Knowledge catalogue
it’s kind of awesome that continual learning has now come to the agent & harness level. i remember when online learning was the big craze in traditional ml a couple of years ago, that transitioned int
arXiv:2605.14998v1 Announce Type: new Abstract: From subcellular structures to entire organisms, many natural systems generate complex organisation through self-organisation: local interactions that c
arXiv:2512.02920v3 Announce Type: replace-cross Abstract: We consider analyzing traffic accident patterns using both road network data and satellite images aligned to road graph nodes. Previous work f
arXiv:2605.14494v1 Announce Type: new Abstract: Two-Stage Robust Optimization (2RO) with discrete uncertainty is challenging, often rendering exact solutions prohibitive. Scenario reduction alleviates
arXiv:2605.14346v1 Announce Type: new Abstract: Single-frame Infrared Small Target Detection (ISTD) aims to localize weak targets under heavy background clutter, yet dense pixel-wise annotations are e
arXiv:2605.14454v1 Announce Type: cross Abstract: As AI agents move from chat interfaces to systems that read private data, call tools, and execute multi-step workflows, guardrails become a last line
arXiv:2605.14548v1 Announce Type: new Abstract: Gait recognition, as a promising biometric technology, identifies individuals through their unique walking patterns and offers distinctive advantages in
arXiv:2605.14407v1 Announce Type: new Abstract: The dominant discourse on AI limitations frames the boundary of AI capability as a divide between digital tasks (where AI excels) and physical tasks (wh
arXiv:2605.14980v1 Announce Type: cross Abstract: Analyzing microscopy images to extract biological object properties (e.g., their morphological organization, temporal dynamics, and population density
arXiv:2509.14159v3 Announce Type: replace Abstract: As robots become more integrated in society, their ability to coordinate with other robots and humans on multi-modal tasks (those with multiple vali
arXiv:2605.14660v1 Announce Type: new Abstract: Post-Traumatic Stress Disorder (PTSD) is fundamentally a neuroplastic problem traumatic contact events encode over-reactive neural pathways through Hebb
arXiv:2605.14781v1 Announce Type: new Abstract: Monocular 3D object detection remains challenging because metric size and depth are underdetermined by single-view evidence, particularly under occlusio
arXiv:2605.14199v1 Announce Type: new Abstract: Motion planning for autonomous vehicles requires generating collision-free and dynamically feasible trajectories in complex environments under real-time
arXiv:2512.16768v3 Announce Type: replace-cross Abstract: Flow matching (FM) constructs continuous-time ODE samplers by prescribing probability paths between a base distribution and a target distribut
arXiv:2510.13583v4 Announce Type: replace-cross Abstract: Causal discovery from i.i.d. observational data is known to be generally ill-posed. We demonstrate that if we have access to the distribution
arXiv:2507.21023v2 Announce Type: replace Abstract: Recent publications have suggested using the Shapley value for anomaly localization for sensor data systems. Using a reasonable mathematical anomaly
arXiv:2605.14277v1 Announce Type: new Abstract: Parallelization has played an instrumental role in the field of artificial intelligence (AI), drastically reducing the time taken to train and evaluate
arXiv:2605.14098v1 Announce Type: cross Abstract: Chain-of-thought (CoT) reasoning with self-consistency improves performance by aggregating multiple sampled reasoning paths. In this setting, correctn
arXiv:2605.14269v1 Announce Type: cross Abstract: Generating realistic human motion is a central yet unsolved challenge in video generation. While reinforcement learning (RL)-based post-training has d
PipelineIQ is a Databricks solution that leverages data analytics and AI to provide predictive sales intelligence, enabling sales teams to forecast pipeline outcomes and identify actionable opportunit
arXiv:2605.14125v1 Announce Type: new Abstract: How do artificial neural networks bind concepts to form complex semantic structures? Here, we propose a simple neural code, whereby the existence and th
arXiv:2605.14297v1 Announce Type: cross Abstract: We study reinforcement learning in hybrid discrete-continuous action spaces, such as settings where the discrete component selects a regime (or index)
arXiv:2605.15164v1 Announce Type: cross Abstract: This position paper argues that behavioural assurance, even when carefully designed, is being asked to carry safety claims it cannot verify. AI govern
arXiv:2605.14294v1 Announce Type: new Abstract: Formal verification of transformers has become increasingly important due to their widespread deployment in safety-critical applications. Compared to cl
arXiv:2605.14991v1 Announce Type: cross Abstract: Ovarian cancer is the most lethal gynecologic malignancy: around 60% of patients are diagnosed at an advanced stage, with an associated 5-year surviva
arXiv:2605.14758v1 Announce Type: new Abstract: History-dependent policies induced by recurrent neural networks (RNNs) rely on latent hidden state dynamics, making verification in partially observable
arXiv:2605.14561v1 Announce Type: new Abstract: Prompt engineering is crucial for effective interaction with generative artificial intelligence systems, yet existing optimisation methods often operate
arXiv:2605.14113v1 Announce Type: cross Abstract: While interpretable prototype networks offer compelling case-based reasoning for clinical diagnostics, their raw continuous outputs lack the semantic
arXiv:2605.14502v1 Announce Type: cross Abstract: Power electronics systems are increasingly exposed to cyber threats due to their integration with digital controllers and communication networks. Howe
arXiv:2605.14686v1 Announce Type: new Abstract: Tabular data sharing under privacy constraints is increasingly important for research and collaboration. Synthetic data generators (SDGs) are a promisin
arXiv:2605.14913v1 Announce Type: new Abstract: Linear attention has emerged as a promising direction for scaling Vision Transformers beyond the quadratic cost of dense self-attention. A prevalent str
arXiv:2605.14174v1 Announce Type: new Abstract: Safe navigation for mobile robots demands policies that remain reliable under the high-consequence perception uncertainty of cluttered environments. Yet
arXiv:2605.14399v1 Announce Type: new Abstract: Many multimodal learning tasks require supervision that remains consistent across edits, viewpoints, and scene-level interventions. However, such superv
arXiv:2605.15155v1 Announce Type: cross Abstract: Reinforcement learning (RL) has emerged as a central paradigm for post-training LLM agents, yet its trajectory-level reward signal provides only coars
arXiv:2605.14318v1 Announce Type: new Abstract: Predictive maintenance in complex systems is often complicated by the heterogeneity and redundancy of monitored variables,which can obscure fault-releva
arXiv:2510.18766v2 Announce Type: replace Abstract: A future lunar habitat, as part of the Artemis program, will require a significant amount of logistics infrastructure. Cargo that is transported to
arXiv:2605.13861v1 Announce Type: cross Abstract: The propagation structure of fake news has been shown to be an important cue for detecting it; yet, existing propagation-based fake news detection met
arXiv:2605.14685v1 Announce Type: cross Abstract: In physical systems, whenever a continuous symmetry is spontaneously broken, the system possesses excitations called Goldstone modes, which allow cohe
arXiv:2605.14808v1 Announce Type: new Abstract: Visual anomaly detection (AD) for industrial inspection is a highly relevant task in modern production environments. The problem becomes particularly ch
arXiv:2605.14889v1 Announce Type: cross Abstract: Online surgical phase recognition (SPR) underpins context-aware operating-room systems and requires committing to a prediction at every frame from pas
arXiv:2605.14396v1 Announce Type: new Abstract: Autonomous vehicles depend on online HD map construction to perceive lane boundaries, dividers, and pedestrian crossings -- safety-critical road element
arXiv:2601.21656v3 Announce Type: replace Abstract: Clustering tabular data is a fundamental yet challenging problem due to heterogeneous feature types, diverse data-generating mechanisms, and the abs
arXiv:2605.14866v1 Announce Type: cross Abstract: As modern microservice systems grow increasingly complex due to dynamic interactions and evolving runtime environments, they experience failures with
arXiv:2506.08809v5 Announce Type: replace Abstract: High-resolution sinogram completion is critical for computed tomography reconstruction, as missing projections can introduce severe artifacts. While
arXiv:2605.14315v1 Announce Type: new Abstract: Recent feed-forward 3D reconstruction methods, such as visual geometry transformers, have substantially advanced the traditional per-scene optimization
arXiv:2605.15186v1 Announce Type: cross Abstract: High-quality 3D scene reconstruction has recently advanced toward generalizable feed-forward architectures, enabling the generation of complex environ
arXiv:2605.14972v1 Announce Type: cross Abstract: A fundamental limitation of Text-to-Code is that no guarantee can be obtained about the correctness of the generated code. Therefore, to ensure its co
Wow! What a week! Lots of new things to learn - new ideas to form The complete Agent Development Life Cycle 🎯 ❤️ SF but can’t wait to get home and back to building! Thanks for the warm welcome and fun
arXiv:2605.14166v1 Announce Type: new Abstract: Face image super-resolution aims to recover high-resolution facial images from severely degraded inputs. Under extreme upscaling factors, fine facial de
arXiv:2605.12689v1 Announce Type: new Abstract: In this paper, we present a novel hybrid approach that combines Reinforcement Learning (RL) with Dynamic Window Approach (DWA) for adaptive 3D local nav
Matt Levine / Bloomberg: A look at GameStop's takeover bid for eBay, a bizarre job application by GameStop CEO Ryan Cohen, who does not have the money to buy eBay, to become eBay's CEO — Also Adani Gr
arXiv:2605.13110v1 Announce Type: cross Abstract: We present a fully automated multi-agent framework for corporate due diligence and market analysis in venture capital. The system runs on an event-dri
arXiv:2605.12706v1 Announce Type: new Abstract: RSNet is an open-source R package that provides a resampling-based framework for robust and interpretable network inference, designed to address the lim
arXiv:2605.12697v1 Announce Type: cross Abstract: Length-dependent logit rescaling is widely used to stabilize long-context self-attention, but existing analyses and methods suggest conflicting invers
arXiv:2605.12569v1 Announce Type: cross Abstract: Global navigation satellite system (GNSS) interference poses a serious threat to reliable positioning, especially in indoor and multipath-rich environ
arXiv:2501.10598v3 Announce Type: replace Abstract: We study the problem of learning optimal policies in finite-horizon Markov Decision Processes (MDPs) using low-rank reinforcement learning (RL) meth
arXiv:2605.12937v1 Announce Type: cross Abstract: Anti-facial recognition (AFR) image filters alter images in ways that are subtle to people but blinding to computer vision. Yet, despite widespread in
The search did not return specific information about the b9140 release. Based on the context, b9140 is a specific build number from the llama.cpp project releases. llama.cpp is an LLM inference implem
The search results show releases near b9143 (specifically b9134 was the most recent) but do not contain specific details about b9143 itself. Based on the available information: llama.cpp is a C/C++ im
The search results show recent llama.cpp releases but don't contain specific details about the b9145 build. Based on the pattern of changes in recent releases, b9145 likely includes updates to SYCL/Le