Knowledge catalogue
arXiv:2301.06217v1 Announce Type: cross Abstract: We provide a detailed exposition of the connections between Boltzmann machines commonly utilized in machine learning problems and the ideas already we
arXiv:2605.04541v1 Announce Type: new Abstract: Image-to-point-cloud registration (I2P) is a fundamental task in robotic applications such as manipulation,grasping, and localization. Existing deep lea
arXiv:2605.04225v1 Announce Type: cross Abstract: Coordinating multi-agent systems over spatially distributed areas requires solving a complex hierarchical problem: first distributing areas among agen
arXiv:2605.04408v1 Announce Type: new Abstract: Laparoscope-holding robots can provide surgeons with a stable laparoscopic field of view (FOV) and reduce the burden on human assistants. To maintain an
ComfyUI announced the availability of a feature or service that can be accessed locally immediately and on cloud infrastructure with a 1-2 hour latency or deployment time. This post likely refers to a
B9050 is a release build of llama.cpp, an open-source C/C++ project that enables LLM inference with minimal setup and high performance on diverse hardware platforms. The project provides LLM inference
I was unable to find specific details about the b9058 release. Based on the context, b9058 is a build version from the llama.cpp project, which is an open source software library that performs inferen
arXiv:2605.04077v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) has become a central paradigm for improving reasoning and code generation in large language mode
arXiv:2605.04406v1 Announce Type: new Abstract: The integration of Symmetric Positive Definite (SPD) matrices into deep learning has historically relied on fixed algebraic Riemannian metrics. Analogou
arXiv:2601.11689v2 Announce Type: replace-cross Abstract: Multimodal image registration between diffusion MRI (dMRI) and T1-weighted (T1w) MRI images is a critical step for aligning diffusion-weighted
arXiv:2605.05104v1 Announce Type: cross Abstract: Materials science data collection can be expensive, making the reuse and long-term utility of datasets critical important for future discovery campaig
arXiv:2602.06810v2 Announce Type: replace Abstract: Tabular anomaly detection (TAD) remains challenging due to the heterogeneity of tabular data: features lack natural relationships, vary widely in di
arXiv:2511.20284v2 Announce Type: replace-cross Abstract: Precise access control decisions are crucial for the security of both traditional applications and emerging agent-based systems. Typically, th
arXiv:2605.04381v1 Announce Type: cross Abstract: Causal discovery methods such as LiNGAM identify causal structure from observational data by assuming mutually independent disturbances. This assumpti
arXiv:2605.04206v1 Announce Type: new Abstract: Large-scale restoration in drylands is widely promoted to address land degradation and biodiversity loss, yet many efforts rely on long-term irrigation,
arXiv:2502.13498v2 Announce Type: replace-cross Abstract: Object-goal visual navigation aims to reach a specific target object using egocentric visual observations. Recent deep reinforcement learning
arXiv:2605.03900v1 Announce Type: new Abstract: Frontier AI systems perform best in settings with clear, stable, and verifiable objectives, such as code generation, mathematical reasoning, games, and
arXiv:2605.05097v1 Announce Type: cross Abstract: LLMs are trained once, then deployed into a world that never stops changing. External memory compensates for this, but most systems manage it explicit
arXiv:2605.03309v1 Announce Type: cross Abstract: Dependency confusion attacks exploit a structural gap in software distribution: once a package is installed, there is no cryptographic proof of which
arXiv:2605.05023v1 Announce Type: new Abstract: Efficient CUDA implementations of attention mechanisms are critical to modern deep learning systems, yet supporting diverse and evolving attention varia
arXiv:2605.03882v1 Announce Type: cross Abstract: Individuals frequently form deep attachments to physical objects (e.g., plush toys) that usually cannot sense or respond to their emotions. While AI c
arXiv:2605.02970v1 Announce Type: cross Abstract: Network traffic anomaly detection represents a critical cybersecurity task, yet widespread encryption makes this task increasingly challenging. In res
arXiv:2605.04234v1 Announce Type: new Abstract: Implicit neural representations (INRs) have emerged as a powerful paradigm for medical imaging via physics-informed unsupervised learning. Classical INR
arXiv:2404.13649v2 Announce Type: replace-cross Abstract: Dimension reduction techniques usually lose information in the sense that reconstructed data are not identical to the original data. However,
Don’t let the exponential gains in ability fool you: there are fewer real grand plans in AI (or frankly any field of human endeavor) than you think. Companies are pivoting as the market changes, somet
arXiv:2605.04079v1 Announce Type: new Abstract: Early and reliable detection of Alzheimer's disease (AD) is crucial for timely clinical intervention and improved patient management. It also supports t
arXiv:2603.16368v2 Announce Type: replace-cross Abstract: Striking a balance between efficiency and transparent motion is a core challenge in human-robot collaboration, as highly expressive movements
arXiv:2605.04054v1 Announce Type: new Abstract: Achieving endogenous regime switching is crucial for the emergence of autonomous intelligence, yet remains a central challenge for existing machine lear
arXiv:2605.04410v1 Announce Type: new Abstract: The evaluation of explainable AI (XAI) methods is affected by a lack of standardization. Metrics are inconsistently defined, incompletely reported, and
This post from Thariq discusses efforts to acquire additional computational resources to improve service delivery, acknowledging that the process may take time. The message suggests commitment to scal
arXiv:2605.04664v1 Announce Type: new Abstract: Anomaly detection methods can be very useful in identifying interesting or concerning events. In this work, we develop and examine new probabilistic ano
arXiv:2506.20911v2 Announce Type: replace Abstract: We develop a cost-efficient neurosymbolic agent to address challenging multi-turn image editing tasks such as ``Detect the bench in the image while
arXiv:2605.05077v1 Announce Type: new Abstract: Accurate image segmentation is essential for modern computer vision applications such as image editing, autonomous driving, and medical image analysis.
arXiv:2605.04157v1 Announce Type: new Abstract: SemEval-2026 Task 13 investigates machine-generated code detection across multiple programming languages and application scenarios, asking participating
arXiv:2605.03383v1 Announce Type: new Abstract: Lithology classification aims to infer subsurface rock types from well-logging signals, supporting downstream applications like reservoir characterizati
arXiv:2605.04279v1 Announce Type: new Abstract: Transformer self-attention can be interpreted as a gradient flow on the unit sphere, in which tokens evolve under softmax interaction potentials and ten
arXiv:2605.04376v1 Announce Type: new Abstract: The integration of deep learning approaches in biomedical research has been transformative, enabling breakthroughs in various applications. Despite thes
arXiv:2605.05072v1 Announce Type: new Abstract: 3D occupancy prediction aims to infer dense, voxel-wise scene semantics from sensor observations, where the 2D-to-3D view transformation serves as a cru
Nous Research announced improvements or updates to their Hermes Agent system, highlighting enhanced capabilities or performance. The post was shared on X (formerly Twitter), suggesting it covers recen
arXiv:2605.04254v1 Announce Type: new Abstract: We introduce State Vector Space Partitioning (SVSP), a novel method to mimic a black box reinforcement learning policy using a set of human-interpretabl
.@huggingface's agentic robotics app store for Reachy Mini is a big step toward more accessible physical AI. 🙌 Excited to see NVIDIA Isaac GR00T N integrated with Hugging Face LeRobot, helping develop
arXiv:2605.05144v1 Announce Type: new Abstract: This paper reflects on a AI research project carried out by a team of high-school and early-undergraduate students under the mentorship of graduate rese
arXiv:2407.14861v3 Announce Type: replace-cross Abstract: With the growing access to administrative health databases, retrospective studies have become crucial evidence for medical treatments. Yet, no
arXiv:2605.04064v1 Announce Type: cross Abstract: Reasoning capabilities are crucial for reliable medical visual question answering (VQA); however, existing datasets rarely include reasoning explanati
arXiv:2605.04355v1 Announce Type: new Abstract: Autonomous driving systems rely heavily on robust sensor fusion to perceive complex envi- ronments. Traditional setups using RGB cameras and LiDAR often
arXiv:2605.04554v1 Announce Type: new Abstract: Humans constantly interact with their surroundings. Existing end-to-end multi-person human mesh recovery methods, typically based on the DETR framework,
arXiv:2605.04671v1 Announce Type: new Abstract: Gradient boosting remains a strong and widely used method for tabular data learning, but its performance often degrades when training labels are noisy.
arXiv:2605.05050v1 Announce Type: cross Abstract: Gap-closing rate and visual looming swap discriminative dominance depending on deceleration intensity - a finding that reconciles a long-standing conf
arXiv:2605.04230v1 Announce Type: new Abstract: Geometry-aware optimizers such as Newton and natural gradient can improve conditioning in deep learning, but scalable variants such as K-FAC, Shampoo, a
arXiv:2605.04445v1 Announce Type: new Abstract: The rapid advancement of generative technologies has made synthetic images nearly indistinguishable from real ones, thereby creating an urgent need for
arXiv:2605.04569v1 Announce Type: new Abstract: Video editing has evolved toward In-Context Learning (ICL) paradigms, yet the resulting quadratic attention costs create a critical computational bottle
arXiv:2510.09881v3 Announce Type: replace Abstract: Recent advances in novel-view synthesis can create the photo-realistic visualization of real-world environments from conventional camera captures. H
arXiv:2312.06423v3 Announce Type: replace-cross Abstract: Machine learning (ML) has gained significant adoption in Android malware detection to address the escalating threats posed by the rapid prolif
arXiv:2604.01342v2 Announce Type: replace Abstract: Multivariate Hawkes processes are a widely used class of self-exciting point processes, but maximum likelihood estimation naively scales as O(N^2) i
arXiv:2605.04278v1 Announce Type: new Abstract: Materials science workflows rely on structured and unstructured data from the vast body of available scientific literature. However, most of the experim
arXiv:2605.03216v1 Announce Type: cross Abstract: Strategy-proofness is a fundamental desideratum in mechanism design, ensuring truthful reporting and robust participation. Stability is another centra
arXiv:2605.04731v1 Announce Type: new Abstract: Building height (BH) and building footprint (BF) jointly describe the vertical and horizontal extent of the built environment and are required inputs fo
Mozilla ran an agentic harness powered by Claude Mythos Preview across Firefox's source code, identifying 271 security bugs fixed in Firefox 150 . The breakthrough was achieved through improvements in
arXiv:2602.01486v2 Announce Type: replace Abstract: Recent years have seen a surge in data-driven surrogates for dynamical systems that can be orders of magnitude faster than numerical solvers. Howeve
In the high-stakes world of digital infrastructure, speed isn't just a metric — it’s currency. At Google Cloud Next ‘26 we announced the Bigtable in-memory tier, a breakthrough for our fully managed c