Knowledge catalogue
Artificial intelligence development firm Anaconda Inc. is enhancing its enterprise AI platform with tools to coordinate groups of AI agents, test their security and move applications into production.
arXiv:2610.04927v1 Announce Type: cross Abstract: Agentic machine learning engineering (MLE) is an emerging AI4SE application for complex ML tasks and a step toward recursive self-improvement of AI sy
arXiv:2610.04405v1 Announce Type: new Abstract: Despite the growing popularity of physics-informed neural networks (PINNs), their applicability in the long-time integration of partial differential equ
arXiv:2610.06244v1 Announce Type: new Abstract: Planar graphs are central to applications across science and engineering, yet existing generators provide limited support for goal-directed generation u
arXiv:2510.06842v2 Announce Type: replace Abstract: Action Quality Assessment (AQA) quantifies human actions in videos, supporting applications in sports scoring, rehabilitation, and skill evaluation.
arXiv:2610.06636v1 Announce Type: new Abstract: Many machine learning applications involve sensitive data and therefore require training under differential privacy (DP). However, DP training often deg
arXiv:2408.16803v2 Announce Type: replace Abstract: Transformers have gained widespread acclaim for their versatility in handling diverse data structures, yet their application to log data remains und
arXiv:2604.26654v1 Announce Type: cross Abstract: This paper presents an application of the biologically realistic JASTAP neural network model to classification tasks. The JASTAP neural network model
arXiv:2503.17589v3 Announce Type: replace Abstract: Kinematic motion planners are among the most widely used control approaches in robotic applications. By modeling the robot as a first-order system,
arXiv:2406.07579v2 Announce Type: replace-cross Abstract: 2D irregular packing is a classic combinatorial optimization problem with various applications, such as material utilization and texture atlas
arXiv:2610.05861v1 Announce Type: new Abstract: Graphical User Interface (GUI) agents have emerged as a promising paradigm for automating complex digital workflows across diverse applications. However
arXiv:2610.05250v1 Announce Type: new Abstract: Kolmogorov--Arnold Networks (KANs) have attracted increasing attention in recent years, with applications across a wide range of AI tasks. In this paper
arXiv:2502.07397v3 Announce Type: replace-cross Abstract: Linear bandits have long been a central topic in online learning, with applications ranging from recommendation systems to adaptive clinical t
arXiv:2411.12426v3 Announce Type: replace Abstract: Real-world applications of stereo matching, such as autonomous driving, place stringent demands on both safety and accuracy. However, learning-based
arXiv:2610.04551v1 Announce Type: new Abstract: Multiple LiDAR-inertial odometry methods have been widely applied in robotic applications owing to their enhanced accuracy and reliability. However, ado
arXiv:2610.05122v1 Announce Type: new Abstract: In recent years, Unmanned Aerial Vehicles (UAVs) or drones have been increasingly adopted in urban environments for applications such as parcel delivery
arXiv:2610.06404v1 Announce Type: new Abstract: We consider the stability of multi-step reasoning processes, which have extensive applications in language models, including chain-of-thought and algori
arXiv:2208.08697v2 Announce Type: replace-cross Abstract: The security of deep learning (DL) systems is an extremely important field of study as they are being deployed in several applications due to
arXiv:2610.04457v1 Announce Type: new Abstract: Vision Transformers (ViTs) achieve strong performance on image recognition and mobile vision applications, but their high-dimensional linear projections
arXiv:2610.06229v1 Announce Type: new Abstract: Spherical data arise in many scientific applications. Often spherical transformers disregard the geometry of the underlying spherical domain, causing di
arXiv:2610.06315v1 Announce Type: new Abstract: Electroencephalography (EEG) based brain-computer interfaces enable direct brain-to-device communication for applications such as rehabilitation and com
arXiv:2507.09200v2 Announce Type: replace Abstract: The rapid proliferation of video in applications such as autonomous driving, surveillance, and sports analytics necessitates robust methods for dyna
arXiv:2407.18137v2 Announce Type: replace Abstract: Small object detection and tracking in videos remain critical yet underexplored challenges in computer vision, particularly for applications such as
arXiv:2610.02869v1 Announce Type: cross Abstract: Autonomous penetration testing agents conduct multi-step attacks by continuously adapting their plans and actions to target responses. As a common def
arXiv:2610.02770v1 Announce Type: new Abstract: Document databases such as MongoDB are core infrastructure for modern applications, and natural-language interfaces to them---text-to-MQL---would let no
arXiv:2603.14275v3 Announce Type: replace-cross Abstract: Existing accent normalization methods do not typically offer control over accent strength, yet many applications-such as language learning and
arXiv:2610.03617v1 Announce Type: new Abstract: Image-text alignment is a core problem in computer vision with applications in caption evaluation, hallucination detection, data curation, and the bench
arXiv:2610.02868v1 Announce Type: cross Abstract: Learning robust survival models under distribution shift is an important but challenging problem in many applications. In heterogeneous populations, a
arXiv:2609.35149v2 Announce Type: replace Abstract: Deploying, migrating, or scaling an agent can change its model, harness, infrastructure, application, and intended users. We formulate agent calibra
arXiv:2610.02260v1 Announce Type: new Abstract: Flow matching models excel at generative modeling, and many downstream applications require their samples to satisfy prescribed constraints, such as obs
arXiv:2506.05937v3 Announce Type: replace-cross Abstract: Reliability of deep learning models is critical for deployment in high-stakes applications, where out-of-distribution or adversarial inputs ma
arXiv:2610.03147v1 Announce Type: cross Abstract: Streaming sensor applications routinely suffer from delayed or missing observations caused by faults, communication losses, or environmental interfere
arXiv:2610.02946v1 Announce Type: new Abstract: Video Object Segmentation (VOS) in complex and long videos is increasingly important for real-world applications, where target objects often appear only
Auto-generated synthesis of 10865 entries about arxiv-cs-cl
arXiv:2610.01944v1 Announce Type: new Abstract: Few-shot personalization enables large vision--language models (LVLMs) to learn user-specific visual concepts for applications such as personalized retr
arXiv:2610.01749v1 Announce Type: cross Abstract: Topological Data Analysis (TDA) offers novel methods for understanding temporal dynamics in complex systems, yet its application in information system
arXiv:2610.00791v1 Announce Type: new Abstract: Enterprise information is represented through artifacts shaped by applications, projects, technologies, organizational boundaries, and local requirement
arXiv:2610.00922v1 Announce Type: new Abstract: Gaze estimation under natural head-eye motion underpins applications from driver monitoring to human-computer interaction. Single-frame methods predict
arXiv:2610.01937v1 Announce Type: new Abstract: Topology is, by its nature and design, suited to structure that is nonlinear, multiscale, and nonstationary - however, within machine learning, its use
arXiv:2610.01502v1 Announce Type: new Abstract: Diffusion models are a powerful generative paradigm used across multimedia and scientific applications. Guided diffusion methods impose requirements on
arXiv:2610.00872v1 Announce Type: new Abstract: Long-term memory systems for large language models (LLMs) have gained popularity for extending reasoning capabilities across applications. Current memor
arXiv:2610.01048v1 Announce Type: new Abstract: World models, which simulate an environment and predict how it changes under actions, are increasingly used in real-world applications such as robotics.
arXiv:2610.00682v1 Announce Type: new Abstract: Large language models (LLMs) increasingly underpin scientific AI applications that reason over structured knowledge, from biomedical question answering
arXiv:2610.00873v1 Announce Type: cross Abstract: In many industrial applications, 1) tabular data is scarce and imbalanced and thus requires synthetic expansion; 2) input distributions drift between
arXiv:2610.02128v1 Announce Type: cross Abstract: Many applications in statistics, economics, and physics require sampling from high-dimensional categorical distributions with local dependence structu
arXiv:2610.00421v1 Announce Type: cross Abstract: Automated classification of brain tumors from MRI is a heavily published application of deep learning in medical imaging, with reported accuracies on
arXiv:2610.00102v1 Announce Type: new Abstract: Many machine learning (ML) applications rely on expert labels, and qualified experts may provide different but plausible interpretations of the same obs
arXiv:2510.23576v2 Announce Type: replace-cross Abstract: Urban micromobility applications, such as delivery robots, demand reliable navigation across large-scale urban environments while following lo
arXiv:2512.12870v2 Announce Type: replace-cross Abstract: Active Learning (AL) is commonly used in applications where labeling data is expensive or time-consuming. In practice, however, labels are oft
arXiv:2607.11555v2 Announce Type: replace Abstract: Learning neural set functions is pivotal to a wide range of important applications, including compound selection in AI-driven drug discovery and pro
arXiv:2609.39467v1 Announce Type: new Abstract: Pedestrian detection plays a crucial role in computer vision with applications in autonomous driving, surveillance, and public safety. However, real-wor
An AI agent uses compute differently than a traditional application. Over a single session, it writes and runs code, calls a model, and waits on a tool or a person before picking the work back up. As
arXiv:2511.06947v2 Announce Type: replace-cross Abstract: The well-aligned attribute of CLIP-based models enables its effective application like CLIPscore as a widely adopted image quality assessment
arXiv:2609.38519v1 Announce Type: new Abstract: Egocentric gaze prediction enables many downstream applications but remains challenging, as human gaze is inherently stochastic. This stochasticity is c
arXiv:2609.39301v1 Announce Type: cross Abstract: This paper considers a class of multiblock nonconvex and nonsmooth optimization problems arising in many applications. Existing methods construct prox
arXiv:2609.38748v1 Announce Type: new Abstract: Recent joint video-audio generation models have achieved strong semantic correspondence and temporal synchronization. However, applications such as AR/V
arXiv:2507.12133v2 Announce Type: replace Abstract: Device recognition is vital for security in wireless communication systems, particularly for applications like access control. Radio Frequency Finge
IBM Corp. today announced a self-hosted deployment option for IBM Bob, its agentic software development platform, allowing enterprises to use artificial intelligence to build and modernize application
arXiv:2609.39547v1 Announce Type: new Abstract: GUI agents built on large language and vision-language models still struggle on unseen applications and complex multi-step tasks, as completing real GUI
arXiv:2609.39527v1 Announce Type: new Abstract: The presence of lens flares in images can significantly reduce the quality of downstream application results for tasks such as 3D scene reconstruction.