arXiv:2605.03964v1 Announce Type: new
Abstract: Training machine learning interatomic potentials (MLIPs) for reactive chemistry is often bottlenecked by the high cost of quantum chemical labels and the scarcity of transition state configurations in ca…
arXiv:2511.18772v2 Announce Type: replace-cross
Abstract: Deep neural networks (DNNs) have become valuable intellectual property of model owners, due to the substantial resources required for their development. To protect these assets in the deployed …
arXiv:2401.12783v3 Announce Type: replace
Abstract: Background: Photoplethysmography (PPG) is a non-invasive optical sensing technique widely used to capture hemodynamic information, with broad deployment in both clinical monitoring systems and wearab…
arXiv:2408.12622v3 Announce Type: replace
Abstract: Artificial intelligence (AI) is reshaping society, from video generation to medical diagnosis, coding agents to autonomous vehicles. Yet researchers, policymakers, and technology companies lack share…
arXiv:2602.00933v2 Announce Type: replace-cross
Abstract: The Model Context Protocol (MCP) is rapidly becoming the standard interface for Large Language Models (LLMs) to discover and invoke external tools. However, existing evaluations often fail to c…
arXiv:2605.01790v1 Announce Type: cross
Abstract: A common design pattern in high-quality music generation is to handle structure and fidelity in different representation spaces: a generator first models high-level structure, followed by diffusion-bas…
arXiv:2605.01809v1 Announce Type: cross
Abstract: Unified audio-visual generation is rapidly gaining industrial and creative relevance, enabling applications in virtual production and interactive media. However, when moving from general audio-video sy…
arXiv:2603.18196v3 Announce Type: replace-cross
Abstract: Investigating cybersecurity incidents requires collecting and analyzing evidence from multiple log sources, including intrusion detection alerts, network traffic records, and authentication eve…
arXiv:2605.01834v1 Announce Type: cross
Abstract: Contrastive learning (CL) reduces annotation cost via auto-derived supervisory signals. Since large-scale in-house CL datasets are infeasible, reliance on third-party or internet data is common. Recent…
arXiv:2604.09111v4 Announce Type: replace-cross
Abstract: Recently, artificial intelligence-based dubbing technology has advanced, enabling automated dubbing (AD) to convert the source speech of a video into target speech in different languages. Howev…