Knowledge catalogue
arXiv:2609.23085v1 Announce Type: cross Abstract: Large language models (LLMs) and agentic AI systems are creating rapidly growing inference energy demands as model sizes grow and reasoning trajectori
arXiv:2502.01562v3 Announce Type: replace Abstract: As the general capabilities of artificial intelligence (AI) agents continue to evolve, their ability to learn to master multiple complex tasks throu
arXiv:2609.23797v1 Announce Type: cross Abstract: Human motion is shaped by both external acoustic events and behavioral intent: spatial audio conveys environmental cues that elicit or guide a respons
arXiv:2509.00754v3 Announce Type: replace Abstract: Dempster--Shafer theory (DST) provides an attractive framework for multi-source information fusion. However, its effectiveness critically depends on
arXiv:2609.24517v1 Announce Type: cross Abstract: Model merging aims to combine multiple fine-tuned models derived from a common pretrained model into a single multi-task model without additional join
arXiv:2609.23055v1 Announce Type: new Abstract: Discrete diffusion models now match autoregressive language models on several benchmarks, while the question of how best to train them has received far
arXiv:2609.23157v1 Announce Type: cross Abstract: Aerial Reconfigurable Intelligent Surfaces (ARISs) can enhance wireless connectivity in obstructed environments by combining reconfigurable metasurfac
arXiv:2609.24338v1 Announce Type: new Abstract: An Intraoperative Hypotension (IOH) event is a frequent complication during administration of general anaesthesia with serious downstream consequences,
arXiv:2503.12083v3 Announce Type: replace-cross Abstract: Current Deep Neural Network (DNN) verifiers are typically designed to prioritize scalability over reliability. Reliability can be reinforced t
arXiv:2609.24569v1 Announce Type: cross Abstract: Over the past decade, a growing body of research has shown that gamma-weak submodularity broadly arises in numerous subset selection tasks, including
arXiv:2609.24370v1 Announce Type: cross Abstract: Self-attention is central to modern Transformer architectures, but its dense dot-product formulation makes it difficult to identify which internal dir
arXiv:2609.22879v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have emerged as a powerful paradigm for embodied intelligence, but fine-tuning them with reinforcement learning (RL)
arXiv:2609.22112v1 Announce Type: new Abstract: Large language models (LLMs) have demonstrated the ability to generate user-specific text with high stylistic fidelity. However, the personal data that
arXiv:2609.23845v1 Announce Type: new Abstract: Decentralised federated learning removes the aggregation server but makes collaboration dependent on transient peer availability. In mobile and intermit
arXiv:2609.23386v1 Announce Type: new Abstract: Text-guided 3D building generation holds tremendous application potential, yet existing generative models typically output inseparable single meshes or
arXiv:2609.23449v1 Announce Type: cross Abstract: Memory systems are becoming a core component of LLM agents, but constructing and maintaining memory remains expensive because it relies on repeated ca
Someone recommended that I try the ByteShape Qwen 3.8 27B IQ3-XXS GGUF after seeing my previous testing of the GSQ quant. So I did. And the result was… surprisingly bad. For context, I'm running: RTX
arXiv:2609.22587v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models commonly predict action chunks, limiting their ability to react to environmental changes during execution. Existing
arXiv:2607.14293v2 Announce Type: replace-cross Abstract: Ionizing radiation from cosmic rays and gammas can induce discontinuous jumps in the environmental charge of superconducting qubits (charge ju
Recommended if you work on agent memory. Retrieval is the hardest memory problem in most harnesses because agents keep pulling stale context. AML tests this with a coding track of 150 software tasks,
arXiv:2406.03678v2 Announce Type: replace Abstract: On-policy reinforcement learning methods, like Trust Region Policy Optimization (TRPO) and Proximal Policy Optimization (PPO), often demand extensiv
arXiv:2609.24750v1 Announce Type: cross Abstract: The growing demand for real-time, data-driven decision-making in complex and dynamic systems is placing increasing pressure on traditional Operational
arXiv:2609.23555v1 Announce Type: cross Abstract: Neural video representations (NVRs) represent videos using neural network parameters and, in hybrid formulations, frame-wise latent embeddings. Althou
arXiv:2609.24850v1 Announce Type: new Abstract: Computing accurate geometry from multi-view images is a fundamental problem in computer vision. Recent feed-forward (FF) models jointly estimate 3D geom
arXiv:2609.22678v1 Announce Type: cross Abstract: Density-Driven Optimal Control (D2OC) provides an effective framework for steering multi-agent systems toward prescribed spatial distributions. Howeve
arXiv:2609.23280v1 Announce Type: new Abstract: Safety-critical control under uncertainty requires uncertainty representations that are both statistically valid (for certifiable performance) and compa
arXiv:2609.22576v1 Announce Type: cross Abstract: Semidefinite programming (SDP) certificates for feedback systems containing deep neural networks (NNs) typically scale with the total number of neuron
arXiv:2609.24497v1 Announce Type: new Abstract: Real-time motion planning remains challenging in large and high-dimensional environments. Prior acceleration of RRT* follows tree-centric state organiza
arXiv:2609.23263v1 Announce Type: new Abstract: Temporal logic is a formal language for reasoning about system behaviors over time. Signal temporal logic (STL), in particular, has been used to encode
arXiv:2505.14468v2 Announce Type: replace Abstract: Multi-LoRA (Low-Rank Adaptation) serving allows many specialized LLM variants to share the same base model by attaching lightweight adapters. This m
arXiv:2609.23456v1 Announce Type: new Abstract: High-precision positioning using the global navigation satellite system (GNSS) embedded in smartphones is demanded for sidewalk-level pedestrian navigat
arXiv:2609.22126v1 Announce Type: cross Abstract: High-resolution surface solar radiation (SSR) is important for solar forecasting and grid operation. However, physically consistent reanalysis product
arXiv:2609.23248v1 Announce Type: new Abstract: A fundamental challenge in deploying vision models is domain shift, which arises when training and test data follow different distributions, leading to
arXiv:2609.23643v1 Announce Type: new Abstract: Autonomous navigation of unmanned aerial vehicles in constrained three-dimensional environments has been a challenge in the robotics domain. The applica
arXiv:2609.22128v1 Announce Type: cross Abstract: The wrist plays a critical role in upper-limb function by enabling precise hand positioning, force regulation, and object manipulation. Continuous bra
arXiv:2609.22534v1 Announce Type: cross Abstract: Strategic classification studies how a decision maker should choose a classifier when the agents being classified can adjust their features in respons
arXiv:2609.23483v1 Announce Type: new Abstract: Humanoid loco-manipulation faces two prominent limitations: controllers using continuous velocity commands cannot precisely regulate individual foothold
arXiv:2609.22392v1 Announce Type: new Abstract: Image steganography hides secret message within normal images, with most existing works relying on cover-preserving transmission. However, such a paradi
arXiv:2108.11204v4 Announce Type: replace-cross Abstract: Humans excel in solving complex reasoning tasks through a mental process of moving from one idea to a related one. Inspired by this, we propos
arXiv:2407.16139v2 Announce Type: replace Abstract: Federated Learning (FL) faces challenges due to data heterogeneity, which limits the global model's performance across diverse client distributions.
arXiv:2609.23151v1 Announce Type: cross Abstract: Assembly remains a challenging robotic manipulation task in presence of tight tolerances and complex contact interactions. While Learning from Demonst
arXiv:2609.22221v1 Announce Type: new Abstract: Large language models (LLMs) can generate fluent and coherent text that is increasingly difficult to distinguish from human writing, motivating the deve
arXiv:2609.22805v1 Announce Type: new Abstract: Natural language generation (NLG) tasks span the spectrum of conditional entropy, ranging from highly constrained machine translation to open-ended dial
arXiv:2609.22292v1 Announce Type: cross Abstract: Unmanned aerial vehicle (UAV) swarms deployed in mission-critical applications must simultaneously track a mobile aerial target and maintain reliable
arXiv:2512.07419v3 Announce Type: replace-cross Abstract: Mixed-Precision Quantization (MPQ) liberates Deep Neural Networks (DNNs) from the Out-Of-Memory (OOM) bottleneck and has garnered increasing r
arXiv:2406.03894v2 Announce Type: replace Abstract: Proximal Policy Optimization (PPO) is a popular model-free reinforcement learning algorithm, esteemed for its simplicity and efficacy. However, due
arXiv:2606.17317v2 Announce Type: replace Abstract: Autonomous capture of a tumbling object with a space manipulator requires trajectory generation under real-time onboard constraints. However, couple
arXiv:2403.01805v2 Announce Type: replace-cross Abstract: Shannon entropy regularization is widely adopted in optimal control due to its ability to promote exploration and enhance robustness, e.g., ma
arXiv:2609.24289v1 Announce Type: new Abstract: As Large Language Model (LLM) agents are applied in continuously interactive environments, driving the evolution of their own capabilities becomes a cor
arXiv:2609.24049v1 Announce Type: new Abstract: Accurate retinal vessel segmentation is important for computer-aided ophthalmic analysis, yet thin vessels, low contrast, and severe foreground-backgrou
arXiv:2609.23169v1 Announce Type: new Abstract: High-quality texture generation is essential for creating realistic and production-ready 3D assets. Recent multi-view diffusion methods have shown promi
arXiv:2609.24579v1 Announce Type: new Abstract: Event logs arise in a wide range of real-world processes, capturing not only event activities and timestamps but also multi-modal contextual information
arXiv:2609.24372v1 Announce Type: new Abstract: In-context learning (ICL) based on large language models (LLMs) has shown promising potential in alleviating performance bottlenecks caused by the limit
arXiv:2609.24997v1 Announce Type: new Abstract: Recent advances in video generative models have enabled high-fidelity, temporally coherent video generation. However, these models often struggle to sat
arXiv:2609.23372v1 Announce Type: new Abstract: Accurate multi-user localization is challenging in complex urban environments, where wireless measurements can become ambiguous under noise, blockage, a
arXiv:2307.00852v3 Announce Type: replace Abstract: The natural language generation domain has witnessed great success thanks to Transformer models. Although they have achieved state-of-the-art genera
arXiv:2609.24028v1 Announce Type: new Abstract: Generating coherent meta-reviews from multiple peer reviews is challenging when reviewer evidence conflicts and varies in reliability. Existing approach
arXiv:2607.18840v2 Announce Type: replace Abstract: World Action Models (WAMs) offer a promising paradigm for robotic manipulation by jointly modeling visual state transitions and robot actions. Howev
arXiv:2609.21044v1 Announce Type: new Abstract: Covariate-rich time-series forecasting requires deciding how external variables enter the target forecasting path. Existing Transformer-based forecaster
arXiv:2609.21718v1 Announce Type: new Abstract: Fully autonomous tractor--trailer systems are increasingly deployed in logistics, agriculture, and industrial environments, where precise and robust pat