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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 | svg |
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 | svg |
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 | svg |
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 | svg |
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 | svg |
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 | svg |
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 | svg |
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 | svg |
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 | svg |
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 | svg |
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 | svg |
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 | svg |
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 | svg |
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 | svg |
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 | svg |
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 | svg |
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 | svg |
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 | svg |
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 | svg |
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 | svg |
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 | svg |
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 | svg |
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 | svg |
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 | svg |
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 | svg |
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 | svg |
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 | svg |
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 | svg |
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 | svg |
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 | svg |
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 | svg |
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 | svg |
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 | svg |
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 | Academic Papers | svg |
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 | Academic Papers | svg |
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 | Academic Papers | svg |
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 | Academic Papers | svg |
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 | Academic Papers | svg |
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 | Academic Papers | svg |
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 | Academic Papers | svg |
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 | Academic Papers | svg |
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 | Academic Papers | svg |
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 | Academic Papers | svg |
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 | svg |
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 | Academic Papers | svg |
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 | Academic Papers | svg |
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 | Academic Papers | svg |
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 | Academic Papers | svg |
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 | Academic Papers | svg |
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 | Academic Papers | svg |
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 | Academic Papers | svg |
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 | Academic Papers | svg |
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 | Academic Papers | svg |
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 | Academic Papers | svg |
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 | Academic Papers | svg |
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 | Academic Papers | svg |
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 | Academic Papers | svg |
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 | Academic Papers | svg |
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 | Academic Papers | svg |
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 | Academic Papers | svg |
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 | Academic Papers | svg |
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 | Academic Papers | svg |
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 | Academic Papers | svg |
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 | Academic Papers | svg |
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 | Academic Papers | svg |
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 | Academic Papers | svg |
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 | Academic Papers | svg |
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 | Academic Papers | svg |
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 | Academic Papers | svg |
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 | Academic Papers | svg |
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 | Academic Papers | svg |
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 | Academic Papers | svg |
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 | Academic Papers | svg |
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 | Academic Papers | svg |
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 | Academic Papers | svg |
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 | Academic Papers | svg |
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 | Academic Papers | svg |
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 | Academic Papers | svg |
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 | Academic Papers | svg |
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 | Academic Papers | svg |
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 | Academic Papers | svg |
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 | Academic Papers | svg |
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 | Academic Papers | svg |
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 | Academic Papers | svg |
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 | Academic Papers | svg |
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 | svg |
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 | Academic Papers | svg |
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 | Academic Papers | svg |
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 | Academic Papers | svg |
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 | Academic Papers | svg |
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 | Academic Papers | svg |
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 | Academic Papers | svg |
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 | Academic Papers | svg |
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 | Academic Papers | svg |
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 | svg |
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 | svg |
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 | svg |
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 | svg |
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 | svg |
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 | svg |
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