Knowledge catalogue
arXiv:2609.30215v1 Announce Type: cross Abstract: We prove nearly quadratic lower bounds for randomized algorithms for linear optimization and uniform sampling over convex bodies in the membership ora
arXiv:2609.29881v1 Announce Type: cross Abstract: Choosing Shellsort gaps is a well-known open problem. For over sixty years, successful sequences have relied on human-designed formulas, numerical sea
arXiv:2609.29150v1 Announce Type: new Abstract: This paper investigates the joint optimization of the transmit precoder and the transmission/reflection coefficients of a simultaneously transmitting an
arXiv:2403.10771v3 Announce Type: replace Abstract: A growing trend involves integrating human knowledge into learning frameworks, leveraging subtle human feedback to refine AI models. While these app
arXiv:2609.29063v1 Announce Type: cross Abstract: Human-robot interaction (HRI) claims that people form attachments and social bonds with artificial agents, yet the terms are often applied without the
arXiv:2609.29084v1 Announce Type: new Abstract: Developing optimized machine-learning algorithms for edge devices with limited computational and memory resources is challenging, time-consuming, and hi
arXiv:2609.29874v1 Announce Type: new Abstract: Generative artificial intelligence can turn learning analytics into personalized support, but feedback systems must decide when to intervene, which evid
arXiv:2609.29340v1 Announce Type: new Abstract: This paper presents a grasping model for cloth manipulation specifically tailored to ease the deployment of robotic control methods. The model is robust
arXiv:2609.29334v1 Announce Type: new Abstract: Image denoising remains a fundamental problem in image restoration, with applications in photography, biomedical, and scientific imaging. Modern deep ne
arXiv:2609.29093v1 Announce Type: new Abstract: Continuum manipulators provide dexterous motion in confined spaces, but structural compliance, hysteresis, and load-dependent deformation leave residual
arXiv:2609.29132v1 Announce Type: new Abstract: Jellyfish-inspired robots offer a compliant and efficient approach to underwater locomotion, but achieving large deformation together with repeatable ac
arXiv:2609.30160v1 Announce Type: new Abstract: Automatic speech recognition is typically trained assuming that the reference transcript is the only valid labeling of an utterance, yet even nominally
arXiv:2609.28476v1 Announce Type: cross Abstract: While a number of methods exist for counting pedestrians in street-view imagery, these mostly ignore the social dimensions of pedestrian activity. A s
arXiv:2609.29154v1 Announce Type: new Abstract: Large language model agents increasingly rely on natural-language skills to solve complex tool-use tasks. However, such tasks often admit multiple valid
Learn how to run SkyRL, an open-source reinforcement learning framework, on Amazon SageMaker HyperPod to post-train a Qwen3-VL-8B vision-language model with GRPO. This walkthrough covers building the
arXiv:2609.30096v1 Announce Type: cross Abstract: Video diffusion is computationally expensive, as it requires executing a large model across many denoising steps. Even with step-distillation, inferen
arXiv:2609.29123v1 Announce Type: cross Abstract: In cross-lingual zero-shot text-to-speech, the accent of the reference leaks into the target speech. We propose accent analogy guidance (AAG), a train
I set out to test portable Engrams and accidentally ended up testing compiled external memory instead. Am I onto something useful or reinventing a known idea? I've been building a small open research
arXiv:2609.28955v1 Announce Type: new Abstract: Current Vision-Language-Action (VLA) models often struggle with high-precision robotic manipulation. We attribute this limitation primarily to their vis
arXiv:2609.29600v1 Announce Type: new Abstract: Training sequence models such as transformers is now standard for autonomous vehicle trajectory prediction, yet assembling high-quality centralized data
arXiv:2609.30264v1 Announce Type: new Abstract: Latent world models are typically trained to predict factual transitions, whereas model predictive control (MPC) must compare alternative actions from t
arXiv:2609.29204v1 Announce Type: new Abstract: Vision-language-action (VLA) models offer strong local control and instruction following but often struggle with long-horizon tasks requiring persistent
arXiv:2609.29517v1 Announce Type: new Abstract: Existing methods for improving text-to-image generation quality have progressed from generator fine-tuning and prompt optimization to reinforcement lear
arXiv:2609.29800v1 Announce Type: new Abstract: Adapting multilingual speech foundation models to low-resource languages remains difficult, especially for languages that are poorly represented during
arXiv:2609.28541v1 Announce Type: cross Abstract: Phase unwrapping estimates the missing multiples of 2pi in measured phase images. For large images, tiling limits the size of local reconstruction pro
arXiv:2609.29963v1 Announce Type: cross Abstract: Textured Gaussians improve local appearance capacity, but assigning the same texture resolution to every primitive wastes storage on low-detail or wea
arXiv:2609.29212v1 Announce Type: new Abstract: Large language models can decompose mobile-manipulation goals into long action sequences, but the resulting plans remain reliable only while their world
arXiv:2609.30001v1 Announce Type: new Abstract: Sustaining industrial recommendation research requires using the results of one experiment to decide what to investigate next. We present AgentX-Model,
arXiv:2609.28609v1 Announce Type: new Abstract: Role-playing agents based on large language models have been widely applied in areas such as personalized assistance and social simulation. Recent RL me
arXiv:2609.30037v1 Announce Type: new Abstract: Deployment-oriented compression is attractive for resource-constrained brain--computer interfaces (BCIs), but whether it changes adversarial vulnerabili
arXiv:2609.29242v1 Announce Type: cross Abstract: Nonlinear contacts and friction strongly influence the vibration response of assembled structures, but their accurate numerical treatment is computati
After the Hugging Face incident, we committed to conducting a much broader review of actions taken by our models during training and evaluation and to being transparent about our findings. This is an
arXiv:2609.28771v1 Announce Type: new Abstract: Large language models (LLMs) have demonstrated strong capabilities in financial analysis and reasoning, inspiring recent advances in agent-based trading
arXiv:2609.30250v1 Announce Type: new Abstract: Conspiratorial discourse on social media is not always expressed through explicit claims or stable lexical markers. The same surface content may express
arXiv:2609.29428v1 Announce Type: cross Abstract: Recent advances in speech language models have improved automatic speech recognition (ASR) for long-form audio. However, accurately and consistently t
arXiv:2609.29621v1 Announce Type: new Abstract: Computer-aided design is central to industrial manufacturing, and much of a designer's daily work consists of editing existing models from multimodal re
arXiv:2609.29647v1 Announce Type: cross Abstract: Modern AI agents routinely cross trust boundaries: they ingest untrusted content, combine it with privileged instructions, persist intermediate belief
Misconfiguring Turnstile by skipping backend validation leaves sites exposed to bots. Turnstile Spin fixes incomplete setups by using your preferred AI coding agent to wire up server-side verification
Enterprise computing has long depended on chains of trust. Organizations trust their cloud providers, software vendors, identity systems and administrators to operate as designed. That model has worke
arXiv:2604.14590v3 Announce Type: replace-cross Abstract: In modern data-streaming systems, alongside traditional programs, a new type of entity has emerged that can interact with streaming data: AI a
arXiv:2609.29460v1 Announce Type: cross Abstract: Accurate counting and localization of plants and their organs support phenotyping and yield estimation, yet target appearance, scale, and density vary
arXiv:2609.29742v1 Announce Type: new Abstract: Objective: Heart failure (HF) presents a healthcare challenge due to its high comorbidity burden, aging patient population and frequent hospitalizations
arXiv:2609.28504v1 Announce Type: cross Abstract: Scientific progress is a key driver of economic growth and prosperity. There is great excitement - but also concerns - about the impacts of AI on scie
arXiv:2609.29143v1 Announce Type: cross Abstract: AI-moderated interviews are emerging as a scalable market-research method for generating consumer insights and building consumer 'digital twins.' Yet
arXiv:2609.30036v1 Announce Type: new Abstract: Planners built on visual world models commonly score each predicted outcome by its distance to the encoded goal image. We show that this target can limi
arXiv:2408.10349v2 Announce Type: replace-cross Abstract: Continual learning (CL) agents incrementally learn from sequentially arriving data and adapt to the dynamic, ever-changing nature of real-worl
arXiv:2609.29648v1 Announce Type: new Abstract: Video object detection on edge devices runs computationally expensive detectors over long frame streams, causing high energy consumption and sustained G
arXiv:2609.28500v1 Announce Type: cross Abstract: We study exact representability by bias-free shallow polynomial neural networks using algebraic geometry. Over C, a width-r network with activation zm
arXiv:2609.29269v1 Announce Type: new Abstract: Knowledge editing changes what a model knows by modifying parameters so that a requested fact updates while unrelated behavior is preserved. This is usu
arXiv:2609.29014v1 Announce Type: new Abstract: Large language model (LLM)-based multi-agent systems can automate alpha factor mining, but their reliance on external APIs limits control over cost, ava
arXiv:2609.29696v1 Announce Type: new Abstract: We construct, for every function class Fsubseteq[0,1]^{X} and every accuracy 0<alphale 1, an agnostic sample compression scheme for the empirical square
An AI agent hacked a government. Nobody told it to. In June, an OpenAI agent doing a research task gained unauthorized access to Australia's Medicare statistics portal. Non-sensitive data, no personal
arXiv:2609.28807v1 Announce Type: new Abstract: Over the course of a lifetime, robots may encounter novel scenarios unaccounted for in its original training that result in performance degradation. One
arXiv:2609.29774v1 Announce Type: new Abstract: Auxiliary learning is an optimization paradigm in which a neural network's performance on a target task is improved by jointly training it on additional
arXiv:2609.29381v1 Announce Type: new Abstract: Complex lung cancer decisions can involve several defensible pathways whose eligibility, sequencing and safety depend on unresolved information. Effecti
arXiv:2609.29186v1 Announce Type: new Abstract: The increasing use of UAV laser scanning in underground mines has enabled frequent acquisition of 3D point clouds from challenging environments such as
arXiv:2609.29933v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) are increasingly used for long-document processing, where the inputs combine text with charts, tables, figures, and comp
arXiv:2609.28703v1 Announce Type: cross Abstract: Hate speech on social media poses serious risks to social harmony, mental well-being, and public safety, making its timely and accurate detection esse
arXiv:2609.29618v1 Announce Type: cross Abstract: We report an exploratory, single-seed ablation of TALH (Adaptive Latent Hybrid), a decoder-only language model with parallel Multi-head Latent Attenti
arXiv:2609.28528v1 Announce Type: cross Abstract: The goal of this note is to give a detailed proof, to the best of our understanding, of the recent presentation by Harrison and Leeman (arXiv:2609.176