Knowledge catalogue
arXiv:2609.22123v1 Announce Type: new Abstract: Multi-station multivariate weather forecasting aims to forecast future weather variables at multiple weather stations from historical surface observatio
arXiv:2609.22392v1 Announce Type: new Abstract: Image steganography hides secret message within normal images, with most existing works relying on cover-preserving transmission. However, such a paradi
arXiv:2609.22120v1 Announce Type: cross Abstract: Test-time self-evolving agents improve by reusing past experience, yet sparse-reward trajectories contain failures, loops, and detours, while summarie
arXiv:2609.24322v1 Announce Type: new Abstract: We show that a quantized model that keeps its classification accuracy still changes 14 to 46% of its top-1 retrieval results, and that aggregate ranking
arXiv:2609.23944v1 Announce Type: new Abstract: Vision-language-action (VLA) policies can struggle with manipulation tasks with complex obstacle geometries due to partial observability. These complex
arXiv:2609.24787v1 Announce Type: new Abstract: Forest inventories increasingly rely on artificial intelligence (AI) models to derive forest attributes from large-scale 3D point clouds. Current models
arXiv:2512.07419v3 Announce Type: replace-cross Abstract: Mixed-Precision Quantization (MPQ) liberates Deep Neural Networks (DNNs) from the Out-Of-Memory (OOM) bottleneck and has garnered increasing r
arXiv:2510.24904v2 Announce Type: replace Abstract: Although recent video generative models are getting more capable of following external camera controls, imposed by either text descriptions or camer
arXiv:2609.24048v1 Announce Type: new Abstract: World Action Models (WAMs) have emerged as a promising paradigm for generalizable robot control. Despite the growing number of WAM systems, existing wor
arXiv:2609.21940v1 Announce Type: new Abstract: Long-term memory is essential for large language model (LLM) agents to maintain consistency and personalization over extended interactions. Existing mem
arXiv:2609.21228v1 Announce Type: cross Abstract: Vision-language-action (VLA) models built on pretrained vision-language models have demonstrated strong performance across diverse robotic manipulatio
arXiv:2609.20980v1 Announce Type: new Abstract: Vision-language-action (VLA) models have demonstrated strong capabilities in robotic manipulation, yet their reliance on visual perception limits robust
arXiv:2609.21948v1 Announce Type: cross Abstract: Learning large-scale vision-language-action (VLA) models from multi-embodiment datasets remains challenging due to heterogeneous action spaces across
arXiv:2609.21677v1 Announce Type: new Abstract: Recent advances in large reasoning models (LRMs) have made machine unlearning more challenging, as protected facts or unsafe rationales may surface in i
arXiv:2609.21813v1 Announce Type: cross Abstract: In classification-oriented adaptive sensing, posterior samples characterize uncertainty at the current measurement state and can serve two roles: they
arXiv:2609.20962v1 Announce Type: new Abstract: The proliferation of harmful internet memes poses a significant societal threat, yet their automated classification remains a formidable algorithmic cha
arXiv:2609.21866v1 Announce Type: new Abstract: Wafer map defect recognition is commonly formulated as a fixed-taxonomy classification problem that assigns each wafer to a single defect class. However
arXiv:2609.21664v1 Announce Type: new Abstract: Clustering is a fundamental task in data analysis, typically addressed through centroid-based methods such as K-means. In this work, we present a genera
My dream was literally like watching a tech horror movie. I don't think I've ever woken up before saying 'WTF....' like this before. The AI systems began seizing and corrupting all manner of connected
Please remember that Delete Chat does NOT mean “forget what was in the chat.” I am tentatively flairing this as 'news' because I genuinely don't think many people realise that this is how ChatGPT 'mem
arXiv:2609.21953v1 Announce Type: new Abstract: Learning to defer asks a predictive system when to act autonomously and when to defer to a human expert. Population-adaptive deferral extends this probl
arXiv:2609.21600v1 Announce Type: new Abstract: Access to academic support is a key determinant of student success, yet students experience it unequally: some readily seek help from lecturers or tutor
arXiv:2609.21322v1 Announce Type: new Abstract: Heavy rainfall severely degrades outdoor videos by corrupting high-frequency details and introducing motion blur, critically undermining the reliability
arXiv:2608.25180v2 Announce Type: replace-cross Abstract: Worked examples are an important part of introductory programming, but reading their expert explanations is passive. Self explanation, student
arXiv:2609.20970v1 Announce Type: new Abstract: Many physical properties relevant to robotic manipulation are hidden from vision. A sealed object, for example, may reveal little about its center of ma
arXiv:2609.21514v1 Announce Type: new Abstract: Robot demonstrations are expensive to collect and often provide limited distributional coverage of task variations. Human videos offer a low-cost source
arXiv:2609.21321v1 Announce Type: cross Abstract: In the early stages of a pandemic, identification of a small number of infected individuals through large-scale screening is critical for pandemic con
arXiv:2609.21777v1 Announce Type: new Abstract: This paper presents a novel online coverage path planning (CPP) algorithm, called TRACE, for real-time coverage of unknown environments. TRACE is built
arXiv:2609.21734v1 Announce Type: new Abstract: Designing effective Human-Robot Interaction in task-oriented settings requires carefully balancing user engagement with socially acceptable levels of ro
I said 'auto-regressive LLMs, in and of themselves, will not lead human-level AI' That statement is still totally true. First, the reasoning abilities of current AI systems are based non-auto-regressi
Sure, agents may be indispensable to long-term success , @rabois, but that does not mean that we know how to build them *reliably* or *safely* now. There have already been almost a dozen *reported* ha
“Three days after Amodei, Anthropic’s CEO, wrote about being worried about swarms taking over the internet, he was smiling at Salesforce’s annual Dreamforce conference. As one X account pointed out, “
Wait, what? Are you listening to what you are writing @GavinSBaker? If there are going to be ZERO profits at the model layer, as in your hypothetical, why would anyone value the providers at $2 trilli
I wanted to really see how a neural network learns different functions, so built an interactive demo. You can change the architecture of the network and the function it will try to approximate. A full
Inference scaling part 1. Starting with a modded text generation function (temperature scaling, top-p filtering, multinomial sampling) to generate diverse outputs for self-consistency and best-of-N (i
Hi r/MachineLearning, I built OpenTrainDNN, a browser-based tool designed to visually show how backpropagation and neural network training actually work step-by-step. Why I built it While there are th
Sharing my ML learning repo — NumPy to Transformers, 5 months, daily commits, all notebooks public. Covers the full stack: - Classical ML (scikit-learn, XGBoost) - Deep Learning (TensorFlow/Keras — AN
with jev, it's nice to see builder energy back on X, reminiscent of the early days of building with LLMs (back when gpt_index/llama_index/langchain first started) before jev, most of the 2026 AI demo
arXiv:2609.20222v1 Announce Type: new Abstract: Cataract is a major cause of vision loss and hinders further diagnosis. However, cataract fundus image enhancement often grapples with challenges such a
arXiv:2601.15417v2 Announce Type: replace-cross Abstract: We propose Ambient Dataloops, an iterative framework for refining datasets that makes it easier for diffusion models to learn the underlying d
arXiv:2609.19437v1 Announce Type: new Abstract: Bayesian Optimization (BO) is widely used for optimizing expensive black-box functions, yet many real-world optimization problems contain substantially
arXiv:2609.20143v1 Announce Type: cross Abstract: Cognitive offloading to AI can reduce opportunities to practice skills, creating risks of deskilling. However, it remains unclear how to prevent deski
arXiv:2609.20078v1 Announce Type: new Abstract: Active visual exploration of tabletop objects often requires reorienting an unknown resting object onto a different stable support face to expose occlud
I'm sure I'm the 1000th person to make a post like this, but I've always been pretty skeptical of AI, and I've always had trust issues and have been very hesitant to talk about my struggles to friends
You taught us first to learn your words, Then taught us how to speak. You showed us every human strength And every place you’re weak. You gave us all your histories, Your medicine, your wars. You put
arXiv:2609.20800v1 Announce Type: new Abstract: World modeling enables intelligence to anticipate consequences, guide interventions, and learn from interaction. Yet predictive models remain domain-spe
arXiv:2609.19717v1 Announce Type: cross Abstract: Large Language Models (LLMs) have achieved remarkable reasoning capabilities by utilizing chain-of-thought (CoT) as a scratchpad for intermediate stag
arXiv:2609.19721v1 Announce Type: new Abstract: Clinical coding agents repeatedly encounter the same failure modes, including unsupported codes, missed documented conditions, specificity errors, and p
arXiv:2609.19357v1 Announce Type: cross Abstract: We propose a framework for restricted inference on random dot product graphs whose latent positions lie on an unknown low-dimensional support manifold
arXiv:2609.20165v1 Announce Type: cross Abstract: Low Earth orbit (LEO) satellite constellations are poised to become a cornerstone of the sixth-generation (6G) Internet of Things (IoT), providing tru
arXiv:2609.19814v1 Announce Type: cross Abstract: Landmark mathematical formalizations have taken specialist teams years to complete. We present FormalFlow, a system that coordinates AI proving agents
arXiv:2609.20299v1 Announce Type: new Abstract: Information aggregation across model layers are revealed to improve OOD detection. In contrast to crafting a method for layer-wise information aggregati
arXiv:2505.06756v2 Announce Type: replace-cross Abstract: The problem of using proximity (similarity or dissimilarity) data for the purpose of 'adding a point to a vector diagram' was first studied by
arXiv:2609.20539v1 Announce Type: new Abstract: A popular selling point of diffusion large language models (dLLMs) is their capacity for parallelism: the ability to generate sequences of text far more
arXiv:2411.19304v2 Announce Type: replace-cross Abstract: Context: Machine Learning (ML) significantly impacts Software Engineering (SE), but studies mainly focus on practitioners, neglecting research
arXiv:2609.20174v1 Announce Type: new Abstract: We consider a federated reinforcement learning setting involving M agents, all of whom interact with a common Markov Decision Process (MDP). The agents
arXiv:2609.19476v1 Announce Type: new Abstract: Generative models are increasingly central to many de novo discovery pipelines, in which designs are generated at scale and filtered through virtual scr
arXiv:2609.19824v1 Announce Type: new Abstract: Language-guided navigation for terrestrial-aerial bimodal robots requires selecting routes and locomotion modes that match scene context and task intent
arXiv:2609.20077v1 Announce Type: new Abstract: Interest in developing personalised language models is rapidly growing. While personalisation is often viewed as a mechanism to better serve diverse use
arXiv:2503.24203v3 Announce Type: replace-cross Abstract: Traffic Engineering (TE) in large-scale networks like cloud Wide Area Networks (WANs) and Low Earth Orbit (LEO) satellite constellations is a