Stay updated with the latest research and technology news
arXiv:2602.21824v1 Announce Type: new Abstract: Effective document intelligence models rely on large amounts of annotated training data. However, procuring sufficient and high-quality data poses significant...
arXiv:2602.21826v1 Announce Type: new Abstract: A large number of URLs are made public by various platforms for security analysis, archiving, and paste sharing -- such...
arXiv:2602.21827v1 Announce Type: new Abstract: We study the problem of preemptively scheduling jobs online over time on a single machine to minimize the total flow...
arXiv:2602.21829v1 Announce Type: new Abstract: Visual storytelling models that correctly ground entities in images may still hallucinate semantic relationships, generating incorrect dialogue attribution, character interactions,...
arXiv:2602.21831v1 Announce Type: new Abstract: AI is increasingly being used to assist fraud and cybercrime. However, it is unclear whether current large language models can...
arXiv:2602.21833v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for automated code refactoring tasks. Although these models can quickly refactor code, the...
arXiv:2602.21835v1 Announce Type: new Abstract: Video foundation models aim to integrate video understanding, generation, editing, and instruction following within a single framework, making them a...
arXiv:2602.21841v1 Announce Type: new Abstract: Federated Learning (FL) has emerged as a key paradigm for building Trustworthy AI systems by enabling privacy-preserving, decentralized model training....
arXiv:2602.21844v1 Announce Type: new Abstract: Differentially private federated learning faces a fundamental tension: privacy protection mechanisms that safeguard client data simultaneously create quantifiable privacy costs...
arXiv:2602.21845v1 Announce Type: new Abstract: Counterfactual explanation (CE) is an important domain within post-hoc explainability. However, the explanations generated by most CE generators are often...
arXiv:2602.21849v1 Announce Type: new Abstract: Deep learning-based watermarking has made remarkable progress in recent years. To achieve robustness against various distortions, current methods commonly adopt...
arXiv:2602.21852v1 Announce Type: new Abstract: Reinforcement learning for traffic signal control is bottlenecked by simulators: training in SUMO takes hours, reproducing results often requires days...
arXiv:2602.21854v1 Announce Type: new Abstract: As multimodal large language models (MLLMs) advance in handling interleaved image-text data, assessing their few-shot learning capabilities remains an open...
arXiv:2602.21855v1 Announce Type: new Abstract: Accurate annotation of endoscopic videos is essential yet time-consuming, particularly for challenging datasets such as dysplasia in Barrett's esophagus, where...
arXiv:2602.21857v1 Announce Type: new Abstract: Complex claim verification requires decomposing sentences into verifiable subclaims, yet existing methods struggle to align decomposition quality with verification performance....
arXiv:2602.21858v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) have made significant progress in mobile agent development, yet their capabilities are predominantly confined to...
arXiv:2602.21862v1 Announce Type: new Abstract: Since individuals may struggle to recall all life details and often confuse events, establishing a system to assist users in...
arXiv:2602.21864v1 Announce Type: new Abstract: Vision-Language Models (VLMs) have emerged as versatile solutions for zero-shot question answering (QA) across various domains. However, enabling VLMs to...
arXiv:2602.21868v1 Announce Type: new Abstract: This technical note proposes a novel airspace complexity metric that quantifies the air traffic controller workload and coordination effort for...
arXiv:2602.21873v1 Announce Type: new Abstract: Federated learning (FL) facilitates the secure utilization of decentralized images, advancing applications in medical image recognition and autonomous driving. However,...
arXiv:2602.21874v1 Announce Type: new Abstract: A user-centered AR interface for disaster response is presented in this work that uses 3D Gaussian Splatting (3DGS) to visualize...
arXiv:2602.21877v1 Announce Type: new Abstract: Image memorability, i.e., how likely an image is to be remembered, has traditionally been studied in computer vision either as...
arXiv:2602.21887v1 Announce Type: new Abstract: Current large reasoning models (LRMs) have shown strong ability on challenging tasks after reinforcement learning (RL) based post-training. However, previous...
arXiv:2602.21889v1 Announce Type: new Abstract: Across a growing number of fields, human decision making is supported by predictions from AI models. However, we still lack...