arXiv:2607.17654v1 Announce Type: cross Abstract: Multidimensional graded response models (MGRMs) are widely used for analyzing ordinal questionnaire data in psychological and educational assessments. A central challenge…
arXiv:2607.17090v1 Announce Type: cross Abstract: We study the expressivity of shallow polynomial neural networks (PNNs) with monomial activation functions over finite fields. For a given architecture,…
arXiv:2602.04596v2 Announce Type: replace Abstract: Bayes-filtered transformers are transformers meta-learned on sequences from a prior predictive distribution to approximate the corresponding posterior predictive distribution. They output…
arXiv:2406.01161v3 Announce Type: replace-cross Abstract: We study a specific type of SCM, called a Dynamic Structural Causal Model (DSCM), whose endogenous variables represent functions of time,…
arXiv:2607.16199v1 Announce Type: new Abstract: Multi-agent LLM systems increasingly rely on a Planner to decompose goals into sub-task sequences that downstream Executor and Critic agents execute…
arXiv:2404.11459v3 Announce Type: replace Abstract: A multimodal AI agent is characterized by its ability to process and learn from various types of data, including natural language,…
arXiv:2607.16777v1 Announce Type: new Abstract: We present JOR-Bench, a collection of five Japanese-language benchmarks for evaluating the ability of large language models (LLMs) to formulate and…
arXiv:2607.16285v1 Announce Type: new Abstract: Facial affect in the wild is naturally multi-task: valence-arousal, discrete expressions, and facial action units describe the same face. Yet real…
arXiv:2607.16941v1 Announce Type: cross Abstract: Polycystic Ovarian Syndrome (PCOS) is a widespread hormone problem for women of childbearing age. Women with PCOS may not ovulate; they…
arXiv:2607.16234v1 Announce Type: new Abstract: Hantavirus genomic surveillance is limited by the distribution of sequence data, non-IID source heterogeneity, and constrained expert-review capacity. We propose HantaWatch,…
arXiv:2607.17858v1 Announce Type: new Abstract: Reservoir computing exploits nonlinear dynamical systems to encode temporal inputs into high-dimensional state space representations. Although reservoir performance is often characterized…
arXiv:2607.16761v1 Announce Type: new Abstract: Dropout and Random Gradient Masking (RaM) are two training techniques used to improve performance in deep learning. Both techniques inject randomness…
arXiv:2607.16198v1 Announce Type: new Abstract: Graph Neural Networks (GNNs) have emerged as the leading paradigm for link prediction, enabling the inference of missing connections and the…
arXiv:2508.09125v3 Announce Type: replace Abstract: Instruction following has catalyzed the recent era of Large Language Models (LLMs) and is the foundational skill underpinning more advanced capabilities…
arXiv:2607.14385v2 Announce Type: replace Abstract: Large language models achieve strong scores on medical benchmarks, yet these benchmarks evaluate each question in isolation, providing no measure of…
arXiv:2607.16282v1 Announce Type: new Abstract: Follow-me person tracking must run on the drone itself, where affordable companion computers offer only a few effective int8 GFLOP/s. At…
arXiv:2604.08625v2 Announce Type: replace-cross Abstract: We develop a theoretical framework for generalization in the interpolating regime of statistical learning. The central question is why highly overparameterized…
arXiv:2106.04770v2 Announce Type: replace Abstract: We study parameter nonuniqueness in continuous-width depth-two fully connected neural networks. Our main contribution is a direct method for solving the…
arXiv:2410.18777v1 Announce Type: cross Abstract: This research presents an online path planner for Unmanned Aerial Vehicles (UAVs) that can handle dynamic obstacles and UAV motion constraints,…
arXiv:2607.16927v1 Announce Type: new Abstract: We introduce Deep Adaptive Bayesian Screening (DABS), a method for performing adaptive factorial screening in high-dimensional discrete design spaces. DABS learns…
arXiv:2607.16197v1 Announce Type: new Abstract: As artificial intelligence systems are deployed in open-ended, high-stakes settings, a critical dimension remains unmeasured: how perceived risk is translated into…
arXiv:2606.17799v2 Announce Type: replace-cross Abstract: Coding agents have become a major mode of software engineering, but the benchmarks we use to compare them were designed in…
arXiv:2607.16790v1 Announce Type: new Abstract: Fine-grained offensive language detection organizes labels into a hierarchical structure, for which two modeling paradigms exist: cascaded decomposition and joint multi-task…
arXiv:2607.16283v1 Announce Type: new Abstract: The rapid advancement of generative AI has outpaced our ability to reliably detect its outputs, particularly when detectors encounter generators they…