Knowledge catalogue
arXiv:2609.28274v1 Announce Type: new Abstract: The final safeguard against rogue AI behavior is the human ability to shut systems down. It has been theorized that when an AI is instructed to perform
arXiv:2609.26820v1 Announce Type: cross Abstract: Physiological time series such as electrocardiograms (ECG) and electroencephalograms (EEG) exhibit complex temporal structure, substantial acquisition
arXiv:2609.26836v1 Announce Type: new Abstract: Agentic AI systems are increasingly adopting automated pipelines that integrate multiple tools. While prior research and benchmarks have studied about t
arXiv:2606.13295v3 Announce Type: replace-cross Abstract: In the era of Explainable Artificial Intelligence, there is a renewed focus on single trees for their ease of interpretation. This paper intro
arXiv:2609.27980v1 Announce Type: new Abstract: Pruning large pre-trained transformer-based ASR models such as OpenAI's Whisper has seen great adoption, as pruning the decoder led to significant end-t
arXiv:2609.27717v1 Announce Type: new Abstract: Human-written agent skills encode rich workflows for real-world problem solving, but are typically used as external inference-time instructions rather t
arXiv:2609.28064v1 Announce Type: new Abstract: Driving world-action models improve planning by coupling multimodal reasoning with future prediction, but their growing inference cost increasingly conf
arXiv:2609.26907v1 Announce Type: cross Abstract: Memes often derive their harmful, hateful, or sarcastic meaning from small but decisive visual, textual, or cross-modal cues. Existing multimodal clas
arXiv:2505.05491v2 Announce Type: replace-cross Abstract: Traffic sign detection is a challenging visual signal processing task for advanced driver assistance, where small objects, scale variation, an
arXiv:2604.00241v2 Announce Type: replace-cross Abstract: Algorithms for the Multi-Armed Bandit (MAB) problem play a central role in sequential decision-making and have been extensively explored both
arXiv:2609.28013v1 Announce Type: cross Abstract: Machine-learned interatomic potentials (MLIPs) for solid-liquid interfaces in advanced materials applications, e.g., electrochemistry, catalysis and c
arXiv:2609.27290v1 Announce Type: new Abstract: Short-horizon forecasts of atmospheric temperature are needed to support climate-aware digital-twin systems, but such forecasts must be produced where t
arXiv:2609.27340v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used as natural-language interfaces for robotic systems, yet their integration with Robot Operating System
arXiv:2609.27904v1 Announce Type: new Abstract: As information technology advances, digital content has become widely adopted across diverse fields such as news broadcasting, entertainment, commerce,
arXiv:2609.26835v1 Announce Type: cross Abstract: COBOL remains widely deployed, yet representative corpora reflecting real production code are rarely available, limiting rigorous benchmarking of mode
arXiv:2609.26989v1 Announce Type: new Abstract: Hexapod robots can achieve static stability with fewer actuated joints than bipeds or quadrupeds, yet many platforms still use 3-DOF legs, increasing we
arXiv:2609.27917v1 Announce Type: cross Abstract: Neural combinatorial optimization solvers generate many candidate solutions per instance and report the best one found, using the same sample budget f
arXiv:2609.27287v1 Announce Type: new Abstract: Real-time payment fraud detection is a non-stationary streaming prediction problem: adversaries adapt before supervised labels mature, and localized bur
arXiv:2609.26854v1 Announce Type: cross Abstract: Sound Scene Generation is about the automatic synthesis of artificial sound scenes. We introduce SsgCaps, a publicly available dataset of human-engine
arXiv:2609.27332v1 Announce Type: new Abstract: Long horizon agents accumulate growing interaction histories that increase context and inference costs. We find that geometric redundancy alone is an in
arXiv:2609.27441v1 Announce Type: new Abstract: Achieving stable long-term neural decoding in invasive brain-machine interfaces (BMIs) remains challenging due to variations in recorded neural populati
arXiv:2606.18305v2 Announce Type: replace-cross Abstract: Operator learning is an emerging field at the intersection of machine learning and scientific computing. By learning mappings between function
arXiv:2609.27606v1 Announce Type: new Abstract: We introduce State-Grounded Conditioning (SGC), a design principle for user-facing LLM agents that must condition on live user state (game state, sessio
arXiv:2609.27298v1 Announce Type: new Abstract: Long-horizon agents continuously accumulate interaction history during task execution, yet the importance of past interactions changes as the agent stat
arXiv:2410.11113v4 Announce Type: replace-cross Abstract: This paper develops theory for deep neural network (DNN) estimators under dependent data. To provide theory applicable to a variety of DNN-bas
arXiv:2609.27238v1 Announce Type: new Abstract: Oriented ship detection in very high resolution (VHR) remote sensing imagery remains challenging due to elongated hull geometry and dense target distrib
arXiv:2609.28470v1 Announce Type: new Abstract: Artificial intelligence offers an unprecedented opportunity to augment human capabilities, yet progress at the frontier has focused primarily on advanci
arXiv:2609.27131v1 Announce Type: new Abstract: Single-image super-resolution of Sun's photospheric magnetograms enables consistent analysis across heterogeneous space-based instruments and supports l
arXiv:2609.28208v1 Announce Type: new Abstract: Tabular foundation models face a feature-side scaling dilemma: full-width pairwise mixing grows quadratically with the number of columns, whereas featur
arXiv:2609.27227v1 Announce Type: new Abstract: Objective assessment of robotic surgery uses instrument kinematics, which must be reconstructed when only video is available. We introduce a kinematic r
arXiv:2609.27696v1 Announce Type: new Abstract: The SYNTAX score is an established tool for assessing coronary artery disease and guiding revascularization treatment decisions. However, its manual est
arXiv:2409.13568v3 Announce Type: replace Abstract: Accurate delineation of agricultural field boundaries is essential for effective crop monitoring and resource management. However, competing methodo
arXiv:2609.27221v1 Announce Type: new Abstract: This paper studies multivariate conformal prediction (CP), a distribution-free uncertainty quantification framework with finite-sample coverage guarante
arXiv:2609.28296v1 Announce Type: new Abstract: While Vision-and-Language Navigation (VLN) has demonstrated remarkable success, the prevailing single-turn paradigm exposes a fundamental vulnerability:
arXiv:2609.28314v1 Announce Type: new Abstract: Human teleoperators spend substantial time demonstrating behaviors that robots can already perform autonomously, limiting the scalability of data collec
arXiv:2609.27988v1 Announce Type: new Abstract: Methods operating on Vision Transformer (ViT) feature spaces typically rely on Euclidean distance or cosine similarity. This assumes that every directio
arXiv:2609.27780v1 Announce Type: cross Abstract: Vision-language robot manipulation policies can follow semantic instructions, but adapting them to a new procedure from only a few demonstrations rema
arXiv:2609.27296v1 Announce Type: cross Abstract: Validating Autonomous Driving Systems (ADS) in simulation requires testing architectures that can discover rare, safety-critical failures while genera
arXiv:2609.28077v1 Announce Type: new Abstract: Steel surface defect detection is critical for automated industrial quality control but remains challenging due to subtle inter-class texture difference
arXiv:2609.27149v1 Announce Type: new Abstract: Remote sensing change detection requires both global reasoning across bitemporal images and precise localization of changed regions. However, dense atte
arXiv:2609.28048v1 Announce Type: cross Abstract: Modern information retrieval (IR) systems rarely represent time, yet many information needs depend on it: in clinical, journalistic, and legal search,
arXiv:2609.28029v1 Announce Type: cross Abstract: The key-value (KV) cache of autoregressive transformers can be viewed as a fourth-order tensor spanning attention heads, tokens, features, and grouped
arXiv:2609.26823v1 Announce Type: cross Abstract: Post-training quantization of speech language models is often summarized with text-output scores and nominal bit widths. Those numbers alone do not es
arXiv:2609.27558v1 Announce Type: new Abstract: Studying syntactic patterns in naturally occurring language requires a large parsed corpus, but manual annotation is costly and difficult to scale. Thai
arXiv:2609.27588v1 Announce Type: cross Abstract: Existing machine learning (ML) scaling laws relate predictive loss to compute, model parameters, and data. However, as models are increasingly deploye
arXiv:2606.19329v2 Announce Type: replace-cross Abstract: We present a framework to cross-match sources from the Chandra Source Catalog (CSC v2.1) with optical sources from Gaia Data Release 3. Unlike
arXiv:2609.26940v1 Announce Type: cross Abstract: Biological sensory neurons have selective receptive fields organized along meaningful stimulus coordinates, such as frequency, motion direction, or re
arXiv:2609.26811v1 Announce Type: new Abstract: Local learning trains each layer with its own auxiliary loss and no global backward pass, which makes layer updates structurally parallel. Two problems
arXiv:2609.27070v1 Announce Type: cross Abstract: Modern robot imitation learning increasingly relies on generative policies based on diffusion or flow-matching models, which generate actions by trans
arXiv:2609.27059v1 Announce Type: new Abstract: We introduce the Illinois Social Attitudes Aggregate Corpus (ISAAC), an open, modular, and accessible corpus of 527 million+ English-language Reddit pos
arXiv:2609.27155v1 Announce Type: cross Abstract: With recent advancements in large language models (LLMs) and LLM-based agents, these agents are becoming increasingly autonomous and gaining broader a
arXiv:2609.27158v1 Announce Type: cross Abstract: To make claims about representations that generalize beyond a particular trained model, we need to specify when two representations should count as eq
arXiv:2609.28466v1 Announce Type: new Abstract: Advances in generative models have improved video fidelity, enabling long-horizon generation, interactive world modeling, and evolving visual environmen
arXiv:2609.27669v1 Announce Type: cross Abstract: Small language models (SLMs) are increasingly paired with knowledge graphs (KGs), yet end-to-end KG question answering conflates graph access, search,
arXiv:2609.27953v1 Announce Type: cross Abstract: Some LLM-based recommendation rerankers are evaluated under an oracle protocol that guarantees the ground-truth item is present in the scored set, eit
arXiv:2609.27250v1 Announce Type: cross Abstract: The Schrodinger bridge owes its computational power to a single structural fact: by Girsanov's theorem the controlled problem is a Kullback--Leibler (
arXiv:2609.28424v1 Announce Type: new Abstract: Catalog skin recolouring has to change pigment and leave shading alone. The classical Reinhard map does not make that split: it rescales lightness by th
arXiv:2609.25804v2 Announce Type: replace Abstract: LLM agents increasingly work on long-horizon tasks, and the decisions they make along the way, such as which hypothesis to test or which implementat
arXiv:2609.27765v1 Announce Type: cross Abstract: In safe hypothesis testing with test supermartingales, Ville's inequality provides anytime-valid type-I error guarantees for every significance level
arXiv:2609.27853v1 Announce Type: cross Abstract: A normal--inverse-gamma (NIG) latent hierarchy has four parameters, but its induced latent law does not identify all four. For sigma^2simInvGamma(alph