Knowledge catalogue
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: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:2605.16953v1 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:2605.17077v1 Announce Type: cross Abstract: Scaling robot policy learning is bottlenecked by the cost of collecting demonstrations, while language annotations for existing demonstrations are com
Unity AI Gateway Guardrails is a Databricks feature designed to protect AI workloads by implementing safety measures and policy controls within the Unity Catalog framework. The tool enables organizati
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:2605.17481v1 Announce Type: new Abstract: Nowadays, people in Bangladesh frequently rely on the internet and social media for daily news instead of traditional newspapers. However, the spread of
This post describes a visualization tool that provides real-time insight into GPT-2's internal processing by displaying concept activations as a 3D graph, with each token generation showing which neur
Sam Altman posted a humorous tweet on X suggesting that if the tweet received 1 like, a person named Tibo would reset Codex rate limits, likely referencing internal OpenAI API management or a playful
arXiv:2505.06852v2 Announce Type: replace Abstract: Random forest regression is a powerful non-parametric method that adapts to local data characteristics through data-driven partitioning, making it e
arXiv:2601.06633v2 Announce Type: replace-cross Abstract: Open-ended tasks, such as coding problems that are common in computer science education, provide detailed insights into student knowledge. How
arXiv:2605.17730v1 Announce Type: cross Abstract: Mainstream methods for multivariate time-series forecasting largely follow the Direct-Mapping paradigm. They learn a unified mapping from history to t
arXiv:2605.16743v1 Announce Type: new Abstract: Cross-embodiment learning from human demonstrations is hindered by the visual gap between human and robot embodiments. While self-supervised learning (S
LangSmith Engine is a tool within the LangChain ecosystem that provides visibility and debugging capabilities for AI applications built with LangChain. This technical deep-dive likely covers how the e
arXiv:2601.20888v3 Announce Type: replace-cross Abstract: We study sampling from posterior distributions in Bayesian linear inverse problems where A, the parameters to observables operator, is computa
arXiv:2605.16357v1 Announce Type: cross Abstract: WiFi fingerprint-based indoor localization has been widely studied, but most existing approaches focus on absolute positioning and rely on dense coord
arXiv:2605.17362v1 Announce Type: new Abstract: Matrix reordering in large sparse solvers seeks a permutation that minimizes factorization fill-in to reduce memory and computation. Because the minimum
arXiv:2605.18701v1 Announce Type: new Abstract: Blood-based biomarkers underpin clinical diagnosis and management, yet their interpretation relies largely on fixed population reference intervals that
arXiv:2605.16834v1 Announce Type: cross Abstract: Multimodal pre-training demonstrates strong generalization performance, but this paradigm is often impractical in domains where paired data are scarce
arXiv:2605.17980v1 Announce Type: new Abstract: Diffusion-based methods demonstrate significant potential for remote sensing image super-resolution at large scaling factors, particularly in reference-
arXiv:2605.16755v1 Announce Type: cross Abstract: Learning permutations is fundamental to sorting, ranking, and matching, but existing differentiable methods based on entropy-regularized Sinkhorn prod
arXiv:2605.12012v2 Announce Type: replace Abstract: Public-sector legal departments in the Netherlands face acute staff shortages, increased case volumes, and increased pressure to meet regulatory com
arXiv:2605.18641v1 Announce Type: new Abstract: Latent visual reasoning involves visual evidence more directly in multimodal reasoning by inserting continuous latent tokens before textual generation.
arXiv:2605.12987v2 Announce Type: replace Abstract: BACKGROUND: Coding Motivational Interviewing (MI) sessions is essential for understanding client behaviors and predicting outcomes, but it requires
arXiv:2603.16947v2 Announce Type: replace-cross Abstract: Although vision-language navigation (VLN) has progressed rapidly, zero-shot VLN in continuous environments (VLN-CE) remains highly challenging
arXiv:2605.17287v1 Announce Type: new Abstract: Driver gaze estimation serves as a fundamental metric for evaluating driver attentiveness in modern monitoring systems. Beyond being vulnerable to sudde
arXiv:2510.25799v2 Announce Type: replace Abstract: Human experts often struggle to select the best option from a large set of items with multiple competing objectives, a process bottlenecked by the d
Chrome DevTools will add support for validating llms.txt files, enabling developers to check the validity and correctness of their llms.txt configurations directly within the browser's developer tools
arXiv:2605.18015v1 Announce Type: new Abstract: Production log analytics in self-hosted, resource-constrained environments requires natural-language access to massive log streams without the cost of r
arXiv:2605.17303v1 Announce Type: new Abstract: Recovering a dynamic 3D scene from a long monocular video is crucial for dense geometry, camera motion, and temporal correspondence to remain consistent
arXiv:2605.18329v1 Announce Type: new Abstract: Ensemble disagreement is widely used as a proxy for epistemic uncertainty in medical image segmentation. In practice, many studies form ensembles via K-
LTX 2.3's image-to-video (i2v) feature exhibits gradual video saturation and brightness degradation over extended generation sequences, though users have developed Python code aimed at recovering thes
arXiv:2605.18572v1 Announce Type: new Abstract: Persuasive dialogue generation plays a vital role in decision-making, negotiation, counseling, and behavior change, yet it remains a challenging problem
arXiv:2605.17120v1 Announce Type: new Abstract: arly identification of motor impairment in infancy relies on expert visual assessment of spontaneous movement, motivating the development of automated,
arXiv:2605.17431v1 Announce Type: cross Abstract: We propose MATE, a simple yet effective memory architecture for solving Contextual Markov Decision Processes (CMDPs), a family of MDPs parameterized b
arXiv:2605.17091v1 Announce Type: new Abstract: Scientific forecasting typically relies on direct state prediction, an approach that grows brittle under data scarcity, extended horizons, non-stationar
arXiv:2605.16468v1 Announce Type: cross Abstract: A central goal in understanding human vision is to uncover the visual features that drive neuronal activity. A growing body of work has used artificia
arXiv:2605.18652v1 Announce Type: new Abstract: Recent GUI agents have made substantial progress in visual grounding and action prediction, yet they remain brittle in long-horizon tasks that require m
arXiv:2506.15588v2 Announce Type: replace Abstract: Differential privacy (DP) protects sensitive data during neural network training, but standard methods like DP-Adam suffer from high memory overhead
arXiv:2605.17539v1 Announce Type: new Abstract: Combinatorial optimization (CO) underlies decision-making from logistics to chip design, where infeasible solutions are operationally unusable and small
arXiv:2605.17444v1 Announce Type: cross Abstract: Modern software ecosystems face a rapidly growing number of disclosed vulnerabilities, increasing the need for automated repair techniques that can op
arXiv:2603.08290v2 Announce Type: replace-cross Abstract: We study the implicit bias of Sharpness-Aware Minimization (SAM) when training L-layer linear diagonal networks on linearly separable binary c
arXiv:2605.16262v1 Announce Type: new Abstract: Variational inequalities play a key role in machine learning research, such as generative adversarial networks, reinforcement learning, adversarial trai
arXiv:2505.02621v2 Announce Type: replace Abstract: The mean-field Langevin dynamics (MFLD) minimizes an entropy-regularized nonlinear convex functional on the Wasserstein space over R^d, and has gain
arXiv:2605.16932v1 Announce Type: new Abstract: Robots deployed in unstructured human environments must frequently execute long-horizon missions, such as find the mug, then the chair, then the printer
arXiv:2502.05462v2 Announce Type: replace Abstract: We propose a real-time implementable motion planning framework for cooperative object transportation by nonholonomic mobile manipulator robots (MMRs
arXiv:2605.17152v1 Announce Type: new Abstract: Multimodal LLMs are evolving from vision-language to tri-modality that see, hear, and read, yet pipelines and benchmarks remain English-centric and comp
arXiv:2605.17421v1 Announce Type: new Abstract: Accurate visual state estimation has been a central topic in robotics with a wide range of applications in robot navigation, autonomous driving, and aut
arXiv:2605.16384v1 Announce Type: cross Abstract: Accurate and effective discrete image tokenization is crucial for long image sequence processing. However, current methods rigidly compress all conten
arXiv:2605.18447v1 Announce Type: new Abstract: Autonomous rendezvous and proximity operations around uncooperative, unknown spacecraft are critical for active debris removal and on-orbit servicing mi
arXiv:2605.16414v1 Announce Type: new Abstract: We present NERVE (Neuromorphic Vision and Radar Ensemble), a multi-sensor dataset comprising 257 minutes of synchronized recordings from five sensors: t
arXiv:2605.16447v1 Announce Type: cross Abstract: Spatiotemporal forecasting is critical for real-world applications like traffic management, yet capturing reliable interactions remains challenging un
arXiv:2605.16893v1 Announce Type: new Abstract: Recent studies introduce conditional memory modules that decouple knowledge storage from neural computation, enabling more direct knowledge access. Comp
arXiv:2605.16818v1 Announce Type: cross Abstract: Learning physical dynamics directly from incomplete observations is challenging because authentic occlusions are structured, sample-dependent, and oft
arXiv:2601.23154v2 Announce Type: replace-cross Abstract: Pain management in intensive care usually involves complex trade-offs, since both inadequate and excessive treatment can compromise patient sa
arXiv:2605.17705v1 Announce Type: cross Abstract: Panel data, in which multiple units are repeatedly observed over time, arise throughout science and engineering. Quantifying predictive uncertainty in
arXiv:2605.06088v2 Announce Type: replace Abstract: Understanding open-vocabulary 3D scenes with Gaussian-based representations remains challenging due to fragmented and spatially inconsistent semanti
arXiv:2605.16341v1 Announce Type: new Abstract: Low-rank gradient compression reduces communication in distributed training by representing updates with rank-r factors. Dion is a recent method that ap
🚨Our paper is out in PNAS: we found classic human persuasion techniques worked on AIs in a 'parahuman' way, making them agree to objectionable requests (upping compliance from 35% to 51%) It worked on