Search: “tutorials”

arXiv:2606.27593v1 Announce Type: new Abstract: We introduce a categorical framework called ODYSSEY for constructing verifiable, local truth-preserving foundation models as compositions of foundries:

arXiv:2605.17152v1 Announce Type: new Abstract: Multimodal LLMs are evolving from vision-language to tri-modality that see, hear, and read, yet pipelines and benchmarks remain English-centric and comp

arXiv:2604.24041v1 Announce Type: cross Abstract: Partially-observed time series (POTS) is ubiquitous in real-world applications, yet most existing toolchains separate missing-value handling from down

arXiv:2604.11507v1 Announce Type: cross Abstract: Artificial intelligence (AI) is moving increasingly beyond prediction to support decisions in complex, uncertain, and dynamic environments. This shift

arXiv:2604.08920v1 Announce Type: cross Abstract: Information retrieval systems have traditionally optimized for topical relevance-the degree to which retrieved documents match a query. However, relev

arXiv:2610.16919v1 Announce Type: cross Abstract: Machine learning engineering (MLE) agents are emerging as a new paradigm for automating end-to-end ML pipeline development. Using large language model

arXiv:2610.01284v1 Announce Type: cross Abstract: Model validation estimates the performance of a complete learning procedure on new data. However, an invalid split can produce an optimistic and stabl

arXiv:2609.39843v1 Announce Type: cross Abstract: Density estimation is a fundamental problem in statistics and machine learning. In this work, we introduce BayesNDE, a neural density estimator based

arXiv:2609.30798v1 Announce Type: new Abstract: Real-time voice agents have moved from research prototypes to production deployments, yet the literature describing them is fragmented across three comm

arXiv:2609.30050v1 Announce Type: new Abstract: We present NNV3, the latest version of the Neural Network Verification (NNV) tool, a MATLAB framework for formal verification of deep learning models an

arXiv:2604.02401v2 Announce Type: replace Abstract: This paper revisits three backup-based safety filters -- Backup Control Barrier Functions (Backup CBF), Model Predictive Shielding (MPS), and gateke

arXiv:2609.19617v1 Announce Type: cross Abstract: Business analytics education requires diverse datasets to support different learning objectives, student backgrounds, and analytical tasks. Real-world

arXiv:2609.18338v1 Announce Type: cross Abstract: Adaptive security at the network edge increasingly relies on automated planners, including rule-based controllers, learned policies, and LLM-assisted

arXiv:2609.17325v1 Announce Type: new Abstract: Biological cells can be viewed as individual, interacting agents whose collective dynamics give rise to adaptive behaviour at multiple levels of organis

arXiv:2609.11382v1 Announce Type: new Abstract: Aerial robot swarms have the potential to transform time-critical safety, security, and search-and-rescue operations. By coordinating multiple robots, t

arXiv:2609.05583v1 Announce Type: new Abstract: Vision-Language Models (VLMs) are reshaping computer vision by aligning visual and textual embeddings, allowing models to recognize visual concepts and

arXiv:2609.03718v1 Announce Type: cross Abstract: Computer-aided engineering (CAE) simulation is among the largest and most demanding areas of engineering, where setting up a solver such as OpenFOAM,

arXiv:2608.21631v1 Announce Type: new Abstract: Trajectory optimization computes dynamically feasible motions that enable autonomous systems to accomplish complex tasks while satisfying operational an

arXiv:2607.05644v1 Announce Type: cross Abstract: Natural language processing (NLP) is a common method for supplying data to clinical research and decision making by extracting information from electr

arXiv:2602.11103v2 Announce Type: replace Abstract: Despite rapid progress on coding agents, progress on their multimodal counterparts has lagged behind. A key challenge is the scarcity of evaluation

arXiv:2606.31334v1 Announce Type: new Abstract: Joint OFDM-RIS optimization for 6G is a mixed-integer nonlinear programming (MINLP) problem covering sum-rate maximization, energy efficiency, max-min f

arXiv:2606.27234v1 Announce Type: cross Abstract: AI nudification uses generative models to create synthetic non-consensual sexually explicit imagery (SNEACI) of real individuals. Prior work has exami

arXiv:2507.07920v2 Announce Type: replace-cross Abstract: Cerebrovascular research heavily relies on quantitative analysis of intracranial arteries from time-of-flight magnetic resonance angiography,

arXiv:2512.03719v2 Announce Type: replace-cross Abstract: Over-the-Air Federated Learning (AirFL) is an emerging paradigm that tightly integrates wireless signal processing and distributed machine lea

arXiv:2606.11560v1 Announce Type: cross Abstract: Large Language Models (LLMs) have advanced rapidly, but their limitations in structured and multi-hop reasoning underscore the need for graph-native,

arXiv:2602.19066v2 Announce Type: replace-cross Abstract: Diffusion Language Models (DLMs) have recently achieved strong results in text generation. However, their multi-step sampling leads to slow in

arXiv:2605.24539v1 Announce Type: new Abstract: Agent harness evolution improves frozen language-model agents by modifying the executable structures around them. We study this paradigm as a form of sa

arXiv:2605.25773v1 Announce Type: cross Abstract: Efficient benchmarking techniques aim to lower the computational cost of evaluating LLMs by predicting full benchmark scores using only a subset of a

arXiv:2603.01655v2 Announce Type: replace Abstract: Ray tracing has become a standard for accurate radio propagation modeling, but suffers from exponential computational complexity, as the number of c

arXiv:2410.18856v4 Announce Type: replace Abstract: Frontier large language models (LLMs), such as GPT-5, Claude 4.5, Gemini 3, Llama 4, and DeepSeek-R1, represent a transformative class of AI tools c

arXiv:2505.17352v2 Announce Type: replace Abstract: Diffusion models have become a central paradigm for image and multimodal generation, yet their deployment raises persistent questions about alignmen

arXiv:2605.17804v1 Announce Type: new Abstract: Generative models have demonstrated remarkable potential in time series analysis tasks, like synthesis, forecasting, imputation, etc. However, offering

arXiv:2605.15647v1 Announce Type: new Abstract: Edge machine learning presents a unique set of constraints not encountered in cloud-scale model deployment: strict memory budgets, limited compute, and

arXiv:2605.14747v1 Announce Type: cross Abstract: Recent advances in multimodal large language models have driven growing interest in graphical user interface (GUI) agents, yet their generalization re

arXiv:2605.04722v1 Announce Type: new Abstract: Input Convex Neural Networks (ICNNs) are commonly used in a two-stage manner: one first trains a convex network and then minimizes it over its input in

arXiv:2605.03412v1 Announce Type: cross Abstract: Passive Acoustic Monitoring (PAM) is an efficient and non-invasive method for surveying ecosystems at a reduced cost. Typically, autonomous recorders

arXiv:2604.05081v2 Announce Type: replace Abstract: We introduce MedGemma 1.5 4B, the latest model in the MedGemma collection. MedGemma 1.5 expands on MedGemma 1 by integrating additional capabilities

arXiv:2604.17460v2 Announce Type: replace-cross Abstract: AI coding assistants have proliferated rapidly, yet structured pedagogical frameworks for learning these tools remain scarce. Developers face

arXiv:2604.17667v1 Announce Type: new Abstract: Peer review is central to scientific publishing, yet reviewers frequently include claims that are subjective, rhetorical, or misaligned with the submitt

arXiv:2604.18481v1 Announce Type: cross Abstract: This paper is a step-by-step, self-contained guide to the complete training cycle of a Physics-Informed Neural Network (PINN) -- a topic that existing

arXiv:2512.12642v2 Announce Type: replace Abstract: Torch Geometric Pool (tgp) is a pooling library built on top of PyTorch Geometric. Graph pooling methods differ in how they assign nodes to supernod

arXiv:2604.13977v1 Announce Type: new Abstract: Synthetic data is a standard component in training large language models, yet systematic comparisons across design dimensions, including rephrasing stra