Knowledge catalogue
arXiv:2603.07926v3 Announce Type: replace-cross Abstract: Test-time adaptation (TTA) has been widely explored to prevent performance degradation when test data differ from the training distribution. H
arXiv:2511.17097v2 Announce Type: replace Abstract: Vision-Language Navigation requires agents to act coherently over long horizons by understanding not only local visual context but also how far they
arXiv:2604.11817v1 Announce Type: cross Abstract: Hybrid quantum-classical models offer a promising route for learning from complex data; however, their application to multi-band remote sensing imager
arXiv:2604.11993v1 Announce Type: new Abstract: Illumination using correlated photon sources has been established as an approach to allowing high-fidelity images to be reconstructed from noisy camera
arXiv:2510.05125v2 Announce Type: replace Abstract: While collaborative filtering delivers predictive accuracy and efficiency, and Large Language Models (LLMs) enable expressive and generalizable reas
arXiv:2601.11310v2 Announce Type: replace Abstract: Semantic ultra-high-resolution (UHR) image segmentation is essential in remote sensing applications such as aerial mapping and environmental monitor
arXiv:2604.11359v1 Announce Type: new Abstract: Accurate interpretation of electrocardiogram (ECG) remains challenging due to the scarcity of labeled data and the high cost of expert annotation. Self-
arXiv:2604.11400v1 Announce Type: cross Abstract: High-speed autonomous racing presents extreme perception challenges, including large relative velocities and substantial domain shifts from convention
arXiv:2512.20642v2 Announce Type: replace-cross Abstract: Particle image velocimetry (PIV) and related optical-flow methods are widely used to quantify fluid motion, but their development and evaluati
arXiv:2604.09645v1 Announce Type: cross Abstract: Medical conversations offer insights into clinical communication often absent from Electronic Health Records. However, developing reliable clinical Na
arXiv:2604.10748v1 Announce Type: cross Abstract: Generating multiple-choice questions (MCQs) with difficulty estimation remains challenging in automated MCQ-generation systems used in adaptive, AI-as
arXiv:2601.08209v3 Announce Type: replace Abstract: In domains such as materials science, biomedicine, and finance, high-stakes deployment of large language models (LLMs) requires injecting private, d
arXiv:2604.11788v1 Announce Type: new Abstract: High dynamic range (HDR) imagery offers a rich and faithful representation of scene radiance, but remains challenging for generative models due to its m
arXiv:2604.11444v1 Announce Type: new Abstract: Synthetic Aperture Radar (SAR) imagery generation is essential for deepening the study of scattering mechanisms, establishing trustworthy electromagneti
arXiv:2604.09670v1 Announce Type: cross Abstract: Intelligent systems must maintain and manipulate task-relevant information online to adapt to dynamic environments and changing goals. This capacity,
arXiv:2604.09942v1 Announce Type: cross Abstract: Object binding is a foundational process in visual cognition, during which low-level perceptual features are joined into object representations. Bindi
arXiv:2604.10971v1 Announce Type: cross Abstract: In the progress of industrial anomaly detection, general anomaly detection (GAD) is an emerging trend and also the ultimate goal. Unlike the conventio
arXiv:2505.23606v4 Announce Type: replace-cross Abstract: Unified generation models aim to handle diverse tasks across modalities -- such as text generation, image generation, and vision-language reas
arXiv:2604.10452v1 Announce Type: new Abstract: Olfaction lies at the intersection of chemical structure, neural encoding, and linguistic perception, yet existing representation methods fail to fully
arXiv:2506.01201v2 Announce Type: replace Abstract: David Marr's seminal theory of human perception stipulates that visual processing is a multi-stage process, prioritizing the derivation of boundary
arXiv:2604.07486v2 Announce Type: replace-cross Abstract: Large language models (LLMs) have emerged as a powerful tool for synthetic data generation. A particularly important use case is producing syn
arXiv:2604.09814v1 Announce Type: new Abstract: Medical image segmentation models built on Segment Anything Model (SAM) achieve strong performance on clean benchmarks, yet their reliability often degr
arXiv:2512.12982v2 Announce Type: replace Abstract: The pursuit of a universal AI-generated image (AIGI) detector often relies on aggregating data from numerous generators to improve generalization. H
arXiv:2604.10495v1 Announce Type: new Abstract: As Large Language Models (LLMs) are increasingly deployed in real-world applications, reliable uncertainty quantification (UQ) becomes critical for safe
arXiv:2604.08722v1 Announce Type: cross Abstract: Sport analysis is crucial for team performance since it provides actionable data that can inform coaching decisions, improve player performance, and e
arXiv:2604.08974v1 Announce Type: new Abstract: Uncertainty quantification is a set of techniques that measure confidence in language models. They can be used, for example, to detect hallucinations or
arXiv:2510.23636v3 Announce Type: replace-cross Abstract: Flight delay prediction has become a key focus in air traffic management (ATM), as delays reflect inefficiencies in the system. This paper pro
arXiv:2604.08719v1 Announce Type: cross Abstract: Recent years have seen remarkable progress in autonomous driving, yet generalization to long-tail and open-world scenarios remains a major bottleneck
arXiv:2604.08575v1 Announce Type: cross Abstract: Molecular generative models must jointly ensure validity, diversity, and property control, yet existing approaches typically trade off among these obj
arXiv:2512.07833v2 Announce Type: replace-cross Abstract: Humans do not just see attribute similarity -- we also see relational similarity. An apple is like a peach because both are reddish fruit, but
arXiv:2604.09034v1 Announce Type: new Abstract: The rapid evolution of Large Language Models (LLMs) has significantly impacted the field of natural language processing, but their growing complexity ra
arXiv:2604.08945v1 Announce Type: new Abstract: Accurate object geometry estimation is essential for many downstream tasks, including robotic manipulation and physical interaction. Although vision is
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arXiv:2604.08519v1 Announce Type: new Abstract: Large language models (LLMs) can struggle to memorize factual knowledge in their parameters, often leading to hallucinations and poor performance on kno
arXiv:2604.03317v2 Announce Type: replace Abstract: Previous studies have illustrated the potential of analysing gaze behaviours in collaborative learning to provide educationally meaningful informati
arXiv:2604.07273v2 Announce Type: replace Abstract: We present GenLCA, a diffusion-based generative model for generating and editing photorealistic full-body avatars from text and image inputs. The ge
arXiv:2604.07092v2 Announce Type: replace Abstract: In this work, we present LIANet (Location Is All You Need Network), a coordinate-based neural representation that models multi-temporal spaceborne E
arXiv:2604.08110v1 Announce Type: new Abstract: Training-free open-vocabulary semantic segmentation(TF-OVSS) has recently attracted attention for its ability to perform dense prediction by leveraging
arXiv:2604.08532v1 Announce Type: new Abstract: Large-scale multi-view reconstruction models have made remarkable progress, but most existing approaches still rely on fully supervised training with gr
arXiv:2601.23155v2 Announce Type: replace-cross Abstract: Information-based data selection for instruction tuning is compelling: maximizing the log-determinant of the Fisher information yields a monot
1/ today we're releasing muse spark, the first model from MSL. nine months ago we rebuilt our ai stack from scratch. new infrastructure, new architecture, new data pipelines. muse spark is the result
Great paper from NVIDIA sharing an open midtraining recipe for agentic coding. NVIDIA kept SFT identical and added one midtraining stage. SWE-bench Multilingual went from 55.8 to 62.8 on Nemotron 3.5
arXiv:2606.17090v2 Announce Type: replace-cross Abstract: ANEForge is a Python package that programs the Apple Neural Engine (ANE), the fixed-function neural accelerator on every recent Apple device,
arXiv:2610.20867v1 Announce Type: new Abstract: We present a general declarative framework for anticipatory reasoning about interactive motion in complex dynamic environments. Our focus is on (explain
arXiv:2610.22077v1 Announce Type: new Abstract: Weather prediction is undergoing an important shift, with data-driven AI models outperforming leading numerical weather prediction systems on average at
arXiv:2610.21459v1 Announce Type: cross Abstract: Unified multimodal models (UMMs) receive image-generation supervision that exposes them to visual information not fully documented in text. Can learni
arXiv:2610.22119v1 Announce Type: new Abstract: We propose Compliant GMT (C-GMT), a modular framework for full-body compliant responses in general motion tracking. As humanoid robots move into real wo
arXiv:2610.21190v1 Announce Type: new Abstract: Point cloud upsampling is essential for 3D applications but remains challenging due to sparse, under-constrained observations. Multi-view images can res
arXiv:2610.21681v1 Announce Type: new Abstract: Data strategy plays a central role in training large language models (LLMs). It governs the selection, weighting, and scheduling of training data, there
arXiv:2610.21672v1 Announce Type: cross Abstract: Diffusion language models generate text by reversing a classical diffusion process over token sequences. We show that their continuous-time forward an
arXiv:2610.21780v1 Announce Type: cross Abstract: We propose DINO-FIL, a transformer-based framework for pixel-level localization of generative image forgeries. The method leverages multi-layer repres
arXiv:2610.20904v1 Announce Type: cross Abstract: Egocentric human videos offer a scalable alternative to costly robot demonstra- tions, yet transferring their manipulation priors to robot control rem
arXiv:2610.22060v1 Announce Type: new Abstract: Discrete image generators learn the distribution of tokens produced by an image tokenizer. These token representations should be easy for generators to
arXiv:2610.21937v1 Announce Type: new Abstract: Vision--language pre-training has enabled substantial progress in image--text retrieval and zero-shot recognition by learning transferable cross-modal r
arXiv:2610.20636v1 Announce Type: cross Abstract: Sampling from continuous flow-based generators such as flow matching models requires numerical ODE or SDE integration, making inference cost depend on
arXiv:2610.21452v1 Announce Type: cross Abstract: Human face-to-face conversation requires coordinating speech, gestures and expressions across both speaking and listening. We present ELLSA 2, an end-
arXiv:2610.21779v1 Announce Type: new Abstract: Multi-modal semantic segmentation benefits from complementary sensors, but this benefit is fragile when some modalities are degraded or missing at test
arXiv:2610.21038v1 Announce Type: cross Abstract: Machine learning models for tabular prediction typically assume that training data are representative of the population on which they will be deployed
arXiv:2606.09366v2 Announce Type: replace Abstract: Large language models (LLMs) provide a powerful reasoning backbone for speech understanding, but integrating continuous acoustic signals into a pret