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arXiv:2602.17395v1 Announce Type: new Abstract: Generalized Category Discovery (GCD) aims to identify novel categories in unlabeled data while leveraging a small labeled subset of known...
arXiv:2602.17397v1 Announce Type: new Abstract: In recent years, significant advances in computer vision have also propelled progress in remote sensing. Concurrently, the use of drones...
arXiv:2602.17402v1 Announce Type: new Abstract: Predicting survival outcomes for non-small cell lung cancer (NSCLC) patients is challenging due to the different individual prognostic features. This...
arXiv:2602.17407v1 Announce Type: new Abstract: Phased-array Bluetooth systems have emerged as a low-cost alternative for performing aided inertial navigation in GNSS-denied use cases such as...
arXiv:2602.17410v1 Announce Type: new Abstract: Large language models (LLMs) have shown great promise in recommender systems, where supervised fine-tuning (SFT) is commonly used for adaptation....
arXiv:2602.17413v1 Announce Type: new Abstract: In current inter-organizational data spaces, usage policies are enforced mainly at the asset level: a whole document or dataset is...
arXiv:2602.17415v1 Announce Type: new Abstract: We present a decentralized, agent agnostic, and safety-aware control framework for human-robot collaboration based on Virtual Model Control (VMC). In...
arXiv:2602.17418v1 Announce Type: new Abstract: Children are increasingly using technologies powered by Artificial Intelligence (AI). However, there are growing concerns about privacy risks, particularly for...
arXiv:2602.17419v1 Announce Type: new Abstract: Industrial anomaly detection is important for smart manufacturing, but many deep learning approaches produce only binary decisions and provide limited...
arXiv:2602.17421v1 Announce Type: new Abstract: Additive manufacturing is enabling soft robots with increasingly complex geometries, creating a demand for sensing solutions that remain compatible with...
arXiv:2602.17423v1 Announce Type: new Abstract: We investigate the convergence guarantee of two-layer neural network training with Gaussian randomly masked inputs. This scenario corresponds to Gaussian...
arXiv:2602.17424v1 Announce Type: new Abstract: Cross-document coreference resolution (CDCR) identifies and links mentions of the same entities and events across related documents, enabling content analysis...
arXiv:2602.17425v1 Announce Type: new Abstract: Evaluating machine translation (MT) quality in extremely low-resource language (ELRL) scenarios poses unique challenges, as widely used metrics such as...
arXiv:2602.17426v1 Announce Type: new Abstract: Self-adaptive systems increasingly operate in close interaction with humans, often sharing the same physical or virtual environments and making decisions...
arXiv:2602.17431v1 Announce Type: new Abstract: Uncertainty quantification has emerged as an effective approach to closed-book hallucination detection for LLMs, but existing methods are largely designed...
arXiv:2602.17433v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used as sources of historical information, motivating the need for scalable audits on contested...
arXiv:2602.17434v1 Announce Type: new Abstract: Multi-agent planning under Signal Temporal Logic (STL) is often hindered by collaborative tasks that lead to computational challenges due to...
arXiv:2602.17442v1 Announce Type: new Abstract: Innovation in Recommender Systems is currently impeded by a fractured ecosystem, where researchers must choose between the ease of in-memory...
arXiv:2602.17443v1 Announce Type: new Abstract: Evaluating the strategic reasoning capabilities of Large Language Models (LLMs) requires moving beyond static benchmarks to dynamic, multi-turn interactions. We...
arXiv:2602.17445v1 Announce Type: new Abstract: Multiple-choice question (MCQ) benchmarks have been a standard evaluation practice for measuring LLMs' ability to reason and answer knowledge-based questions....
arXiv:2602.17448v1 Announce Type: new Abstract: To meet the ever-increasing demands of the cybersecurity workforce, AI tutors have been proposed for personalized, scalable education. But, while...
arXiv:2602.17449v1 Announce Type: new Abstract: Machine learning training places immense demands on cluster networks, motivating specialized architectures and co-design with parallelization strategies. Recent designs incorporating...
arXiv:2602.17450v1 Announce Type: new Abstract: Web research and practices have evolved significantly over time, offering users diverse and accessible solutions across a wide range of...
arXiv:2602.17452v1 Announce Type: new Abstract: We present Jolt Atlas, a zero-knowledge machine learning (zkML) framework that extends the Jolt proving system to model inference. Unlike...