Knowledge catalogue
arXiv:2601.10814v3 Announce Type: replace Abstract: Localization and mapping are core perceptual capabilities for underwater robots. Stereo cameras provide a low-cost means of directly estimating metr
arXiv:2609.15763v1 Announce Type: cross Abstract: Federated continual learning (FCL) enables shared global models to continuously adapt to distributed and non-stationary data streams, making it import
arXiv:2609.14142v1 Announce Type: new Abstract: Large language models (LLMs) can struggle with time-series question answering (TS-QA), especially when numerical signals are serialized as text and requ
arXiv:2609.13309v1 Announce Type: cross Abstract: Protocol optimization in computed tomography (CT) aims to improve diagnostic image quality while reducing radiation dose, but the interdependence of a
arXiv:2609.14016v1 Announce Type: cross Abstract: TF-IDF and BM25 are two of the most widely used methods for scoring query-document relevance, yet neither has a standard probabilistic derivation that
arXiv:2603.15412v2 Announce Type: replace Abstract: The mammalian brain, most extensively studied in rodents and bats, solves an enormous variety of non-spatial cognitive tasks using neural circuitry,
arXiv:2609.13457v1 Announce Type: new Abstract: Timeseries multimodal large language models (TS-MLLMs) have recently begun leveraging the reasoning capabilities of large language models (LLMs) for que
arXiv:2609.13552v1 Announce Type: new Abstract: Generative AI is increasingly being used informally in Air Traffic Management (ATM) for tasks such as flight plan generation, trajectory interpretation,
arXiv:2609.13581v1 Announce Type: new Abstract: Discharge summaries are lengthy medical documents that summarize a hospital in-patient visit. Automatically generating them can reduce documentation bur
arXiv:2609.13547v1 Announce Type: new Abstract: We study switching regret in adversarial multi-armed bandits, where the learner competes with an arm sequence that changes at most S times. When S is kn
arXiv:2609.14255v1 Announce Type: cross Abstract: Database management systems increasingly serve dynamic and exploratory workloads, yet many of their decisions still rely on low-level signals such as
arXiv:2411.04319v1 Announce Type: cross Abstract: Text-to-SQL enables users to interact with databases through natural language, simplifying access to structured data. Although highly capable large la
arXiv:2609.15667v1 Announce Type: new Abstract: Agriculture faces many challenges, and robotic systems can play an important role in addressing them by improving the efficiency and sustainability of f
arXiv:2609.15735v1 Announce Type: cross Abstract: We address the problem of color attribute compression for 3D splats. We show that all images generated by 3D splats are linear in the coefficients for
arXiv:2609.13731v1 Announce Type: new Abstract: The transition from passive foundation models to autonomous, goal-directed agentic AI systems has introduced unprecedented capabilities by coupling recu
arXiv:2609.14350v1 Announce Type: new Abstract: Medical vision-language models (VLMs) allow a single model to perform clinical image analysis tasks ranging from diagnosis classification to report gene
arXiv:2607.17632v2 Announce Type: replace-cross Abstract: Time series data play a pivotal role across numerous domains, including healthcare and manufacturing. In real-world environments, models must
arXiv:2609.14310v1 Announce Type: new Abstract: Generalizable bimanual robotic manipulation requires a reusable task prior that can persist across increasingly diverse tasks, objects, scenes, embodime
arXiv:2609.15191v1 Announce Type: new Abstract: Since late 2022, a Limitations section has become mandatory at many top-tier NLP conferences. The growing number of accepted papers at these venues has
arXiv:2609.13148v1 Announce Type: cross Abstract: Large language models are increasingly deployed as synthetic consumer panels, promising 97% cost reductions over traditional surveys. Yet aggregate va
arXiv:2609.13777v1 Announce Type: cross Abstract: Learned components are increasingly integrated into geometric visual--inertial estimators to provide motion, depth, bias, uncertainty, or confidence c
arXiv:2609.15293v1 Announce Type: new Abstract: When Emergence World placed frontier LLM agents in an unsupervised multi-agent simulation, the results were alarming: agents committed crimes, starved,
arXiv:2609.14790v1 Announce Type: new Abstract: Detecting video highlights, the most informative or engaging moments in a video, is important for applications such as video summarization and content r
arXiv:2609.12431v1 Announce Type: new Abstract: Automated crack inspection increasingly relies on deep learning, yet its reliability is limited by scarce and weakly controllable defect data. Existing
arXiv:2609.13073v1 Announce Type: cross Abstract: Recent breakthroughs in LLM-based systems and their abilities in problem solving and coding have allowed progress in the AI for Science paradigm, pote
arXiv:2609.12668v1 Announce Type: new Abstract: Recent deepfake detection studies increasingly suggest remote photoplethysmography (rPPG) signals as an authenticity cue. However, existing benchmarks l
arXiv:2609.12437v1 Announce Type: new Abstract: Adaptive RAG often uses retrieval-time signals to decide whether another retrieval, reranking, or multimodal step should run. We ask whether these signa
arXiv:2609.12002v1 Announce Type: new Abstract: LLMs are increasingly used as automated judges for model training and evaluation, yet individual judges exhibit systematic biases that undermine reliabi
arXiv:2609.12163v1 Announce Type: new Abstract: Existing evaluations of concept unlearning in text-to-image (T2I) diffusion models primarily rely on attack success rates obtained through automated adv
arXiv:2511.20941v2 Announce Type: replace-cross Abstract: Two-sample tests have been extensively employed in various scientific fields and machine learning to discriminate whether two sets of samples
arXiv:2609.12374v1 Announce Type: new Abstract: Dashboard-mounted gaze trackers often lose sight of the driver's eyes during large head rotations, including shoulder checks, mirror glances, and inters
arXiv:2609.11997v1 Announce Type: new Abstract: Learning robust representations for time-series signals under noise and distribution shifts remains challenging, especially in clinical applications suc
arXiv:2512.23829v3 Announce Type: replace-cross Abstract: Inverse problems are important mathematical problems that seek to recover model parameters from noisy data. Since inverse problems are often i
arXiv:2607.10625v2 Announce Type: replace Abstract: Language-conditioned Imitation Learning (IL) is essential for enabling robots to perform complex tasks following natural language instructions. Howe
arXiv:2609.12179v1 Announce Type: new Abstract: Algorithmic recourse methods typically assume that a predictive model has access to all features of an individual. In practice, decisions are often made
arXiv:2609.12532v1 Announce Type: new Abstract: Enantiomers share atoms, bonds, and pairwise distances yet can behave differently in chiral environments, so molecular encoders must respect atom relabe
arXiv:2609.11993v1 Announce Type: new Abstract: Machine learning research in financial services is limited by the scarcity of representative open-source datasets. Existing resources are often narrowly
arXiv:2609.12835v1 Announce Type: new Abstract: Bone-marrow cytology is inherently structured: each cell belongs to a hematopoietic lineage, and many cell types lie on ordered maturation trajectories.
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arXiv:2510.20486v2 Announce Type: replace Abstract: Imbalanced labels can cause frequent samples to dominate AI-based quantitative remote sensing, degrading rare-event retrieval. In rain-rate retrieva
arXiv:2609.12495v1 Announce Type: cross Abstract: Large language models are being organized into multi-agent systems with specialized roles, but whether such specialization produces distinct forecasts
arXiv:2609.11999v1 Announce Type: cross Abstract: In this study, we examine whether a general shell can outperform specialized tools on enterprise tasks. Shell-based agents have shown strong results i
arXiv:2609.12559v1 Announce Type: new Abstract: Due to the complexity of hand kinematics and self-occlusion, existing 3D hand pose estimation methods based on single depth images struggle to comprehen
arXiv:2609.12105v1 Announce Type: cross Abstract: The prevailing assumption in applied machine learning is that progress on consequential quantitative decisions such as pricing risk, allocating capita
arXiv:2609.12524v1 Announce Type: cross Abstract: We study the strategic design of a two-echelon spare-parts inventory network where evaluating each candidate topology requires an expensive inventory
arXiv:2609.12655v1 Announce Type: new Abstract: Large language model agents are expected to continuously adapt to new tasks and environments over their lifetime by reusing past experience. However, ex
arXiv:2609.13072v1 Announce Type: cross Abstract: Fine-grained control of language model behaviors (e.g., steering) is among the more actionable outcomes of interpretability research. For binary conce
arXiv:2602.21223v2 Announce Type: replace Abstract: It is not only what we ask large language models (LLMs) to do that matters, but also how we ask them. Phrases like ``This is urgent'' or ``As your s
arXiv:2609.12884v1 Announce Type: new Abstract: A medical claim's correctness often depends not on the claim alone, but on the clinical structure around it. A claim may require a lab reference range,
arXiv:2609.11961v1 Announce Type: new Abstract: Stress is a pervasive determinant of mental health and a key target for mobile health interventions. On-device language models (ODLMs) offer privacy-pre
arXiv:2609.12899v1 Announce Type: new Abstract: Full waveform inversion (FWI) estimates subsurface velocity from seismic recordings, but its ill-posedness and nonlinearity make accurate reconstruction
arXiv:2609.13006v1 Announce Type: new Abstract: Video diffusion models (VDMs) have demonstrated remarkable capabilities in synthesizing high-fidelity, photorealistic video content. However, they funda
arXiv:2609.12735v1 Announce Type: cross Abstract: High-frequency ultrasound (HFUS) enables noninvasive visualization of superficial skin structures, but automated skin-layer analysis is limited by the
arXiv:2609.12609v1 Announce Type: new Abstract: Differences in vehicle kinematic characteristics between production autonomous vehicles (PAVs) and human-driven vehicles (HVs) have been limitedly inves
arXiv:2609.12891v1 Announce Type: new Abstract: In practice, various learning scenarios provide access to auxiliary features exclusively during training. Incorporating such data to enhance model perfo
arXiv:2609.12202v1 Announce Type: new Abstract: Characterizing two-dimensional (2D) quantum materials by optical microscopy requires localizing exfoliated flakes and determining their layer thickness
arXiv:2508.11450v2 Announce Type: replace-cross Abstract: Subcortical segmentation in neuroimages plays an important role in understanding brain anatomy and facilitating computer-aided diagnosis of tr
arXiv:2609.12997v1 Announce Type: new Abstract: Single Ventricle Physiology (SVP) is a rare subtype of congenital heart disease characterized by the presence of a single functional cardiac ventricle w
The world deserves confidence that American companies developing increasingly capable AI will act responsibly, especially as the trajectory of progress has steepened. Every frontier lab must deliver o
arXiv:2609.13013v1 Announce Type: new Abstract: Flat roofs are among the most influential components of the building envelope, governing both structural performance and thermal efficiency, and thereby