Knowledge catalogue
arXiv:2608.00530v1 Announce Type: new Abstract: Infrared-visible image fusion under realistic degradation scenarios is a challenging task, as degradations not only cause a loss of reliable modality-sp
arXiv:2603.19040v2 Announce Type: replace Abstract: Differentially private wireless federated learning (DPWFL) is a promising framework for protecting sensitive user data. However, foundational questi
arXiv:2607.28733v1 Announce Type: cross Abstract: This proceedings contribution elaborates on the findings of arXiv:2605.26234v2: a joint work with Marco Usula, where we introduced a machine learning
arXiv:2408.03230v2 Announce Type: replace Abstract: Quantifying and evaluating image complexity can be instrumental in enhancing the performance of various computer vision tasks. Supervised learning c
arXiv:2607.19345v2 Announce Type: replace-cross Abstract: Large language models that generate step-by-step reasoning traces have achieved strong performance on complex tasks, and extending them to lon
arXiv:2607.29337v1 Announce Type: cross Abstract: Background and Objective: Generating realistic medical images with anatomically accurate segmentation masks helps address the shortage of annotated da
arXiv:2509.25146v2 Announce Type: replace-cross Abstract: This paper develops a mathematical argument and algorithms for building representations of data from event-based cameras, that we call Fast Fe
arXiv:2607.29235v1 Announce Type: cross Abstract: Although world-action models (WAMs) enhance long-horizon robot control by predicting visual evolution before acting, long-horizon reliability demands
arXiv:2607.28935v1 Announce Type: new Abstract: Recently, 3D semantic occupancy prediction has garnered increasing attention for understanding the indoor scene. However, unlike structured outdoor envi
Of course, the concern is that in the end, this thread will be fed into the models' training data, but I feel benchmarking isn't so open and very fragmented. submitted by /u/jinnyjuice [link] [comment
arXiv:2603.25464v2 Announce Type: replace-cross Abstract: Zero-shot reinforcement learning (RL) algorithms aim to learn a family of policies from a reward-free dataset, and recover optimal policies fo
arXiv:2607.29180v1 Announce Type: cross Abstract: Text-to-motion generation must produce motions that are semantically correct, temporally coherent, and physically plausible. A natural approach is to
arXiv:2607.29221v1 Announce Type: cross Abstract: We address the challenge of securely and efficiently outsourcing AI computations from a trusted but computationally weak client to an untrusted but po
arXiv:2607.29000v1 Announce Type: cross Abstract: Multimodal information can improve the accuracy of click-through rate (CTR) prediction and effectively alleviate item cold-start and long-tail problem
arXiv:2308.08794v4 Announce Type: replace Abstract: Tipping points are abrupt, drastic, and often irreversible changes in the evolution of non-stationary and chaotic dynamical systems. For instance, i
arXiv:2607.28643v1 Announce Type: cross Abstract: Automating facilitation in online discussions is a long-standing social concern given the increasing time we spend on online spaces and the failure of
arXiv:2607.29592v1 Announce Type: new Abstract: The primary challenge of continual learning (CL) systems is to learn new tasks while remaining performant on previously learned tasks. A similarly impor
arXiv:2607.29032v1 Announce Type: cross Abstract: Large language model (LLM) agents increasingly operate over long interaction histories, where effective reasoning requires identifying and exploiting
arXiv:2607.29256v1 Announce Type: new Abstract: Designing polyimide structures with specific glass transition temperatures (Tg) is highly challenging. Existing methods primarily focus on target-condit
The egg test for AI 'I hereby offer @elonmusk a million dollar bet against his prediction that Optimus will be better than the best humans in surgery by the end of the decade.' ~ @GaryMarcus Haha. I'm
Kimi K3 has set a new bar for OSS model intelligence! 2.8T params, 1M context, OpenAI-compatible API. Complete guide to running Kimi K3 on Together AI 👇 👏👏 @Kimi_Moonshot 👏👏 https://www.together.ai/bl
**Kimi K3 is Moonshot AI’s 2.8‑trillion‑parameter open‑weight language model—the largest ever released—designed for frontier tasks such as long‑horizon coding and deep reasoning.** Its architecture us
Our Twitch streams with @Cohere_Labs are #1 in the tech category⚡️ Cohere Labs' free ML Summer School series has brought together viewers from 20+ countries to learn about everything from NLP in LLMs
TLDR: There is no one prompting trick that will result in Krea 2 Turbo giving you exactly the style you want and across the whole image. Instead, if you are trying to achieve styles without the use of
arXiv:2607.28487v1 Announce Type: new Abstract: Fine-grained segmentation of auricular structures in CT is challenging because the ear occupies a small image region, cartilage boundaries are highly ir
arXiv:2607.27953v1 Announce Type: new Abstract: Combinatorial optimization problems (COPs) underpin many real-world decisions, but their exponentially large search spaces make high-quality solutions c
arXiv:2607.11623v3 Announce Type: replace Abstract: Real-world paired image dehazing remains challenging because haze degradation is spatially non-uniform, illumination-dependent, and physically ambig
arXiv:2508.16129v3 Announce Type: replace Abstract: Multimodal large language models (MLLMs) have recently demonstrated remarkable reasoning abilities with reinforcement learning paradigm. Although se
arXiv:2607.28410v1 Announce Type: cross Abstract: Parent-order execution is a core problem in algorithmic trading, where the goal is to split a large order into smaller orders while reducing execution
arXiv:2607.28236v1 Announce Type: cross Abstract: Pre-trained language models have significantly improved sentence representation learning, yet their embedding remain sensitive to semantic preserving
I got a fever and cough and assumed that this is some viral infection that will just go away on its own. I wear a Fitbit watch which measures my heart rate. Just out of curiosity I posted my symptoms
arXiv:2301.01188v5 Announce Type: replace-cross Abstract: Deep R Programming is a comprehensive and in-depth introductory course on one of the most popular languages for data science. It equips ambiti
arXiv:2512.03661v2 Announce Type: replace Abstract: Activation steering has emerged as a powerful method for guiding the behavior of generative models towards desired outcomes such as toxicity mitigat
arXiv:2507.18046v2 Announce Type: replace Abstract: Recent advances in AI-generated video have shown strong performance on text-to-video tasks, particularly for short clips depicting a single scene. H
arXiv:2607.27665v1 Announce Type: new Abstract: Federated graph learning enables collaborative training over decentralized graph data without sharing raw graph information. As such risks evolve, clien
arXiv:2607.28571v1 Announce Type: new Abstract: Operational Earth observation increasingly calls for answering queries such as ``find the image pairs where a new building appeared.'' This means search
arXiv:2607.27969v1 Announce Type: new Abstract: Despite substantial progress in remote sensing multi-temporal change detection (MTCD), most existing MTCD methods still represent the dynamic process at
arXiv:2607.26634v1 Announce Type: cross Abstract: Organizational digitalization expands cybersecurity risks, making cybersecurity an increasingly important research area in Information Systems (IS). A
arXiv:2607.10285v2 Announce Type: replace Abstract: We study how unsupervised autoencoders trained on microscopic spin configurations from the Ising model learn macroscopic, theory-relevant variables
arXiv:2508.18007v2 Announce Type: replace Abstract: Fully Unsupervised Anomaly Detection (FUAD) addresses the practical scenario where training data is contaminated with unlabeled anomalies. This sett
arXiv:2602.23050v2 Announce Type: replace Abstract: Deep state-space models (DSSMs) enable temporal predictions by learning the underlying dynamics of observed sequence data. They are often trained by
arXiv:2409.08521v2 Announce Type: replace-cross Abstract: In cybersecurity practice, new forms of cyberattacks continuously emerge, deliberately designed to evade defense systems that rely on previous
arXiv:2607.27865v1 Announce Type: new Abstract: Perceiving human motion and intent at long range is a prerequisite for socially intelligent aerial robots, yet the data to learn it barely exists. We in
arXiv:2602.05307v2 Announce Type: replace Abstract: Large reasoning models (LRMs) achieve strong performance by producing long chains of thought, but their inference costs are high and often generate
arXiv:2511.21007v2 Announce Type: replace Abstract: Selecting an appropriate pre-trained source model is a critical, yet computationally expensive, task in transfer learning. Model Transferability Est
arXiv:2603.16140v2 Announce Type: replace Abstract: Reinforcement learning with verifiable rewards (RLVR) has driven recent capability advances of large language models across various domains. Recent
arXiv:2607.28624v1 Announce Type: new Abstract: We introduce PhiZero, a physical world model built around physical language, a compact discrete representation of world-state transitions. Existing phys
arXiv:2603.11325v2 Announce Type: replace Abstract: Low-field to high-field MRI synthesis has emerged as a promising strategy to improve image quality when access to high-field scanners is limited. Ho
arXiv:2602.04635v2 Announce Type: replace Abstract: Robots are finding wider adoption in human environments, increasing the need for natural human-robot interaction. However, understanding a natural l
arXiv:2607.27271v1 Announce Type: new Abstract: Code models are increasingly trained with execution feedback, but most training signals still stop at correctness. This leaves an important gap for syst
arXiv:2607.27835v1 Announce Type: new Abstract: Accurate cell segmentation and classification are foundational to digital pathology, enabling quantitative tissue analysis for diagnosis and treatment p
arXiv:2607.28525v1 Announce Type: new Abstract: Many real-world graphs support multiple predictive tasks over the same underlying structure, creating an opportunity to reuse supervision across node cl
arXiv:2601.13732v2 Announce Type: replace Abstract: The fact that robots are getting deployed more often in dynamic environments, together with the increasing complexity of their software systems, rai
arXiv:2607.28261v1 Announce Type: new Abstract: Video re-shooting aims to regenerate videos with controllable camera motion and viewpoint. Existing methods rely on explicit 3D priors, which are limite
arXiv:2607.27179v1 Announce Type: cross Abstract: Conversational AI is increasingly positioned as a teammate rather than a tool, yet we know little about how its presence reshapes communication among
arXiv:2408.06083v2 Announce Type: replace Abstract: In the field of monocular depth estimation (MDE), many models with excellent zero-shot performance in general scenes emerge recently. However, these
arXiv:2607.27966v1 Announce Type: new Abstract: Graph Foundation Models (GFMs) have recently emerged as a promising paradigm for general-purpose graph learning, aiming to learn reusable knowledge that
arXiv:2511.07210v3 Announce Type: replace Abstract: Clean-image backdoor attacks, which use only label manipulation in training datasets to compromise deep neural networks, pose a significant threat t
arXiv:2607.26752v1 Announce Type: new Abstract: Medical world models aim to learn a latent state of patient or organ physiology and a transition function that forecasts how that state evolves under in
arXiv:2505.06945v5 Announce Type: replace Abstract: Multimodal data modeling has emerged as a powerful approach in clinical research, enabling the integration of diverse data types such as imaging, ge