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arXiv:2502.05376v2 Announce Type: replace Abstract: Post-training quantization (PTQ) is a promising approach to reducing the storage and computational requirements of large language models (LLMs) without...
arXiv:2502.09980v4 Announce Type: replace Abstract: Current autonomous driving vehicles rely mainly on their individual sensors to understand surrounding scenes and plan for future trajectories, which...
arXiv:2502.10295v3 Announce Type: replace Abstract: From a variational perspective, many statistical learning criteria involve seeking a distribution that balances empirical risk and regularization. In this...
arXiv:2502.13286v2 Announce Type: replace Abstract: Online trajectory planning enables robot manipulators to react quickly to changing environments or tasks. Many robot trajectory planners exist for...
arXiv:2502.14560v4 Announce Type: replace Abstract: Direct Preference Optimization (DPO) has emerged as a promising approach for aligning large language models with human preferences. While prior...
arXiv:2502.16730v2 Announce Type: replace Abstract: We present RapidPen, a fully automated penetration testing (pentesting) framework that addresses the challenge of achieving an initial foothold (IP-to-Shell)...
arXiv:2502.17315v2 Announce Type: replace Abstract: Tabular data contains rich structural semantics and plays a crucial role in organizing and manipulating information. Recent methods employ Multi-modal...
arXiv:2502.20326v2 Announce Type: replace Abstract: This paper presents the first end-to-end framework that combines guidance, navigation, and centralised task allocation for multiple UAVs performing autonomous...
arXiv:2503.00187v3 Announce Type: replace Abstract: Large language models (LLMs) are shown to be vulnerable to jailbreaking attacks where adversarial prompts are designed to elicit harmful...
arXiv:2503.00632v2 Announce Type: replace Abstract: Improving social welfare is a complex challenge requiring policymakers to optimize objectives across multiple time horizons. Evaluating the impact of...
arXiv:2503.01884v2 Announce Type: replace Abstract: In this paper, we apply quantum machine learning (QML) to predict the stock prices of multiple assets using a contextual...
arXiv:2503.04641v3 Announce Type: replace Abstract: Understanding and replicating the real world is a critical challenge in Artificial General Intelligence (AGI) research. To achieve this, many...
arXiv:2503.08796v2 Announce Type: replace Abstract: We introduce Robust Multi-Objective Decoding (RMOD), a novel inference-time algorithm that robustly aligns Large Language Models (LLMs) to multiple human...
arXiv:2503.09027v2 Announce Type: replace Abstract: Temporally localizing user-queried events through natural language is a crucial capability for video models. Recent methods predominantly adapt video LLMs...
arXiv:2503.09411v2 Announce Type: replace Abstract: The learning rate in stochastic gradient methods is a critical hyperparameter that is notoriously costly to tune via standard grid...
arXiv:2503.10522v3 Announce Type: replace Abstract: Audio and music generation based on flexible multimodal control signals is a widely applicable topic, with the following key challenges:...
arXiv:2503.10568v3 Announce Type: replace Abstract: We introduce ARPG, a novel visual autoregressive model that enables randomized parallel generation, addressing the inherent limitations of conventional raster-order...
arXiv:2503.12385v2 Announce Type: replace Abstract: Fine-grained visual categorization (FGVC) is a challenging but significant task in computer vision, which aims to recognize different sub-categories of...
arXiv:2503.13194v3 Announce Type: replace Abstract: The ability of artificial intelligence agents to make optimal decisions and generalise them to different domains and tasks is compromised...
arXiv:2504.06193v3 Announce Type: replace Abstract: Link prediction is a crucial graph-learning task with applications including citation prediction and product recommendation. Distilling Graph Neural Networks (GNNs)...
arXiv:2504.07667v2 Announce Type: replace Abstract: The generalization of learning-based high dynamic range (HDR) fusion is often limited by the availability of training data, as collecting...
arXiv:2504.09733v3 Announce Type: replace Abstract: Accurately estimating decision boundaries in black box systems is critical when ensuring safety, quality, and feasibility in real-world applications. However,...
arXiv:2504.13335v2 Announce Type: replace Abstract: Harmonic generation plays a crucial role in contrast-enhanced ultrasound, both for imaging and therapeutic applications. However, accurately capturing these nonlinear...
arXiv:2504.14326v2 Announce Type: replace Abstract: Mobile metaverses are envisioned as a transformative digital ecosystem that delivers immersive, intelligent, and ubiquitous services through mobile devices. Driven...