lack of ideal training data: paired videos where only a subject's lip movements differ while all other visual conditions are identical. Existing...
https://arxiv.org/abs/2512.25066
Academic Papers
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16cb296a71957f000610de099e6e133000fe9f5c1ef4264c25aeb168159ae42a
2026-01-01T00:00:00-05:00
FineTec: Fine-Grained Action Recognition Under Temporal Corruption via Skeleton Decomposition and Sequence Completion
arXiv:2512.25067v1 Announce Type: new Abstract: Recognizing fine-grained actions from temporally corrupted skeleton sequences remains a significant challenge, particularly in real-world scenarios where online pose estimation often yields substantial missing data. Existing methods often struggle to accurately recover te...
https://arxiv.org/abs/2512.25067
Academic Papers
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49d5b4d90c65ff7d4c79d6e30b8e8269c68843fe8617d6c8cafe3f277efc09b6
2026-01-01T00:00:00-05:00
Scaling Open-Ended Reasoning to Predict the Future
arXiv:2512.25070v1 Announce Type: new Abstract: High-stakes decision making involves reasoning under uncertainty about the future. In this work, we train language models to make predictions on open-ended forecasting questions. To scale up training data, we synthesize novel forecasting questions from global events repor...
https://arxiv.org/abs/2512.25070
Academic Papers
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e796d2065e19f91f659cfc241b002004c57b6facac1cf2cc007371865c7dd903
2026-01-01T00:00:00-05:00
Edit3r: Instant 3D Scene Editing from Sparse Unposed Images
arXiv:2512.25071v1 Announce Type: new Abstract: We present Edit3r, a feed-forward framework that reconstructs and edits 3D scenes in a single pass from unposed, view-inconsistent, instruction-edited images. Unlike prior methods requiring per-scene optimization, Edit3r directly predicts instruction-aligned 3D edits, ena...
https://arxiv.org/abs/2512.25071
Academic Papers
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ca5762cfa509890a6ea354f35b7926f1db6732a9cea1d22a78150301cc8a01c3
2026-01-01T00:00:00-05:00
Coordinated Humanoid Manipulation with Choice Policies
arXiv:2512.25072v1 Announce Type: new Abstract: Humanoid robots hold great promise for operating in human-centric environments, yet achieving robust whole-body coordination across the head, hands, and legs remains a major challenge. We present a system that combines a modular teleoperation interface with a scalable lea...
https://arxiv.org/abs/2512.25072
Academic Papers
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7e308d17cfb8122f23fdd0583550e6a366c17b3c6993da8b174be682f74d5a98
2026-01-01T00:00:00-05:00
GaMO: Geometry-aware Multi-view Diffusion Outpainting for Sparse-View 3D Reconstruction
arXiv:2512.25073v1 Announce Type: new Abstract: Recent advances in 3D reconstruction have achieved remarkable progress in high-quality scene capture from dense multi-view imagery, yet struggle when input views are limited. Various approaches, including regularization techniques, semantic priors, and geometric constrain...
https://arxiv.org/abs/2512.25073
Academic Papers
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c5b23fe82e18d6b1ed2a31764096238e709f7d9fcc4b5def69acb46e860977f5
2026-01-01T00:00:00-05:00
SpaceTimePilot: Generative Rendering of Dynamic Scenes Across Space and Time
arXiv:2512.25075v1 Announce Type: new Abstract: We present SpaceTimePilot, a video diffusion model that disentangles space and time for controllable generative rendering. Given a monocular video, SpaceTimePilot can independently alter the camera viewpoint and the motion sequence within the generative process, re-render...
https://arxiv.org/abs/2512.25075
Academic Papers
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f52b6a35bb1ba89c4ca044b0d7321216d770975371d6436e7b863e6225dffa6a
2026-01-01T00:00:00-05:00
On Good-for-MDPs Automata
arXiv:2202.07629v4 Announce Type: cross Abstract: Nondeterministic good-for-MDPs (GFM) automata are for MDP model checking and reinforcement learning what good-for-games (GFG) automata are for reactive synthesis: a more compact alternative to deterministic automata that displays nondeterminism, but only so much that it...
https://arxiv.org/abs/2202.07629
Academic Papers
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98a988bf461638ea84b2de935381665eb5bfcafa30f0d2ee820f4b90cc2c61d1
2026-01-01T00:00:00-05:00
Comparative Evaluation of Embedding Representations for Financial News Sentiment Analysis
arXiv:2512.13749v1 Announce Type: cross Abstract: Financial sentiment analysis enhances market understanding; however, standard natural language processing approaches encounter significant challenges when applied to small datasets. This study provides a comparative evaluation of embedding-based methods for financial ne...
https://arxiv.org/abs/2512.13749
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3ad0d2146738f0d73b65552083fe8dc1a208494fdbee463449bbe3aad6a23aca
2026-01-01T00:00:00-05:00
q3-MuPa: Quick, Quiet, Quantitative Multi-Parametric MRI using Physics-Informed Diffusion Models
arXiv:2512.23726v1 Announce Type: cross Abstract: The 3D fast silent multi-parametric mapping sequence with zero echo time (MuPa-ZTE) is a novel quantitative MRI (qMRI) acquisition that enables nearly silent scanning by using a 3D phyllotaxis sampling scheme. MuPa-ZTE improves patient comfort and motion robustness, and...
https://arxiv.org/abs/2512.23726
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99dc492e8e37fb08197cfd323b7fa03a8d5f8ea2aef43bf3f60a99e030ad362f
2026-01-01T00:00:00-05:00
Spike-Timing-Dependent Plasticity for Bernoulli Message Passing
arXiv:2512.23728v1 Announce Type: cross Abstract: Bayesian inference provides a principled framework for understanding brain function, while neural activity in the brain is inherently spike-based. This paper bridges these two perspectives by designing spiking neural networks that simulate Bayesian inference through mes...
https://arxiv.org/abs/2512.23728
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d3b3cfcce53fbac63dfe9cdeeb89505a82b110b002858d20db0b3448a57e59c6
2026-01-01T00:00:00-05:00
Leveraging Machine Learning for Early Detection of Lung Diseases
arXiv:2512.23757v1 Announce Type: cross Abstract: A combination of traditional image processing methods with advanced neural networks concretes a predictive and preventive healthcare paradigm. This study offers rapid, accurate, and non-invasive diagnostic solutions that can significantly impact patient outcomes, partic...
https://arxiv.org/abs/2512.23757
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968237e3aea93f607da4d23098bd4b031178a67101ab5c4820fdd5ac090cf2b2
2026-01-01T00:00:00-05:00
Stochastic Galerkin Method and Hierarchical Preconditioning for PDE-constrained Optimization
arXiv:2512.23804v1 Announce Type: cross Abstract: We develop efficient hierarchical preconditioners for optimal control problems governed by partial differential equations with uncertain coefficients. Adopting a discretize-then-optimize framework that integrates finite element discretization, stochastic Galerkin approx...
https://arxiv.org/abs/2512.23804
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112bbfaa7b47ec11a2969165caa447f80cfb7b1d2e7236596fcdbfd54354d9e7
2026-01-01T00:00:00-05:00
Fitted Q Evaluation Without Bellman Completeness via Stationary Weighting
arXiv:2512.23805v1 Announce Type: cross Abstract: Fitted Q-evaluation (FQE) is a central method for off-policy evaluation in reinforcement learning, but it generally requires Bellman completeness: that the hypothesis class is closed under the evaluation Bellman operator. This requirement is challenging because enlargin...
https://arxiv.org/abs/2512.23805
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9d9e9b3ce1c5a70fee12d67594564bf52cb4fb3277dcef2ff54ef23ad59cfcd9
2026-01-01T00:00:00-05:00
Syndrome aware mitigation of logical errors
arXiv:2512.23810v1 Announce Type: cross Abstract: Broad applications of quantum computers will require error correction (EC). However, quantum hardware roadmaps indicate that physical qubit numbers will remain limited in the foreseeable future, leading to residual logical errors that limit the size and accuracy of achi...
https://arxiv.org/abs/2512.23810
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d79226c46c6e4115d9b719f177b96ca880b4ac48e41d33fbeff2a652a531c012
2026-01-01T00:00:00-05:00
Quantum Error Mitigation with Attention Graph Transformers for Burgers Equation Solvers on NISQ Hardware
arXiv:2512.23817v1 Announce Type: cross Abstract: We present a hybrid quantum-classical framework augmented with learned error mitigation for solving the viscous Burgers equation on noisy intermediate-scale quantum (NISQ) hardware. Using the Cole-Hopf transformation, the nonlinear Burgers equation is mapped to a diffus...
https://arxiv.org/abs/2512.23817
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235f408ca37f448e76b4672a155f8c8ca3a7d29791fb2db62a14c6444ad93c37
2026-01-01T00:00:00-05:00
Energy-Tweedie: Score meets Score, Energy meets Energy
arXiv:2512.23818v1 Announce Type: cross Abstract: Denoising and score estimation have long been known to be linked via the classical Tweedie's formula. In this work, we first extend the latter to a wider range of distributions often called "energy models" and denoted elliptical distributions in this work. Next, we exam...
https://arxiv.org/abs/2512.23818
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dd132e7ff9109649c5e23991540f92413cabd132710c04ef0b13ada2bee92825
2026-01-01T00:00:00-05:00
The Flow-Limit of Reflect-Reflect-Relax: Existence, Stability, and Discrete-Time Behavior
arXiv:2512.23843v1 Announce Type: cross Abstract: We study the Reflect-Reflect-Relax (RRR) algorithm in its small-step (flow-limit) regime. In the smooth transversal setting, we show that the transverse dynamics form a hyperbolic sink, yielding exponential decay of a natural gap measure. Under uniform geometric assumpt...
https://arxiv.org/abs/2512.23843
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3a7516a76bf91aea120897ed42e50524fdfeeb02beb6f2e8704fc6ecbf7319e3
2026-01-01T00:00:00-05:00
A Test of Lookahead Bias in LLM Forecasts
arXiv:2512.23847v1 Announce Type: cross Abstract: We develop a statistical test to detect lookahead bias in economic forecasts generated by large language models (LLMs). Using state-of-the-art pre-training data detection techniques, we estimate the likelihood that a given prompt appeared in an LLM's training corpus, a ...
https://arxiv.org/abs/2512.23847
Academic Papers
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cd90eaadb33616dee96ed7ba875c3eb57bb8ccccb97cfe35e70ba6fa05471e3f
2026-01-01T00:00:00-05:00
Autoregressive long-horizon prediction of plasma edge dynamics
arXiv:2512.23884v1 Announce Type: cross Abstract: Accurate modeling of scrape-off layer (SOL) and divertor-edge dynamics is vital for designing plasma-facing components in fusion devices. High-fidelity edge fluid/neutral codes such as SOLPS-ITER capture SOL physics with high accuracy, but their computational cost limit...
https://arxiv.org/abs/2512.23884
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bb040399f5bd7e8c66abdbd6d3f052af75a0a506e8cd130f4e75393446889050
2026-01-01T00:00:00-05:00
A multimodal Transformer for InSAR-based ground deformation forecasting with cross-site generalization across Europe
arXiv:2512.23906v1 Announce Type: cross Abstract: Near-real-time regional-scale monitoring of ground deformation is increasingly required to support urban planning, critical infrastructure management, and natural hazard mitigation. While Interferometric Synthetic Aperture Radar (InSAR) and continental-scale services su...
https://arxiv.org/abs/2512.23906
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e7b2b89ba6f959eebda62abb5cc86feab78ae955bf3d32b7510fbb09bd482cc8
2026-01-01T00:00:00-05:00
Tensor Computing Interface: An Application-Oriented, Lightweight Interface for Portable High-Performance Tensor Network Applications
arXiv:2512.23917v1 Announce Type: cross Abstract: Tensor networks (TNs) are a central computational tool in quantum science and artificial intelligence. However, the lack of unified software interface across tensor-computing frameworks severely limits the portability of TN applications, coupling algorithmic development...
https://arxiv.org/abs/2512.23917
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5efcfaf6f3d736c8b0c1de3c37cde6d0ce250919b6c2822108eaf63517d06ca8
2026-01-01T00:00:00-05:00
Stationary Reweighting Yields Local Convergence of Soft Fitted Q-Iteration
arXiv:2512.23927v1 Announce Type: cross Abstract: Fitted Q-iteration (FQI) and its entropy-regularized variant, soft FQI, are central tools for value-based model-free offline reinforcement learning, but can behave poorly under function approximation and distribution shift. In the entropy-regularized setting, we show th...
https://arxiv.org/abs/2512.23927
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0aad164e37b48119dcb7d969024a8d2c822e7344e7a0086dd46ca369dc700399
2026-01-01T00:00:00-05:00
Assessing generative modeling approaches for free energy estimates in condensed matter
arXiv:2512.23930v1 Announce Type: cross Abstract: The accurate estimation of free energy differences between two states is a long-standing challenge in molecular simulations. Traditional approaches generally rely on sampling multiple intermediate states to ensure sufficient overlap in phase space and are, consequently,...
https://arxiv.org/abs/2512.23930
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b7e10b6ed4acbdcf10822e51bfa41a68533957f4617e04cbab767fe8ec353ca5
2026-01-01T00:00:00-05:00
Implicit geometric regularization in flow matching via density weighted Stein operators
arXiv:2512.23956v1 Announce Type: cross Abstract: Flow Matching (FM) has emerged as a powerful paradigm for continuous normalizing flows, yet standard FM implicitly performs an unweighted $L^2$ regression over the entire ambient space. In high dimensions, this leads to a fundamental inefficiency: the vast majority of t...
https://arxiv.org/abs/2512.23956
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70983fc113ec2a4d4d5f153a497446cbb1c7fe11c46b0148678dcfbd255f5c95
2026-01-01T00:00:00-05:00
Fundamental limits for weighted empirical approximations of tilted distributions
arXiv:2512.23979v1 Announce Type: cross Abstract: Consider the task of generating samples from a tilted distribution of a random vector whose underlying distribution is unknown, but samples from it are available. This finds applications in fields such as finance and climate science, and in rare event simulation. In thi...
https://arxiv.org/abs/2512.23979
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200cdc6a6d441663b51c068ae2a8c6b125e8e0e880fbe83b02347a7bda12b104
2026-01-01T00:00:00-05:00
One-Shot Structured Pruning of Quantum Neural Networks via $q$-Group Engineering and Quantum Geometric Metrics
arXiv:2512.24019v1 Announce Type: cross Abstract: Quantum neural networks (QNNs) suffer from severe gate-level redundancy, which hinders their deployment on noisy intermediate-scale quantum (NISQ) devices. In this work, we propose q-iPrune, a one-shot structured pruning framework grounded in the algebraic structure of ...
https://arxiv.org/abs/2512.24019
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5b07c7e68f75f0816a1f9051cdc6d1c4ca2f25985e869e7c77c2d42d5cb1fec0
2026-01-01T00:00:00-05:00
Exposed: Shedding Blacklight on Online Privacy
arXiv:2512.24041v1 Announce Type: cross Abstract: To what extent are users surveilled on the web, by what technologies, and by whom? We answer these questions by combining passively observed, anonymized browsing data of a large, representative sample of Americans with domain-level data on tracking from Blacklight. We f...
https://arxiv.org/abs/2512.24041
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29ac61b9bb883b84ecd7a885c9d9ace7292bfcde376c0709b459a00fd58c41ae
2026-01-01T00:00:00-05:00
$L^p$ Estimates for Numerical Approximation of Hamilton-Jacobi Equations
arXiv:2512.24051v1 Announce Type: cross Abstract: We establish $L^p$ error estimates for monotone numerical schemes approximating Hamilton-Jacobi equations on the $d$-dimensional torus. Using the adjoint method, we first prove a $L^1$ error bound of order one for finite-difference and semi-Lagrangian schemes under stan...
https://arxiv.org/abs/2512.24051
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509144ef12fec955142cf3e887a3231409e31f46f7e217fd1ab2a6e7c77e9f23
2026-01-01T00:00:00-05:00
Policy Mirror Descent with Temporal Difference Learning: Sample Complexity under Online Markov Data
arXiv:2512.24056v1 Announce Type: cross Abstract: This paper studies the policy mirror descent (PMD) method, which is a general policy optimization framework in reinforcement learning and can cover a wide range of policy gradient methods by specifying difference mirror maps. Existing sample complexity analysis for poli...
https://arxiv.org/abs/2512.24056
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086b6d201f03e54d11b9029dda9a3edf364eadd52a2c57236764dc94098c109e
2026-01-01T00:00:00-05:00
Notes on the 33-point Erd\H{o}s--Szekeres problem
arXiv:2512.24061v1 Announce Type: cross Abstract: The determination of $ES(7)$ is the first open case of the planar Erd\H{o}s--Szekeres problem, where the general conjecture predicts $ES(7)=33$. We present a SAT encoding for the 33-point case based on triple-orientation variables and a 4-set convexity criterion for exc...
https://arxiv.org/abs/2512.24061
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eef5690e07ab1ab35551a10e32dc3e89b49a42554c19cfb6c3e422c6d12cbf17
2026-01-01T00:00:00-05:00
Constructive Approximation of Random Process via Stochastic Interpolation Neural Network Operators
arXiv:2512.24106v1 Announce Type: cross Abstract: In this paper, we construct a class of stochastic interpolation neural network operators (SINNOs) with random coefficients activated by sigmoidal functions. We establish their boundedness, interpolation accuracy, and approximation capabilities in the mean square sense, ...
https://arxiv.org/abs/2512.24106
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a992bdca68bcda491953fb16d1a15052f6084eddcc86d494df09edacaf516f70
2026-01-01T00:00:00-05:00
Dominion of some graphs
arXiv:2512.24115v1 Announce Type: cross Abstract: Given a graph G equals (V,E), a subset S subset of V is a dominating set if every vertex in V minus S is adjacent to some vertex in S. The dominating set with the least cardinality, gamma, is called a gamma-set which is commonly known as a minimum dominating set. The do...
https://arxiv.org/abs/2512.24115
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6b22d1b414bf1753de41653db9cd7efe6363def7e6bf55e70b60b42029e63385
2026-01-01T00:00:00-05:00
Quantitative Understanding of PDF Fits and their Uncertainties
arXiv:2512.24116v1 Announce Type: cross Abstract: Parton Distribution Functions (PDFs) play a central role in describing experimental data at colliders and provide insight into the structure of nucleons. As the LHC enters an era of high-precision measurements, a robust PDF determination with a reliable uncertainty quan...
https://arxiv.org/abs/2512.24116
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272ddb6862425c4bdc9f213abfaa67ee316266c5166482937f2d863e6a6ae81d
2026-01-01T00:00:00-05:00
Targeted Semantic Segmentation of Himalayan Glacial Lakes Using Time-Series SAR: Towards Automated GLOF Early Warning
arXiv:2512.24117v1 Announce Type: cross Abstract: Glacial Lake Outburst Floods (GLOFs) are one of the most devastating climate change induced hazards. Existing remote monitoring approaches often prioritise maximising spatial coverage to train generalistic models or rely on optical imagery hampered by persistent cloud c...
https://arxiv.org/abs/2512.24117
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e256d8805b54841a6336e6244648595bbc42beda94b58ae499a027556f27c832
2026-01-01T00:00:00-05:00
Score-based sampling without diffusions: Guidance from a simple and modular scheme
arXiv:2512.24152v1 Announce Type: cross Abstract: Sampling based on score diffusions has led to striking empirical results, and has attracted considerable attention from various research communities. It depends on availability of (approximate) Stein score functions for various levels of additive noise. We describe and ...
https://arxiv.org/abs/2512.24152
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0f1325df7018425e8d102da733439a87064c4aa97d1d5142fe78b173b4874e36
2026-01-01T00:00:00-05:00
Discovering Optimal Robust Minimum Redundancy Arrays (RMRAs) through Exhaustive Search and Algebraic Formulation of a New Sub-Optimal RMRA
arXiv:2512.24155v1 Announce Type: cross Abstract: Modern sparse arrays are maximally economic in that they retain just as many sensors required to provide a specific aperture while maintaining a hole-free difference coarray. As a result, these are susceptible to the failure of even a single sensor. Contrarily, two-fold...
https://arxiv.org/abs/2512.24155
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eb8f1cfe10dbb61dea681137fc45ce312d3e8b04b61f1a68f387ce910fb7ecbf
2026-01-01T00:00:00-05:00
Variational Quantum Brushes
arXiv:2512.24173v1 Announce Type: cross Abstract: Quantum brushes are computational arts software introduced by Ferreira et al (2025) that leverage quantum behavior to generate novel artistic effects. In this outreach paper, we introduce the mathematical framework and describe the implementation of two quantum brushes ...
https://arxiv.org/abs/2512.24173
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4d4d15b0db485ea4d2c2476ca571c7d84ec90a40aed1afef13fe10d5328d0f84
2026-01-01T00:00:00-05:00
Fast reconstruction-based ROI triggering via anomaly detection in the CYGNO optical TPC
arXiv:2512.24290v1 Announce Type: cross Abstract: Optical-readout Time Projection Chambers (TPCs) produce megapixel-scale images whose fine-grained topological information is essential for rare-event searches, but whose size challenges real-time data selection. We present an unsupervised, reconstruction-based anomaly-d...
https://arxiv.org/abs/2512.24290
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d22cf33a6362e9382c4b3ae200307870de9f2a13710252018c805effc758199c
2026-01-01T00:00:00-05:00
On maximum distance separable and completely regular codes
arXiv:2512.24292v1 Announce Type: cross Abstract: We investigate when a maximum distance separable ($MDS$) code over $F_q$ is also completely regular ($CR$). For lengths $n=q+1$ and $n=q+2$ we provide a complete classification of the $MDS$ codes that are $CR$ or at least uniformly packed in the wide sense ($UPWS$). For...
https://arxiv.org/abs/2512.24292
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316235a9f2f38b4f38b13d0b6764206af93f91c3a94daf6d416bd66d8a155b20
2026-01-01T00:00:00-05:00
Generative Video Compression: Towards 0.01% Compression Rate for Video Transmission
arXiv:2512.24300v1 Announce Type: cross Abstract: Whether a video can be compressed at an extreme compression rate as low as 0.01%? To this end, we achieve the compression rate as 0.02% at some cases by introducing Generative Video Compression (GVC), a new framework that redefines the limits of video compression by lev...
https://arxiv.org/abs/2512.24300
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bf9d96a9cd467be703851f3fc0d815e55c9c027c4a6ef6b76193f6c43dc0c354
2026-01-01T00:00:00-05:00
Topological Spatial Graph Coarsening
arXiv:2512.24327v1 Announce Type: cross Abstract: Spatial graphs are particular graphs for which the nodes are localized in space (e.g., public transport network, molecules, branching biological structures). In this work, we consider the problem of spatial graph reduction, that aims to find a smaller spatial graph (i.e...
https://arxiv.org/abs/2512.24327
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37c14e3894213ca9cf93b62ac9bc332e2907a53c5b34c3ded0b304752d952858
2026-01-01T00:00:00-05:00
OptiVote: Non-Coherent FSO Over-the-Air Majority Vote for Communication-Efficient Distributed Federated Learning in Space Data Centers
arXiv:2512.24334v1 Announce Type: cross Abstract: The rapid deployment of mega-constellations is driving the long-term vision of space data centers (SDCs), where interconnected satellites form in-orbit distributed computing and learning infrastructures. Enabling distributed federated learning in such systems is challen...
https://arxiv.org/abs/2512.24334
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cc0c3153036f841b828ba144e6520a01f483efb8db7e8119380fbfb63685f53e
2026-01-01T00:00:00-05:00
Deep Learning in Geotechnical Engineering: A Critical Assessment of PINNs and Operator Learning
arXiv:2512.24365v1 Announce Type: cross Abstract: Deep learning methods -- physics-informed neural networks (PINNs), deep operator networks (DeepONet), and graph network simulators (GNS) -- are increasingly proposed for geotechnical problems. This paper tests these methods against traditional solvers on canonical probl...
https://arxiv.org/abs/2512.24365
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14dfe21025f76173f2d2b3738d035873529f8de978f75904659693fead6cbd69
2026-01-01T00:00:00-05:00
Implicit score matching meets denoising score matching: improved rates of convergence and log-density Hessian estimation
arXiv:2512.24378v1 Announce Type: cross Abstract: We study the problem of estimating the score function using both implicit score matching and denoising score matching. Assuming that the data distribution exhibiting a low-dimensional structure, we prove that implicit score matching is able not only to adapt to the intr...
https://arxiv.org/abs/2512.24378
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82a522cd05e0f343de7b276d90e546c0915a53a1613345ee31fcf4a5ebe9ee4e
2026-01-01T00:00:00-05:00
Finite element analysis of very large bone models based on micro-CT scans
arXiv:2512.24401v1 Announce Type: cross Abstract: High-resolution voxel-based micro-finite element ($\mu$FE) models derived from $\mu$CT imaging enable detailed investigation of bone mechanics but remain computationally challenging at anatomically relevant scales. This study presents a comprehensive $\mu$FE framework f...
https://arxiv.org/abs/2512.24401
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340d2b75c6b19327ac604b40309543c168a20eb416c905b961547dddfdfadf2a
2026-01-01T00:00:00-05:00
Virasoro Symmetry in Neural Network Field Theories
arXiv:2512.24420v1 Announce Type: cross Abstract: Neural Network Field Theories (NN-FTs) can realize global conformal symmetries via embedding space architectures. These models describe Generalized Free Fields (GFFs) in the infinite width limit. However, they typically lack a local stress-energy tensor satisfying confo...
https://arxiv.org/abs/2512.24420
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14fdb4aa2ec0b2c43ffaaf6cd37cb73fd100b3c82aa6fbdd293be17f5836a166
2026-01-01T00:00:00-05:00
Automated Market Making for Energy Sharing
arXiv:2512.24432v1 Announce Type: cross Abstract: We develop an axiomatic theory for Automated Market Makers (AMMs) in local energy sharing markets and analyze the Markov Perfect Equilibrium of the resulting economy with a Mean-Field Game. In this game, heterogeneous prosumers solve a Bellman equation to optimize energ...
https://arxiv.org/abs/2512.24432
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b31ca0718b44947f5a8d7f5bb2a09e164d49e8713fdc163e0e7371089ab0b8fd
2026-01-01T00:00:00-05:00
Quasicrystalline Gibbs states in 4-dimensional lattice-gas models with finite-range interactions
arXiv:2512.24436v1 Announce Type: cross Abstract: We construct a four-dimensional lattice-gas model with finite-range interactions that has non-periodic, ``quasicrystalline'' Gibbs states at low temperatures. Such Gibbs states are probability measures which are small perturbations of non-periodic ground-state configura...
https://arxiv.org/abs/2512.24436
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faa32383d53eb33ac9ae8556cf9eee7b9f0d5153f2ea2897e282a05de464fd1c
2026-01-01T00:00:00-05:00
Towards mechanistic understanding in a data-driven weather model: internal activations reveal interpretable physical features
arXiv:2512.24440v1 Announce Type: cross Abstract: Large data-driven physics models like DeepMind's weather model GraphCast have empirically succeeded in parameterizing time operators for complex dynamical systems with an accuracy reaching or in some cases exceeding that of traditional physics-based solvers. Unfortunate...
https://arxiv.org/abs/2512.24440
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0a623ad00e16c73f3a1bd259f8438b25430b7b58b58b704d619ba63080f70b22
2026-01-01T00:00:00-05:00
The Wigner-Ville Transform as an Information Theoretic Tool in Radio-frequency Signal Analysis
arXiv:2512.24488v1 Announce Type: cross Abstract: This paper presents novel interpretations to the field of classical signal processing of the Wigner-Ville transform as an information measurement tool. The transform's utility in detecting and localizing information-laden signals amidst noisy and cluttered backgrounds, ...
https://arxiv.org/abs/2512.24488
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4a4482fef318064311078a642e49619e03d9d2951e4120ae3e03aa76b4f6c44b
2026-01-01T00:00:00-05:00
Automated Classification of First-Trimester Fetal Heart Views Using Ultrasound-Specific Self-Supervised Learning
arXiv:2512.24492v1 Announce Type: cross Abstract: Congenital heart disease remains the most common congenital anomaly and a leading cause of neonatal morbidity and mortality. Although first-trimester fetal echocardiography offers an opportunity for earlier detection, automated analysis at this stage is challenging due ...
https://arxiv.org/abs/2512.24492
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87e9ec42387891001904de8047df70b730bcd6588840b87deb74f74e2ad497a8
2026-01-01T00:00:00-05:00
Improving the stability of the covariance-controlled adaptive Langevin thermostat for large-scale Bayesian sampling
arXiv:2512.24515v1 Announce Type: cross Abstract: Stochastic gradient Langevin dynamics and its variants approximate the likelihood of an entire dataset, via random (and typically much smaller) subsets, in the setting of Bayesian sampling. Due to the (often substantial) improvement of the computational efficiency, they...
https://arxiv.org/abs/2512.24515
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e139279afd0bf4d4713a1fee8be35c5c036de89a97e6051dece6795923f882b7
2026-01-01T00:00:00-05:00
Power Analysis is Essential: High-Powered Tests Suggest Minimal to No Effect of Rounded Shapes on Click-Through Rates
arXiv:2512.24521v1 Announce Type: cross Abstract: Underpowered studies (below 50%) suffer from the winner's curse: a statistically significant result must exaggerate the true treatment effect to meet the significance threshold. A study by Dipayan Biswas, Annika Abell, and Roger Chacko published in the Journal of Consum...
https://arxiv.org/abs/2512.24521
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09654a0e1e474969f0e5e9c653d78d17ed0e71d12e51b678ddd3d3c49690843c
2026-01-01T00:00:00-05:00
Proper colorings of a graph in linear time using a number of colors linear in the maximum degree of the graph
arXiv:2512.24522v1 Announce Type: cross Abstract: A new algorithm for exactly sampling from the set of proper colorings of a graph is presented. This is the first such algorithm that has an expected running time that is guaranteed to be linear in the size of a graph with maximum degree \( \Delta \) when the number of c...
https://arxiv.org/abs/2512.24522
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9996d61bc3847559afd1a8b00fd971c59afb796d898b178b833086bbfb61738e
2026-01-01T00:00:00-05:00
Generative AI-enhanced Sector-based Investment Portfolio Construction
arXiv:2512.24526v1 Announce Type: cross Abstract: This paper investigates how Large Language Models (LLMs) from leading providers (OpenAI, Google, Anthropic, DeepSeek, and xAI) can be applied to quantitative sector-based portfolio construction. We use LLMs to identify investable universes of stocks within S&P 500 s...
https://arxiv.org/abs/2512.24526
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1ad442b2c30c744b54614eaf9cf6aa2eb651f7f8d08b549ce952b507b582241b
2026-01-01T00:00:00-05:00
Probabilistic Computers for Neural Quantum States
arXiv:2512.24558v1 Announce Type: cross Abstract: Neural quantum states efficiently represent many-body wavefunctions with neural networks, but the cost of Monte Carlo sampling limits their scaling to large system sizes. Here we address this challenge by combining sparse Boltzmann machine architectures with probabilist...
https://arxiv.org/abs/2512.24558
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1b51a6cfa1dfc74f4c6fc778ce83183eda4e3aae3083d5cec08112bad5642132
2026-01-01T00:00:00-05:00
Robust Bayesian Dynamic Programming for On-policy Risk-sensitive Reinforcement Learning
arXiv:2512.24580v1 Announce Type: cross Abstract: We propose a novel framework for risk-sensitive reinforcement learning (RSRL) that incorporates robustness against transition uncertainty. We define two distinct yet coupled risk measures: an inner risk measure addressing state and cost randomness and an outer risk meas...
https://arxiv.org/abs/2512.24580
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7159ac4fb8f09d9911540d568fe6850b917ace59b848567d5e116f756b41ed06
2026-01-01T00:00:00-05:00
On Circular Threshold Words and Other Stronger Versions of Dejean's conjecture
arXiv:2512.24581v1 Announce Type: cross Abstract: Let the root of the word $w$ be the smallest prefix $v$ of $w$ such that $w$ is a prefix of $vvv...$. $per(w)$ is the length of the root of $w$. For any $n\ge5$, an $n$-ary threshold word is a word $w$ such that for any factor (subword) $v$ of $w$ the condition $\frac{|...
https://arxiv.org/abs/2512.24581
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a1a1cf45d308f8125674b6d9f0916b05c43202f77d1879036e0450731ef78650
2026-01-01T00:00:00-05:00
MultiRisk: Multiple Risk Control via Iterative Score Thresholding
arXiv:2512.24587v1 Announce Type: cross Abstract: As generative AI systems are increasingly deployed in real-world applications, regulating multiple dimensions of model behavior has become essential. We focus on test-time filtering: a lightweight mechanism for behavior control that compares performance scores to estima...
https://arxiv.org/abs/2512.24587
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cb237294fde856e2be7143bce7579a76fc1566c8acf10849007b0e5e5139af92
2026-01-01T00:00:00-05:00
A Uniform Pilot and Data Payload Optimization Framework for OTFS-Based ISAC
arXiv:2512.24624v1 Announce Type: cross Abstract: The orthogonal time frequency space (OTFS) signal is considered a promising solution for high-mobility wireless environments. It manages Doppler effects by utilizing delay-Doppler (DD) domain processing. However, the relatively long OTFS frame duration could introduce c...
https://arxiv.org/abs/2512.24624
Academic Papers
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66db174841f9f1c34ddaf3fa49b3b058c2e064f6cc41ea8896dd05133517d0f6
2026-01-01T00:00:00-05:00
Soliton profiles: Classical Numerical Schemes vs. Neural Network - Based Solvers
arXiv:2512.24634v1 Announce Type: cross Abstract: We present a comparative study of classical numerical solvers, such as Petviashvili's method or finite difference with Newton iterations, and neural network-based methods for computing ground states or profiles of solitary-wave solutions to the one-dimensional dispersiv...
https://arxiv.org/abs/2512.24634
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2cc211f273f51751bbcfd14d227137e6a0789af73c84602e17315ceecf25030c
2026-01-01T00:00:00-05:00
A unified spatiotemporal formulation with physics-preserving structure for time-dependent convection-diffusion problems
arXiv:2512.24650v1 Announce Type: cross Abstract: We propose a unified four-dimensional (4D) spatiotemporal formulation for time-dependent convection-diffusion problems that preserves underlying physical structures. By treating time as an additional space-like coordinate, the evolution problem is reformulated as a stat...
https://arxiv.org/abs/2512.24650
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6d20ad52a18bb836c3d92b9878af9a68a5781883778db10964e99201361ea589
2026-01-01T00:00:00-05:00
An Adaptive, Disentangled Representation for Multidimensional MRI Reconstruction
arXiv:2512.24674v1 Announce Type: cross Abstract: We present a new approach for representing and reconstructing multidimensional magnetic resonance imaging (MRI) data. Our method builds on a novel, learned feature-based image representation that disentangles different types of features, such as geometry and contrast, i...
https://arxiv.org/abs/2512.24674
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f3852f630d227420e826d07a1346ff1973c781b2eda533ecd28ec3b349db3e52
2026-01-01T00:00:00-05:00
A New Decomposition Paradigm for Graph-structured Nonlinear Programs via Message Passing
arXiv:2512.24676v1 Announce Type: cross Abstract: We study finite-sum nonlinear programs whose decision variables interact locally according to a graph or hypergraph. We propose MP-Jacobi (Message Passing-Jacobi), a graph-compliant decentralized framework that couples min-sum message passing with Jacobi block updates. ...
https://arxiv.org/abs/2512.24676
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4831194f26e2afbf58d4f7f1651312b9329113c0c35f23762d301194a714ced4
2026-01-01T00:00:00-05:00
Quantum Visual Word Sense Disambiguation: Unraveling Ambiguities Through Quantum Inference Model
arXiv:2512.24687v1 Announce Type: cross Abstract: Visual word sense disambiguation focuses on polysemous words, where candidate images can be easily confused. Traditional methods use classical probability to calculate the likelihood of an image matching each gloss of the target word, summing these to form a posterior p...
https://arxiv.org/abs/2512.24687
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4670a28625cfbc7ed9ee0a504837804cf76bb1728e1006ed6c57882cc6a2f769
2026-01-01T00:00:00-05:00
Fairness-Aware Insurance Pricing: A Multi-Objective Optimization Approach
arXiv:2512.24747v1 Announce Type: cross Abstract: Machine learning improves predictive accuracy in insurance pricing but exacerbates trade-offs between competing fairness criteria across different discrimination measures, challenging regulators and insurers to reconcile profitability with equitable outcomes. While exis...
https://arxiv.org/abs/2512.24747
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4a4fc5b3aafeaa86c9b7069aec63b55aaa0c2dce1308dc9af1c4c1345d3325a1
2026-01-01T00:00:00-05:00
AstroReview: An LLM-driven Multi-Agent Framework for Telescope Proposal Peer Review and Refinement
arXiv:2512.24754v1 Announce Type: cross Abstract: Competitive access to modern observatories has intensified as proposal volumes outpace available telescope time, making timely, consistent, and transparent peer review a critical bottleneck for the advancement of astronomy. Automating parts of this process is therefore ...
https://arxiv.org/abs/2512.24754
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6f778d0f4cbcfa779763cf6f5671a0b935c5bc791062ad99672219cc806c94d3
2026-01-01T00:00:00-05:00
Sparse Offline Reinforcement Learning with Corruption Robustness
arXiv:2512.24768v1 Announce Type: cross Abstract: We investigate robustness to strong data corruption in offline sparse reinforcement learning (RL). In our setting, an adversary may arbitrarily perturb a fraction of the collected trajectories from a high-dimensional but sparse Markov decision process, and our goal is t...
https://arxiv.org/abs/2512.24768
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c9fbdcfcea8c0e10c76377a356a6123fc8ad351067067e50a0ef8012c0121a34
2026-01-01T00:00:00-05:00
Structured Production Systems: Viability
arXiv:2512.24777v1 Announce Type: cross Abstract: This paper introduces a novel framework for analysing equilibrium in structured production systems incorporating a static social division of labour by distinguishing between consumption goods traded in competitive markets and intermediate goods exchanged through bilater...
https://arxiv.org/abs/2512.24777
Academic Papers
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e21535866ed8d2711c966d8bb7e7668f4e36aaff0e6ff87b4c41d9a25e39cde1
2026-01-01T00:00:00-05:00
Limits of quantum generative models with classical sampling hardness
arXiv:2512.24801v1 Announce Type: cross Abstract: Sampling tasks have been successful in establishing quantum advantages both in theory and experiments. This has fueled the use of quantum computers for generative modeling to create samples following the probability distribution underlying a given dataset. In particular...
https://arxiv.org/abs/2512.24801
Academic Papers
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28704f83a09d5a8bf1109c34456fd342fe18f7e8a51c3aa89d3358714e4f94ea
2026-01-01T00:00:00-05:00
Learning Temporally Consistent Turbulence Between Sparse Snapshots via Diffusion Models
arXiv:2512.24813v1 Announce Type: cross Abstract: We investigate the statistical accuracy of temporally interpolated spatiotemporal flow sequences between sparse, decorrelated snapshots of turbulent flow fields using conditional Denoising Diffusion Probabilistic Models (DDPMs). The developed method is presented as a pr...
https://arxiv.org/abs/2512.24813
Academic Papers
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942225e3d71003145864dd79e67ba8fec776a31d4f162c1d09daa2d0b8701ce1
2026-01-01T00:00:00-05:00
Advances in Agentic AI: Back to the Future
arXiv:2512.24856v1 Announce Type: cross Abstract: In light of the recent convergence between Agentic AI and our field of Algorithmization, this paper seeks to restore conceptual clarity and provide a structured analytical framework for an increasingly fragmented discourse. First, (a) it examines the contemporary landsc...
https://arxiv.org/abs/2512.24856
Academic Papers
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5bd244b5bd9d0c17de319dd55182cb8cecafc242731e10867890daf477a02c85
2026-01-01T00:00:00-05:00
Approximate Computation via Le Cam Simulability
arXiv:2512.24860v1 Announce Type: cross Abstract: We propose a decision-theoretic framework for computational complexity, complementary to classical theory: moving from syntactic exactness (Turing / Shannon) to semantic simulability (Le Cam). While classical theory classifies problems by the cost of exact solution, mod...
https://arxiv.org/abs/2512.24860
Academic Papers
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0da5532f4b6dd3f02edc68227e0ce95ca09121bfa990fd3e9142e9e94dc12603
2026-01-01T00:00:00-05:00
On Prime Matrix Product Factorizations
arXiv:2512.24864v1 Announce Type: cross Abstract: A graph $G$ factors into graphs $H$ and $K$ via a matrix product if $A = BC$, where $A$, $B$, and $C$ are the adjacency matrices of $G$, $H$, and $K$, respectively. The graph $G$ is prime if, in every such factorization, one of the factors is a perfect matching that is,...
https://arxiv.org/abs/2512.24864
Academic Papers
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