January 2026

arXiv:2601.08959v1 Announce Type: new Abstract: As zero-day Android malware attacks grow more sophisticated, recent research highlights the effectiveness of using image-based representations of malware bytecode to detect previously unseen threats. However, existing studies often overlook how image type and resolution affect detection and ignore valuable textual data in Android Application Packages (APKs), such as permissions and metadata, limiting their ability to fully capture malicious behavior. The integration of multimodality, which combines image and text data, has gained momentum […]

Ver mais

arXiv:2601.08956v1 Announce Type: new Abstract: Brain tumor segmentation is essential for diagnosis and treatment planning, yet many CNN and U-Net based approaches produce noisy boundaries in regions of tumor infiltration. We introduce UAMSA-UNet, an Uncertainty-Aware Multi-Scale Attention-based Bayesian U-Net that in- stead leverages Monte Carlo Dropout to learn a data-driven smoothing prior over its predictions, while fusing multi-scale features and attention maps to capture both fine details and global context. Our smoothing-regularized loss augments binary cross-entropy with a […]

Ver mais

arXiv:2601.08955v1 Announce Type: new Abstract: Recent advances in world models have shown promise for modeling future dynamics of environmental states, enabling agents to reason and act without accessing real environments. Current methods mainly perform single-step or fixed-horizon rollouts, leaving their potential for complex task planning under-exploited. We propose Imagine-then-Plan (texttt{ITP}), a unified framework for agent learning via lookahead imagination, where an agent’s policy model interacts with the learned world model, yielding multi-step “imagined” trajectories. Since the imagination horizon […]

Ver mais

arXiv:2601.08954v1 Announce Type: new Abstract: This chapter examines how data analytics can be leveraged to enhance immersive teacher simulations, situating this inquiry within the broader learning sciences discourse on embodied cognition, data-informed feedback, and teacher professional learning. It explores both conceptual foundations and empirical cases to illustrate how analytics serve as mediational tools that connect immersive experiences with reflective teaching practice. The chapter unfolds in multiple sections: (1) The Innovation Journey: An Overview of Immersive Teacher Simulations outlines […]

Ver mais

arXiv:2601.08953v1 Announce Type: new Abstract: Complex decision-making by autonomous machines and algorithms could underpin the foundations of future society. Generative AI is emerging as a powerful engine for such transitions. However, we show that Generative AI-driven developments pose a critical pitfall: fairness concerns. In robotic applications, although intuitions about fairness are common, a precise and implementable definition that captures user utility and inherent data randomness is missing. Here we provide a utility-aware fairness metric for robotic decision making […]

Ver mais

arXiv:2601.08951v1 Announce Type: new Abstract: Current AI safety frameworks, which often treat harmfulness as binary, lack the flexibility to handle borderline cases where humans meaningfully disagree. To build more pluralistic systems, it is essential to move beyond consensus and instead understand where and why disagreements arise. We introduce PluriHarms, a benchmark designed to systematically study human harm judgments across two key dimensions — the harm axis (benign to harmful) and the agreement axis (agreement to disagreement). Our scalable […]

Ver mais

arXiv:2601.08950v1 Announce Type: new Abstract: In educational applications, LLMs exhibit several fundamental pedagogical limitations, such as their tendency to reveal solutions rather than support dialogic learning. We introduce ConvoLearn (https://huggingface.co/datasets/masharma/convolearn ), a dataset grounded in knowledge building theory that operationalizes six core pedagogical dimensions: cognitive engagement, formative assessment, accountability, cultural responsiveness, metacognition, and power dynamics. We construct a semi-synthetic dataset of 1250 tutor-student dialogues (20 turns each) in middle school Earth Science through controlled interactions between human teachers […]

Ver mais

arXiv:2601.08929v1 Announce Type: new Abstract: We study when the variable-indexed matrix of pairwise (f)-mutual informations (M^{(f)}_{ij}=I_f(X_i;X_j)) is positive semidefinite (PSD). Let (f:(0,infty)tomathbb{R}) be convex with (f(1)=0), finite in a neighborhood of (1), and with (f(0)<infty) so that diagonal terms are finite. We give a sharp emph{local} characterization around independence: there exists (delta=delta(f)>0) such that for every (n) and every finite-alphabet family ((X_1,ldots,X_n)) whose pairwise joint-to-product ratios lie in ((1-delta,1+delta)), the matrix (M^{(f)}) is PSD if and only if […]

Ver mais

arXiv:2601.08928v1 Announce Type: new Abstract: Supply chain forecasting models degrade over time as real-world conditions change. Promotions shift, consumer preferences evolve, and supply disruptions alter demand patterns, causing what is known as concept drift. This silent degradation leads to stockouts or excess inventory without triggering any system warnings. Current industry practice relies on manual monitoring and scheduled retraining every 3-6 months, which wastes computational resources during stable periods while missing rapid drift events. Existing academic methods focus narrowly […]

Ver mais

arXiv:2601.08927v1 Announce Type: new Abstract: For any positive integer $g ge 2$, we derive general conditions for the existence of a $2g$-cycle in the Tanner graph of two-dimensional ($2$-D) classical quasi-cyclic (QC) low-density parity-check (LDPC) codes. Based on these conditions, we construct a family of $2$-D classical QC-LDPC codes with girth greater than $4$ by stacking $p times p times p$ tensors, where $p$ is an odd prime. Furthermore, for composite values of $p$, we propose two additional […]

Ver mais