Knowledge catalogue
arXiv:2609.18655v1 Announce Type: new Abstract: Quantum neural networks (QNNs) are typically built from variational quantum circuits (VQCs), which are limited by local measurements. Adaptive non-local
arXiv:2609.18148v1 Announce Type: new Abstract: The remarkable success of large language models (LLMs) has provided important inspiration for the next generation of recommender systems. Structurally,
arXiv:2609.17736v1 Announce Type: cross Abstract: Most molecular transitions occur on timescales far beyond direct molecular dynamics simulations. The committor, the probability that a configuration r
arXiv:2609.17965v1 Announce Type: new Abstract: AI is changing what leaders must judge, explain, learn, and coordinate, yet existing measures do not capture these behaviors at the level needed to stud
arXiv:2609.18961v1 Announce Type: new Abstract: Mechanistic interpretability identifies sparse subsets of heads and MLP blocks that carry specific behaviors. We ask whether such causal signals can gui
arXiv:2609.17709v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) systems typically employ fixed retriever and generator configurations across queries, despite substantial differe
arXiv:2412.00176v4 Announce Type: replace Abstract: We explore whether pre-training on datasets with paintings is necessary for a model to learn an artistic style with only a few examples. To investig
arXiv:2609.18304v1 Announce Type: new Abstract: Large language model (LLM) agents increasingly tackle long-horizon tasks through multi-step environment interaction, yet a single erroneous action can a
arXiv:2609.17726v1 Announce Type: cross Abstract: Reconstructing the mass of a heavy resonance from its decay products with missing energy is one of the central tasks that directly determine the sensi
arXiv:2609.17956v1 Announce Type: new Abstract: Large-scale machine-translation (MT) systems are typically evaluated on random samples from a corpus whose distributional composition is an artifact of
🔥 take: @CompleteSkeptic//TypeSafe killed Quantum Computing Jev feels a bit like bringing the quantum-computing intuition to AI: evaluate a distribution of possibilities in parallel instead of generat
arXiv:2609.18407v1 Announce Type: cross Abstract: Weekly influenza surveillance counts guide vaccine distribution and public-health alerts, yet they are hard to forecast. Each region offers only a few
The latest issue of Scientific American (@sciam) features our Smart Cellular Bricks research: simple cubes that collectively recognize their own shape and repair themselves without a central brain. ht
arXiv:2609.18163v1 Announce Type: new Abstract: Forecasting scientific relations can guide discovery by identifying promising connections before they emerge. Existing approaches often model concept se
arXiv:2609.18565v1 Announce Type: cross Abstract: We propose a compact NISQ-compatible quantum transformer architecture for synthetic QNLP sequence modelling. The model preserves the autoregressive ne
arXiv:2609.18413v1 Announce Type: new Abstract: What is a gait? Appearance-based gait networks consider a gait as the human shape and motion information from images. Model-based gait networks treat a
arXiv:2609.17901v1 Announce Type: cross Abstract: Generative modeling of time-dependent data is typically formulated on a discrete temporal grid, restricting supervision to the observed timestamps in
What AI has done so far: MEDICINE • Helped paralysed people speak again. (Brain implants turn intended speech into words, even recreating their own voice.) • Helped a paralysed man stand and walk agai
arXiv:2609.17637v1 Announce Type: new Abstract: Restricting what a module can read may improve what a system learns to compute. We test this in a preregistered confirmation with sixty four-cell system
arXiv:2609.18960v1 Announce Type: new Abstract: Quality-aware synthetic-data selection rests on a proxy: examples that an LLM judge rates as good should also help a downstream model learn. In a contro
arXiv:2609.17594v1 Announce Type: new Abstract: Can gradient-based training learn the rank needed to store and compose associations in a matrix memory? In our earlier study, we used a matrix-augmented
arXiv:2609.17909v1 Announce Type: cross Abstract: We introduce Zing-0.5, a 5B autoregressive world model designed for playability: users can explore generated worlds, influence unfolding events, and r
arXiv:2609.16031v1 Announce Type: cross Abstract: Ultra-low-dose computed tomography (ULDCT) reduces radiation exposure but suffers from severe noise that degrades diagnostic image quality. Existing d
hey folks, it's Merve from Hugging Face 🤗 with the latest cool things happening in between LLMs and 3D, we have written an illustrative explainer guide on 3D asset landscape, what 3D representation yo
arXiv:2609.16606v1 Announce Type: new Abstract: Approximating the input-output behavior of a multivariable black-box function from limited data is challenging when blind to the importance of its input
arXiv:2501.09166v2 Announce Type: replace-cross Abstract: Pretrained Transformers keep what they learned in their weights and lose what they observe once a session ends. The first version of this pape
arXiv:2609.17065v1 Announce Type: cross Abstract: AI assistance places a metacognitive demand on users, who must judge their own competence and the system's. Yet designers lack comparative evidence on
arXiv:2609.17039v1 Announce Type: new Abstract: Sparse-view 3D scene reconstruction with 3D Gaussian Splatting (3DGS) is inherently underconstrained. Plausible renderings can also coexist with erroneo
Learn how to automate end-to-end PII detection and redaction from scanned documents at scale using Amazon Bedrock Data Automation with a custom blueprint, AWS Step Functions, and AWS Lambda. A custom
arXiv:2609.16017v1 Announce Type: cross Abstract: Time-of-flight non-line-of-sight (NLOS) imaging recovers information from hidden objects by analyzing the time of flight of indirect photons scattered
arXiv:2609.16768v1 Announce Type: new Abstract: IMU-based human activity recognition (HAR) enables continuous, privacy-friendly monitoring of daily activities using wearable sensors. However, building
arXiv:2609.16489v1 Announce Type: cross Abstract: Electrocardiogram (ECG) delineation identifies the boundaries of P waves, QRS complexes, and T waves, providing structural annotations that can guide
arXiv:2609.17189v1 Announce Type: new Abstract: 3D hand mesh reconstruction is a challenging yet essential task for downstream applications, including human-robot interaction and AR/VR. Although conve
arXiv:2609.17172v1 Announce Type: new Abstract: A walking robotic hand must use the same fingers to move its body, support its weight, and interact with the environment. We show how an anthropomorphic
arXiv:2609.16594v1 Announce Type: new Abstract: Generative models trained on a single image often struggle to balance global structural integrity and local diversity. Existing single-image generation
arXiv:2609.16946v1 Announce Type: new Abstract: No-reference video quality assessment (NR VQA) has recently seen promising progress with deep learning. However, video data is inherently large, and pro
arXiv:2601.12547v2 Announce Type: replace Abstract: Clinical artificial intelligence increasingly builds high-dimensional representations of patients, yet every finite clinical model is an abstraction
arXiv:2609.16155v1 Announce Type: cross Abstract: This paper presents a novel framework leveraging Large Language Models (LLMs) to generate synthetic time series data for manufacturing processes. Moti
arXiv:2609.16033v1 Announce Type: cross Abstract: Cervical vertebral maturation (CVM) assessment plays a pivotal role in orthodontic diagnosis and determining the optimal timing of treatment, especial
As enterprise organizations scale mission-critical applications, storage I/O and memory access can become severe operational bottlenecks. Whether its Oracle databases, in-memory databases like SAP HAN
arXiv:2609.16004v1 Announce Type: cross Abstract: While AI systems increasingly shape high-stakes societal domains, their governance is limited by the lack of risk management methods that operate on r
arXiv:2512.15708v2 Announce Type: replace Abstract: Foundation models are vital tools in various Computer Vision applications. They take as input a single RGB image and output a deep feature represent
arXiv:2609.16540v1 Announce Type: cross Abstract: State Space Models (SSMs) have emerged as a compelling alternative to Transformers, enabling sequence modeling with constant memory and linear compute
arXiv:2609.17521v1 Announce Type: cross Abstract: Interactive control for video generation is moving from coarse prompts toward fine-grained, physically meaningful manipulation of dynamic scenes. Yet
arXiv:2609.17249v1 Announce Type: new Abstract: Finite-dimensional Koopman models enable efficient linear prediction and control of nonlinear robotic systems. However, models learned purely from traje
arXiv:2609.17061v1 Announce Type: cross Abstract: Message-passing Graph Neural Networks (GNNs) iteratively propagate and aggregate local neighborhood information followed by global readout to learn gr
arXiv:2609.16737v1 Announce Type: cross Abstract: Generative video models can serve as a promising backbone for robot navigation by predicting future observations as video plans. Recent approaches oft
arXiv:2609.16306v1 Announce Type: new Abstract: Bharatanatyam is the oldest Indian Classical Dance (ICD) which is learned and practiced across India and the world. Adavu is the core of this dance form
arXiv:2609.17019v1 Announce Type: new Abstract: While Chain-of-Thought (CoT) reasoning has been proven to be effective, it often leads to overthinking, resulting in computational overhead, inference l
arXiv:2609.16289v1 Announce Type: cross Abstract: In social dilemma games, additional rewards or punishments have been studied as means of promoting cooperation. Therefore, it is important to investig
arXiv:2609.16076v1 Announce Type: cross Abstract: Large Language Models (LLMs) excel at programming tasks but frequently fail at deterministic, fine-grained reasoning in natural language, relying heav
arXiv:2609.15980v1 Announce Type: cross Abstract: When a video model generates physically incorrect motion, did it fail to learn the correct motion, or did it learn it but fail to use it? We show the
arXiv:2606.13633v2 Announce Type: replace-cross Abstract: Aerial wildfire suppression requires decisions about when, where, and how to deploy limited aircraft. We present an intervention-design framew
arXiv:2603.25175v2 Announce Type: replace Abstract: Monocular egocentric 3D pose estimation is difficult because severe foreshortening, self-occlusion, and a restricted field of view often remove the
arXiv:2512.24999v2 Announce Type: replace-cross Abstract: In this work, we introduce extit{basic inequalities} for first-order iterative optimization algorithms, forming a simple yet versatile framewo
arXiv:2609.15072v1 Announce Type: cross Abstract: Methods of Branched Optimal Transport (BOT) mimic the economy and efficiency of natural tree-like structures, such as those found in rivers and biolog
Manually tagging thousands of catalog products is slow and inconsistent. This walkthrough shows how to customize Qwen3-8B with supervised fine-tuning (SFT) and reinforcement learning with verifiable r
arXiv:2609.13714v1 Announce Type: new Abstract: An updated model can improve an aggregate metric while degrading a slice that matters to a downstream user. We study checkpoint selection subject to non
arXiv:2609.15393v1 Announce Type: cross Abstract: Text-to-Time Series Generation (Text-to-TS) provides a promising paradigm for synthesizing time series from natural language, enabling scenario-specif
arXiv:2609.15225v1 Announce Type: new Abstract: Objective: To develop an intelligent framework, termed CUA-Net, for the automated classification of congenital uterine anomalies (CUA) without requiring