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arXiv:2601.20692v1 Announce Type: new Abstract: Group counterfactual explanations find a set of counterfactual instances to explain a group of input instances contrastively. However, existing methods...
arXiv:2601.20694v1 Announce Type: new Abstract: Exogenous MDPs (Exo-MDPs) capture sequential decision-making where uncertainty comes solely from exogenous inputs that evolve independently of the learner's actions....
arXiv:2601.20696v1 Announce Type: new Abstract: Combinatorial optimization problems such as the Job-Shop Scheduling Problem (JSP) and Knapsack Problem (KP) are fundamental challenges in operations research,...
arXiv:2601.20699v1 Announce Type: new Abstract: We present a propagation model showing that a transmitter randomly positioned in space generates unbounded peaks in the histogram of...
arXiv:2601.20701v1 Announce Type: new Abstract: Real-time robotic control demands fast action generation. However, existing generative policies based on diffusion and flow matching require multi-step sampling,...
arXiv:2601.20704v1 Announce Type: new Abstract: Large language models are increasingly used to curate bibliographies, raising the question: are their reference lists distinguishable from human ones?...
arXiv:2601.20705v1 Announce Type: new Abstract: Recent multimodal large language models (MLLMs) have shown remarkable progress across vision, audio, and language tasks, yet their performance on...
arXiv:2601.20706v1 Announce Type: new Abstract: Diffusion Large Language Models (dLLMs) introduce iterative denoising to enable parallel token generation, but their sampling phase displays fundamentally different...
arXiv:2601.20707v1 Announce Type: new Abstract: We present an AI-based framework for semantic transmission of multimedia data over band-limited, time-varying channels. The method targets scenarios where...
arXiv:2601.20709v1 Announce Type: new Abstract: Biomedical researchers face increasing challenges in navigating millions of publications in diverse domains. Traditional search engines typically return articles as...
arXiv:2601.20714v1 Announce Type: new Abstract: Reinforcement Learning (RL) agents often struggle in real-world applications where environmental conditions are non-stationary, particularly when reward functions shift or...
arXiv:2601.20716v1 Announce Type: new Abstract: Decentralized Identifiers (DIDs) are increasingly deployed on distributed ledgers, yet systematic cross-platform evidence on their operational behavior remains limited. We...
arXiv:2601.20718v1 Announce Type: new Abstract: A $t$-spanner of an undirected $n$-vertex graph $G$ is a sparse subgraph $H$ of $G$ that preserves all pairwise distances...
arXiv:2601.20720v1 Announce Type: new Abstract: End-to-end perception and trajectory prediction from raw sensor data is one of the key capabilities for autonomous driving. Modular pipelines...
arXiv:2601.20722v1 Announce Type: new Abstract: Portals have many applications in the field of computer graphics. Recently, they have found use as a way of artificially...
arXiv:2601.20723v1 Announce Type: new Abstract: We study binary coordination games over graphs under log-linear learning when neighbor actions are conveyed through explicit noisy communication links....
arXiv:2601.20727v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly embedded in consequential decisions across healthcare, finance, employment, and public services. Yet accountability remains...
arXiv:2601.20729v1 Announce Type: new Abstract: The Cox Proportional Hazards (PH) model is widely used in survival analysis. Recently, artificial neural network (ANN)-based Cox-PH models have...
arXiv:2601.20730v1 Announce Type: new Abstract: The evolution of Large Language Models (LLMs) into autonomous agents necessitates the management of extensive, dynamic contexts. Current benchmarks, however,...
arXiv:2601.20731v1 Announce Type: new Abstract: This paper examines how Large Language Models (LLMs) reproduce societal norms, particularly heterocisnormativity, and how these norms translate into measurable...
arXiv:2601.20732v1 Announce Type: new Abstract: As digital environments (data distribution) are in flux, with new GUI data arriving over time-introducing new domains or resolutions-agents trained...
arXiv:2601.20735v1 Announce Type: new Abstract: We develop a computational approach to Metric Answer Set Programming (ASP) to allow for expressing quantitative temporal constraints, like durations...
arXiv:2601.20737v1 Announce Type: new Abstract: Family learning takes place in everyday routines where children and caregivers read, practice, and develop new skills together. Despite growing...
arXiv:2601.20738v1 Announce Type: new Abstract: Biased gradient compression with error feedback (EF) reduces communication in federated learning (FL), but under non-IID data, the residual error...