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arXiv:2601.22241v1 Announce Type: new Abstract: Gradient-free black-box optimization (BBO) is widely used in engineering design and provides a flexible framework for topology optimization (TO), enabling...
arXiv:2601.22242v1 Announce Type: new Abstract: A driving algorithm that aligns with good human driving practices, or at the very least collaborates effectively with human drivers,...
arXiv:2601.22244v1 Announce Type: new Abstract: Vector-quantized variational autoencoders (VQ-VAEs) are central to models that rely on high reconstruction fidelity, from neural compression to generative pipelines....
arXiv:2601.22246v1 Announce Type: new Abstract: As large language models (LLMs) become integral to applications such as question answering and content creation, reliable content attribution has...
arXiv:2601.22249v1 Announce Type: new Abstract: Code generation is a core application of large language models (LLMs), yet LLMs still frequently fail on complex programming tasks....
arXiv:2601.22255v1 Announce Type: new Abstract: This article sets off for an exploration of the still evolving discourse surrounding artificial intelligence (AI) in the wake of...
arXiv:2601.22256v1 Announce Type: new Abstract: Monitoring in-class programming exercises can help instructors identify struggling students and common challenges. However, understanding students' progress can be prohibitively...
arXiv:2601.22257v1 Announce Type: new Abstract: The attention mechanism in its standard implementation contains extraneous rotational degrees of freedom that are carried through computation but do...
arXiv:2601.22259v1 Announce Type: new Abstract: While tabular foundation models have achieved remarkable success in classification and regression, adapting them to model time-to-event outcomes for survival...
arXiv:2601.22264v1 Announce Type: new Abstract: In principle, Continuous Integration (CI) pipeline failures provide valuable feedback to developers on code-related errors. In practice, however, pipeline jobs...
arXiv:2601.22265v1 Announce Type: new Abstract: Limited access to medical infrastructure forces elderly and vulnerable patients to rely on home-based care, often leading to neglect and...
arXiv:2601.22269v1 Announce Type: new Abstract: Judge agents are fundamental to agentic AI frameworks: they provide automated evaluation, and enable iterative self-refinement of reasoning processes. We...
arXiv:2601.22274v1 Announce Type: new Abstract: Real-world federated systems seldom operate on static data: input distributions drift while privacy rules forbid raw-data sharing. We study this...
arXiv:2601.22275v1 Announce Type: new Abstract: The quadratic complexity of the attention mechanism severely limits the context scalability of Video Diffusion Transformers (DiTs). We find that...
arXiv:2601.22276v1 Announce Type: new Abstract: As Text-to-Image (T2I) diffusion models are increasingly used in real-world creative workflows, a principled framework for valuing contributors who provide...
arXiv:2601.22284v1 Announce Type: new Abstract: We introduce Riemannian Lyapunov Optimizers (RLOs), a family of optimization algorithms that unifies classic optimizers within one geometric framework. Unlike...
arXiv:2601.22285v1 Announce Type: new Abstract: Model merging combines knowledge from separately fine-tuned models, yet success factors remain poorly understood. While recent work treats mergeability as...
arXiv:2601.22288v1 Announce Type: new Abstract: LLM-based and agent-based synthetic personas are increasingly used in design and product decision-making, yet prior work shows that prompt-based personas...
arXiv:2601.22289v1 Announce Type: new Abstract: We focus on multi-object rearrangement planning in densely cluttered environments using a car-like robot pusher. The combination of kinematic, geometric...
arXiv:2601.22290v1 Announce Type: new Abstract: Large Language Models demonstrate remarkable capabilities yet remain fundamentally probabilistic, presenting critical reliability challenges for enterprise deployment. We introduce the...
arXiv:2601.22292v1 Announce Type: new Abstract: Multi-agent systems often operate in dynamic and uncertain environments, where agents must not only pursue individual goals but also safeguard...
arXiv:2601.22296v1 Announce Type: new Abstract: Reservoir Computing (RC) has established itself as an efficient paradigm for temporal processing. However, its scalability remains severely constrained by...
arXiv:2601.22297v1 Announce Type: new Abstract: The reasoning abilities of large language models (LLMs) have been substantially improved by reinforcement learning with verifiable rewards (RLVR). At...
arXiv:2601.22298v1 Announce Type: new Abstract: Conditional generative models map input variables to complex, high-dimensional distributions, enabling realistic sample generation in a diverse set of domains....