Knowledge catalogue
arXiv:2512.09269v2 Announce Type: replace Abstract: Inferring the eventual goal of a mobile agent from noisy observations of its trajectory is a fundamental estimation problem. We initiate the study o
arXiv:2605.17812v1 Announce Type: new Abstract: Vertical AI firms in accounting, law, healthcare, procurement, and similar domains historically bundled workflow, domain logic, and accountability into
arXiv:2511.08154v2 Announce Type: replace-cross Abstract: We revisit the fermion mass problem of the SU(5) grand unified theory using machine learning techniques. The original SU(5) model proposed by
arXiv:2605.16435v1 Announce Type: cross Abstract: Heatwaves are an important problem in cities, and climate change makes this problem more difficult. In this paper, we present a GPU-based deep learnin
arXiv:2506.14009v2 Announce Type: replace Abstract: Autonomous drones capable of interpreting and executing high-level language instructions in unstructured environments remain a long-standing goal. Y
arXiv:2512.22473v5 Announce Type: replace-cross Abstract: Transformers empirically perform precise probabilistic reasoning in carefully constructed ``Bayesian wind tunnels'' and in large-scale languag
arXiv:2602.07884v2 Announce Type: replace-cross Abstract: Survival analysis is complicated by censored data, high-dimensional features, and non-linear interactions. Classical models offer interpretabi
arXiv:2508.02383v2 Announce Type: replace Abstract: Spectral graph embedding plays a critical role in graph representation learning by generating low-dimensional vector representations from graph spec
arXiv:2605.18387v1 Announce Type: cross Abstract: Graph Neural Networks (GNNs) and Graph Transformers (GTs) are now a fundamental paradigm for graph learning, combining the representation-learning cap
arXiv:2605.17343v1 Announce Type: new Abstract: Computed tomography (CT) metal artifact reduction (MAR) aims to reduce the severe streaking artifacts induced by metallic implants and other high-densit
arXiv:2605.17617v1 Announce Type: new Abstract: Complex operational workflows coordinating personnel, tools, and information are central to enterprise operations, yet end-to-end automation remains cha
arXiv:2511.19078v2 Announce Type: replace-cross Abstract: Large language models (LLMs) have demonstrated impressive capabilities in natural language understanding and generation, including multi-step
arXiv:2605.16598v1 Announce Type: cross Abstract: Agentic retrieval improves multi-hop question answering by giving language models autonomy to iteratively gather evidence. Recent work augments these
arXiv:2605.17727v1 Announce Type: new Abstract: Frozen vision-language embeddings contain signals at multiple semantic resolutions, from object identity to attributes, relations, and full-caption mean
arXiv:2605.16668v1 Announce Type: cross Abstract: We introduce GraViti, a transformer-based graph-level variational autoencoder that maps entire graphs to compact latent vectors. This design produces
arXiv:2605.16714v1 Announce Type: new Abstract: Security knowledge graphs can provide computable external memory for security agents, but constructing them from long-form cyber threat intelligence (CT
arXiv:2605.17879v1 Announce Type: cross Abstract: Training frontier-scale foundation models involves coordinating tens of thousands of GPUs over multi-month runs, where even minor performance degradat
arXiv:2411.03936v2 Announce Type: replace Abstract: Generative modelling of multi-user datasets has become prominent in science and engineering. Generating a data point for a given user requires emplo
arXiv:2507.16481v3 Announce Type: replace Abstract: Jumping poses a significant challenge for quadruped robots, despite being crucial for many operational scenarios. While optimisation methods exist f
arXiv:2605.18567v1 Announce Type: new Abstract: Structural equation modeling is widely used in IS research. However, inconsistent construct definitions impede the cumulative development of knowledge.
arXiv:2508.08501v3 Announce Type: replace Abstract: We introduce GVGAI-LLM, a video game benchmark for evaluating the reasoning and problem-solving capabilities of large language models (LLMs). Built
arXiv:2605.16873v1 Announce Type: new Abstract: Diffusion priors have recently demonstrated strong capability in enhancing the quality of sparse-view 3D reconstruction by augmenting training views at
arXiv:2605.17007v1 Announce Type: new Abstract: Large language models (LLMs) have achieved remarkable progress in natural language generation, but remain susceptible to hallucination. In response to g
arXiv:2605.16389v1 Announce Type: cross Abstract: Haptic rendering of viscoelastic materials that exhibit creep and stress relaxation is crucial for many applications, such as medical training with re
arXiv:2605.16966v1 Announce Type: new Abstract: Solving inverse partial differential equation (PDE) problems is a fundamental topic in scientific research due to its broad significance across a wide r
arXiv:2605.17734v1 Announce Type: new Abstract: Equipping LLM agents with reusable skills derived from past experience has become a popular and successful approach for tackling complex and long-horizo
arXiv:2603.20421v2 Announce Type: replace-cross Abstract: We present Hawkeye, a system for analyzing and reproducing GPU-level arithmetic operations. Using our framework, anyone can re-execute on a CP
arXiv:2605.17300v1 Announce Type: new Abstract: We introduce HCLM, a hierarchical framework for general-purpose cooperative loco-manipulation with dual quadrupedal systems. Coordinating multi-robot co
arXiv:2506.23287v3 Announce Type: replace Abstract: In single-cell research, tracing and analyzing high-throughput single-cell differentiation trajectories is crucial for understanding biological proc
arXiv:2605.17093v1 Announce Type: cross Abstract: Distilling vision-language models into faster hybrid architectures, such as 3:1 Mamba-2/attention mixes, is now standard practice for making inference
arXiv:2602.16346v3 Announce Type: replace Abstract: LLM-based agents execute real-world workflows via tools and memory. These affordances enable ill-intended adversaries to also use these agents to ca
arXiv:2605.16268v1 Announce Type: cross Abstract: Banks receive millions of reports of fraud, scams, and disputed transactions every year, making it challenging to accurately direct customers to the a
arXiv:2603.20380v2 Announce Type: replace-cross Abstract: Industry practitioners and academic researchers regularly use multi-agent systems to accelerate their work, but the applications through which
arXiv:2605.17393v1 Announce Type: new Abstract: Coordination graphs are a central abstraction in cooperative multi-agent reinforcement learning (MARL), yet existing sparse-graph learners lack a theore
arXiv:2605.18437v1 Announce Type: new Abstract: Vehicular edge computing (VEC) enables latency-sensitive vehicular applications by offloading computation-intensive tasks to nearby edge servers. Howeve
arXiv:2605.17875v1 Announce Type: new Abstract: The accurate automated diagnosis of cardiac abnormalities from 12-lead electrocardiograms (ECGs) is critical for managing cardiovascular disease. Howeve
arXiv:2605.16442v1 Announce Type: cross Abstract: Long-horizon vessel trajectory forecasting under real ocean conditions is critical for collision avoidance, traffic management, and route planning. Ho
arXiv:2605.17294v1 Announce Type: new Abstract: High-resolution image editing is essential for professional and creative applications, yet existing multimodal diffusion-based editors remain computatio
arXiv:2605.17177v1 Announce Type: cross Abstract: Understanding the behavior of stochastic gradient methods is a central problem in modern machine learning. Recent work has highlighted diagonal linear
arXiv:2504.03035v2 Announce Type: replace-cross Abstract: Random feature ridge regression is often analyzed in the high-dimensional regime under the homogeneous sampling model x_i=Sigma^{1/2}x_i', whe
arXiv:2310.20389v2 Announce Type: replace-cross Abstract: Diffusion Tensor Cardiac Magnetic Resonance (DT-CMR) is the only in vivo method to non-invasively examine the microstructure of the human hear
arXiv:2605.16918v1 Announce Type: new Abstract: We present HighSync, an end-to-end diffusion-based framework for high-fidelity lip synchronization that generates photorealistic talking-face videos ali
arXiv:2605.16385v1 Announce Type: cross Abstract: Geometric problem solving, as a typical multimodal reasoning problem, has attracted much attention and made great progress recently, however most of w
arXiv:2605.17873v1 Announce Type: cross Abstract: Training long-horizon LLM agents with reinforcement learning is challenging because sparse outcome rewards reveal whether a task succeeds, but not whi
arXiv:2605.18408v1 Announce Type: new Abstract: Accurate vessel estimated-time-of-arrival forecasts are critical for port operations and decarbonization, yet global-scale travel-time prediction remain
arXiv:2605.17543v1 Announce Type: new Abstract: Video outpainting generates plausible visual content beyond the original spatial extent of a video, playing a key role in adapting videos to diverse dis
arXiv:2605.16286v1 Announce Type: cross Abstract: Different AI tools such as ChatGPT, Gemini, and Claude are becoming very popular. Although they are helpful for many day-to-day tasks, they can be use
arXiv:2603.25476v2 Announce Type: replace Abstract: Transfer learning is a crucial concept within deep learning that allows artificial neural networks to benefit from a large pre-training data basis w
arXiv:2605.17276v1 Announce Type: cross Abstract: While scaling laws have established a fundamental framework for foundation models in natural language processing, their applicability to electrocardio
arXiv:2605.16953v1 Announce Type: new Abstract: While AI-generated hallucinations pose considerable risks, the underlying cognitive mechanisms by which humans can successfully recognize or be misled b
arXiv:2605.17718v1 Announce Type: cross Abstract: Feature learning is widely regarded as the key mechanism distinguishing neural networks from fixed-kernel methods, yet its impact on the induced funct
arXiv:2605.16591v1 Announce Type: cross Abstract: In-context learning (ICL) excels at new tasks from minimal examples, yet we still lack a mechanistic explanation of how few-shot prompts shape a model
arXiv:2605.18111v1 Announce Type: new Abstract: Recent advancements in Large Language Models (LLMs) and Large Vision Language Models (LVLMs) have enabled general-purpose systems to demonstrate promisi
arXiv:2605.18105v1 Announce Type: new Abstract: Landslides often hit newsstands due to their destructive and potentially fatal effects. News are a valuable source of information for creating or enrich
arXiv:2605.16359v1 Announce Type: cross Abstract: Vision-language models improve perception by feeding increasingly long visual token sequences into language backbones, but the resulting inference cos
arXiv:2605.17570v1 Announce Type: cross Abstract: Group Relative Policy Optimization (GRPO) has been a key driver of recent progress in reinforcement learning with verifiable rewards (RLVR) for large
arXiv:2605.17077v1 Announce Type: cross Abstract: Scaling robot policy learning is bottlenecked by the cost of collecting demonstrations, while language annotations for existing demonstrations are com
arXiv:2603.07438v2 Announce Type: replace Abstract: Stress testing poses a causal question: how would portfolio credit losses change if the macroeconomy followed an adverse counterfactual path? Yet st
arXiv:2605.16347v1 Announce Type: new Abstract: Modern scientific research increasingly depends on High-Performance Computing (HPC) infrastructures, yet many researchers face significant operational b
arXiv:2506.03837v2 Announce Type: replace-cross Abstract: The discovery of high-temperature superconducting materials holds great significance for human industry and daily life. In recent years, resea