Knowledge catalogue
arXiv:2503.04500v3 Announce Type: replace-cross Abstract: Video understanding has largely relied on deep spatiotemporal architectures, including 3D convolutional networks and optical flow (OF) based m
arXiv:2608.20083v1 Announce Type: cross Abstract: Question Answering over Temporal Knowledge Graphs (TKGQA) requires reasoning over time-sensitive facts, yet existing embedding-based methods struggle
arXiv:2608.20117v1 Announce Type: new Abstract: The emergence of large-scale Weather and Climate (W&C) datasets offers new opportunities for modeling extreme Earth events (ExEE) and their impacts usin
arXiv:2608.19723v1 Announce Type: cross Abstract: Streaming video understanding requires models to causally update state as video arrives and organize growing history into semantic units that can evol
arXiv:2505.13064v4 Announce Type: replace-cross Abstract: Multi-body mechanical systems have rich internal dynamics, whose solutions can be exploited as energy-efficient control targets. Yet, solution
arXiv:2608.20024v1 Announce Type: new Abstract: District heating energy hubs require reliable heat load forecasts for efficient operational scheduling. Conventional forecasting workflows train system-
T-Rex: Tactile-Reactive Dexterous Manipulation Website: https://tactile-reactive-dexterous.github.io/ Open dataset: https://huggingface.co/datasets/zekaiwang/trex_dataset This work is led by @Dantong_
arXiv:2608.19637v1 Announce Type: new Abstract: Text editing in product posters entails inserting new text or replacing existing text while preserving product appearance, background content, and globa
arXiv:2608.19593v1 Announce Type: new Abstract: A task-effective proposal is not yet a justified physical action. In networked Physical AI, a proposal may be understood while valid, timely, proposal-b
arXiv:2511.20973v2 Announce Type: replace-cross Abstract: Large Audio Language Models (LALMs) deliver strong performance across speech and audio tasks, but their audio encoders generate high-rate toke
arXiv:2511.03618v2 Announce Type: replace Abstract: In this paper, we formalize the almost sure convergence of Q-learning and linear temporal difference (TD) learning with Markovian samples using the
arXiv:2608.19210v1 Announce Type: cross Abstract: This paper focuses on the implementation of a novel supervised Machine Learning model for estimating helicopter weight during takeoff, utilizing exten
arXiv:2608.20284v1 Announce Type: new Abstract: Reliable surgical planning requires models to anticipate not only how instruments will move, but also how the operative visual state will evolve togethe
arXiv:2608.20255v1 Announce Type: cross Abstract: This paper develops a general transfer learning framework for nonparametric regression with data consisting of multiple groups. Under the assumption t
arXiv:2608.19200v1 Announce Type: cross Abstract: Text summarization refers to the task of condensing a document into a shorter version while preserving its key information. Automatic text summarizati
arXiv:2608.19234v1 Announce Type: new Abstract: Decision-making in complex systems often involves dealing with imprecise or uncertain information, frequently represented using fuzzy sets, particularly
arXiv:2608.19351v1 Announce Type: new Abstract: Robustness verification of neural networks is increasingly important, due to their use in many critical domains. In certain scenarios, proof sharing has
arXiv:2608.19894v1 Announce Type: new Abstract: Multi-view computer vision pipelines typically rely on accurate sparse keypoints and robust descriptors. While incorporating line features has shown cle
arXiv:2608.19801v1 Announce Type: new Abstract: Financial anomaly detection often relies on large unlabeled transaction logs, where anomalous samples may already be present during training. Such train
arXiv:2608.20069v1 Announce Type: new Abstract: While generalist VLMs are expensive to train, creating domain experts is widely assumed to require fine-tuning increasingly large foundation models. We
arXiv:2608.19583v1 Announce Type: cross Abstract: Recent studies suggest that video generation models can exhibit certain forms of zero-shot visual reasoning through generated frames. Yet reliable eva
arXiv:2608.19480v1 Announce Type: new Abstract: Human pose estimation has advanced significantly due to the development of deep learning models, increased data availability, and improved computing res
arXiv:2608.20043v1 Announce Type: cross Abstract: We study bilateral teleoperation between nonlinear, multi-DOF robotic manipulators in the presence of constant communication delays. Unlike classical
arXiv:2510.25960v2 Announce Type: replace-cross Abstract: In this paper, we present a framework that uses acoustic side-channel analysis (ASCA) to monitor and verify whether a robot correctly executes
When the biotech company Insilico Medicine used its computer models to propose a promising drug for pulmonary fibrosis, it enthusiastically claimed in a press release that the molecule had been “disco
arXiv:2608.19644v1 Announce Type: new Abstract: Diffusion Transformers (DiTs) incur high memory traffic and energy costs because sampling repeatedly evaluates large denoisers dominated by linear opera
arXiv:2608.19812v1 Announce Type: new Abstract: To prevent the adoption of aesthetically polished but pedagogically flawed AI content, we study a video authoring pipeline featuring two layers of struc
arXiv:2608.19903v1 Announce Type: cross Abstract: In fixed-confidence best-arm identification, proofs often use a union bound across the competing arms. From a multiple-testing point of view this can
Apple derives a repetition-aware mixture scaling law showing scarce target data can be reused ~15–20× when mixed with generic corpora.
arXiv:2603.21064v3 Announce Type: replace Abstract: Pose-free feed-forward 3D Gaussian Splatting (3DGS) has opened a new frontier for rapid 3D modeling, enabling high-quality Gaussian representations
arXiv:2608.18316v1 Announce Type: new Abstract: Structural Magnetic Resonance Imaging (MRI) is widely used in neuroimaging research and clinical practice, but structural MRI volumes may retain facial
arXiv:2608.18813v1 Announce Type: cross Abstract: In the last years, a number of proofs of the fact that O_2 is a multiple context-free grammar (MCFG) were given. Such results can be exploited in the
arXiv:2608.18188v1 Announce Type: cross Abstract: Autism spectrum disorder (ASD) is a developmental disability characterized by challenges in social interaction and communication. As the causes of ASD
arXiv:2608.18364v1 Announce Type: new Abstract: Pneumatic artificial muscles have provided new opportunities to develop upper-extremity soft exosuits for reha- bilitation, augmentation, and assisted d
arXiv:2608.18402v1 Announce Type: cross Abstract: We study finite-sample linear regression in the presence of varied and unknown label noise, focusing on the heteroskedastic and adaptive linear regres
arXiv:2608.18230v1 Announce Type: new Abstract: Looped language models improve reasoning and knowledge manipulation by applying shared computation repeatedly. Existing systems usually repeat an entire
arXiv:2608.18946v1 Announce Type: cross Abstract: Clifford circuits play a foundational role in quantum computing, particularly due to their importance in quantum error correction and fault-tolerant l
arXiv:2608.18507v1 Announce Type: new Abstract: Continuum arm aerial manipulation systems leverage soft-manipulator compliance and dexterity for tasks in confined or hazardous environments, but propel
arXiv:2608.18689v1 Announce Type: cross Abstract: We present Aslema, our system for NADI 2026 Shared Task 5, which consists of two subtasks: intent recognition and slot filling. We evaluate four omni
arXiv:2407.05788v2 Announce Type: replace-cross Abstract: Bayesian optimization (BO) is an efficient framework for optimization of black-box objectives when function evaluations are costly and gradien
arXiv:2608.18095v1 Announce Type: cross Abstract: Recent advances in deep learning have significantly enhanced the capabilities of Natural Language Processing (NLP) and Vision-Language Models (VLMs).
arXiv:2608.18454v1 Announce Type: new Abstract: Robotic assembly layout planning must determine the assembly site and the initial pose of each part while ensuring collision-free execution of a prescri
Banger paper on harness continual learning. (bookmark it) If you already are allowing your agents to rewrite their own prompts, skills, or memory files, this one is worth your time. (bookmark it) Cont
arXiv:2608.18101v1 Announce Type: new Abstract: Longitudinal text streams exhibit topic birth and death, but also discrete structural reorganizations in which themes split into subtopics or merge into
arXiv:2608.18193v1 Announce Type: cross Abstract: Distribution-free risk control adds organ-specific recall guarantees to frozen segmentation. We calibrate per-organ thresholds for an AMOS-trained nnU
arXiv:2608.19144v1 Announce Type: new Abstract: Continuous-time generative models are often built from endpoint-conditioned bridges, but generation requires a different object: a non-anticipative Mark
arXiv:2608.18480v1 Announce Type: cross Abstract: Digital twins (DTs) increasingly leverage artificial intelligence (AI) and machine learning (ML) pipelines, both to build real-time DTs from high-fide
arXiv:2606.21654v2 Announce Type: replace Abstract: Computer use agents are evaluated almost exclusively on atomic desktop tasks, but realistic desktop work requires sustaining state across multiple o
arXiv:2608.18191v1 Announce Type: new Abstract: Bats are key indicators of ecosystem health and are protected throughout Europe, making reliable population monitoring a conservation priority. Their cr
arXiv:2608.19133v1 Announce Type: new Abstract: We present a novel application of embedding-based dynamic topic modeling techniques to detect and quantify topic drift at the comment level in a massive
arXiv:2608.18413v1 Announce Type: new Abstract: 3D Gaussian Splatting enables efficient novel view synthesis, but accurate mesh reconstruction remains difficult in weakly observed and occluded regions
arXiv:2608.18911v1 Announce Type: new Abstract: We introduce the CDSP (context-conditional deliberation signal pipeline), converting an investment committee's meeting transcripts into structured predi
arXiv:2608.18634v1 Announce Type: new Abstract: Federated Active Learning (FAL) addresses the dual challenges of data privacy and label scarcity, where the absence of a global data view introduces add
arXiv:2307.12896v5 Announce Type: replace Abstract: The article introduces corrections to Zipf's and Heaps' laws based on systematic models of the proportion of hapaxes, i.e., words that occur once. T
arXiv:2608.18479v1 Announce Type: new Abstract: Semantic segmentation of aerial point cloud is trapped in a generalization crisis under distinct domain shifts. While test-time adaptation offers a priv
arXiv:2608.19032v1 Announce Type: cross Abstract: Visual Counterfactual Explanations (VCEs) aim to explain image classifiers by generating minimally edited and realistic versions of an input image tha
arXiv:2608.18515v1 Announce Type: new Abstract: Transvaginal ultrasound (TVUS) and magnetic resonance imaging (MRI) provide complementary information for endometriosis image analysis, yet existing stu
arXiv:2506.00244v2 Announce Type: replace Abstract: Noisy labelled datasets are generally inexpensive compared to clean labelled datasets, and the same is true for graph data. In this paper, we propos
arXiv:2608.18610v1 Announce Type: cross Abstract: Dense text embeddings are widely used in data mining, retrieval, and downstream machine learning systems due to their compact and semantically rich re
arXiv:2608.18470v1 Announce Type: new Abstract: Existing visual navigation models often aim to develop foundation models that can generalize robot navigation across diverse platforms. However, many of