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arXiv:2410.03481v4 Announce Type: replace Abstract: In this paper, we introduce a sensor designed for integration in robot fingers, where it can provide information on the...
arXiv:2410.04779v3 Announce Type: replace Abstract: Neural fields are an emerging paradigm that represent data as continuous functions parameterized by neural networks. Despite many advantages, neural...
arXiv:2410.23222v2 Announce Type: replace Abstract: Recent advancements in foundation models have been successfully extended to the time series (TS) domain, facilitated by the emergence of...
arXiv:2411.06158v4 Announce Type: replace Abstract: Approximate $k$-nearest neighbor (AKNN) search is a fundamental problem with wide applications. To reduce memory and accelerate search, vector quantization...
arXiv:2411.06501v3 Announce Type: replace Abstract: We study the regret in stochastic Multi-Armed Bandits (MAB) with multiple agents that communicate over an arbitrary connected communication graph....
arXiv:2411.12992v2 Announce Type: replace Abstract: In order to reduce the computational complexity of large language models, great efforts have been made to to improve the...
arXiv:2411.14349v3 Announce Type: replace Abstract: We consider the problem of learning an arbitrarily-biased ReLU activation (or neuron) over Gaussian marginals with the squared loss objective....
arXiv:2501.01062v2 Announce Type: replace Abstract: DAG-based BFT consensus has attracted growing interest in distributed data management systems for consistent replication in untrusted settings due to...
arXiv:2501.02770v5 Announce Type: replace Abstract: This paper proposes a novel planning framework to handle a multi-agent pathfinding problem under team-connected communication constraint, where all agents...
arXiv:2501.15280v2 Announce Type: replace Abstract: Recent work demonstrates that filtering harmful content from pretraining data improves model safety without degrading capabilities. We propose a natural...
arXiv:2501.18533v3 Announce Type: replace Abstract: Large Vision-Language Models (VLMs) have achieved remarkable performance across a wide range of tasks. However, their deployment in safety-critical domains...
arXiv:2502.01177v2 Announce Type: replace Abstract: Deep graph learning focuses on flexible and generalizable models that learn patterns in an automated fashion. Network science focuses on...
arXiv:2502.02542v3 Announce Type: replace Abstract: Most flagship language models generate explicit reasoning chains, enabling inference-time scaling. However, producing these reasoning chains increases token usage (i.e.,...
arXiv:2502.05743v4 Announce Type: replace Abstract: Diffusion models, though originally designed for generative tasks, have demonstrated impressive self-supervised representation learning capabilities. A particularly intriguing phenomenon in...
arXiv:2502.07077v3 Announce Type: replace Abstract: The tendency of users to anthropomorphise large language models (LLMs) is of growing interest to AI developers, researchers, and policy-makers....
arXiv:2502.08841v3 Announce Type: replace Abstract: Illegal content on social media poses significant societal harm and necessitates timely removal. However, the impact of the speed of...
arXiv:2502.14782v2 Announce Type: replace Abstract: Coastal regions and river floodplains are particularly vulnerable to the impacts of extreme weather events. Accurate real-time forecasting of hydrodynamic...
arXiv:2502.16667v3 Announce Type: replace Abstract: Scalable and generalizable physics-aware deep learning has long been considered a significant challenge with various applications across diverse domains ranging...
arXiv:2502.18179v4 Announce Type: replace Abstract: This paper defines and explores the design space for information extraction (IE) from layout-rich documents using large language models (LLMs)....
arXiv:2503.00227v4 Announce Type: replace Abstract: This work introduces a unified framework for analyzing games in greater depth. In the existing literature, players' strategies are typically...
arXiv:2503.11294v2 Announce Type: replace Abstract: Efficiently representing supply and demand curves is vital for energy market analysis and downstream modelling; however, dimensionality reduction often produces...
arXiv:2503.11717v3 Announce Type: replace Abstract: Model Predictive Path Integral (MPPI) control is a widely used sampling-based approach for real-time control, valued for its flexibility in...
arXiv:2503.12968v2 Announce Type: replace Abstract: Accurate 3D multi-object tracking (MOT) is crucial for autonomous driving, as it enables robust perception, navigation, and planning in complex...
arXiv:2503.13745v3 Announce Type: replace Abstract: Video super-resolution (VSR) aims to enhance low-resolution videos by leveraging both spatial and temporal information. While deep learning has led...