Knowledge catalogue
arXiv:2609.13927v1 Announce Type: new Abstract: Biological organisms minimize free energy by balancing two competing demands on their internal world model: it must be accurate enough to predict sensor
arXiv:2509.11252v3 Announce Type: replace-cross Abstract: LLMs have become the mainstream approaches to code generation. Existing LLMs mainly employ autoregressive generation, i.e. generating code tok
arXiv:2609.14913v1 Announce Type: new Abstract: Repository-level repair requires not only correct patches but also inspectable records that explain how issue requirements are translated into code chan
arXiv:2609.15209v1 Announce Type: cross Abstract: Automatic prompt optimization (APO) improves language-model programs by revising prompts from task feedback, yet it typically holds its training data
arXiv:2609.14539v1 Announce Type: new Abstract: This work proposes a model-based fault detection and diagnosis framework for underwater vehicles subject to actuator faults that explicitly accounts for
arXiv:2609.13315v1 Announce Type: cross Abstract: We investigate whether a Chern-Simons (CS) context reservoir is a viable computational substrate and whether evolving its gauge connection provides a
arXiv:2409.17685v3 Announce Type: replace Abstract: Hypomimia has drawn growing interest as a digital marker for screening Parkinson's disease (PD). However, developing reliable facial-expression-base
arXiv:2609.13262v1 Announce Type: new Abstract: 3D Gaussian Splatting achieves photorealistic reconstruction within training view distribution, yet it degrades on out-of-distribution novel views, exhi
arXiv:2609.14451v1 Announce Type: cross Abstract: Modern semi-supervised learning (SSL) couples pseudo-label generation and classifier training, using the classifier's own confidence to select the pse
arXiv:2609.14384v1 Announce Type: new Abstract: What must a neural system be capable of to implement language? Current research annotates stimuli with linguistic variables and tests which electrodes,
arXiv:2609.15015v1 Announce Type: new Abstract: Synthetic perturbations appear to offer inexpensive calibration data for LLM evaluators in biomedical ML, where expert review is scarce. Yet a planted m
arXiv:2609.13519v1 Announce Type: new Abstract: Molecular design is most effective when generation mirrors the edits chemists actually make: extending a scaffold, replacing a substituent, or decoratin
arXiv:2609.13617v1 Announce Type: new Abstract: We evaluate whether the improvements advertised for ChatGPT Images 2.5 translate into better performance on forgery tasks with predetermined answers. We
arXiv:2609.15219v1 Announce Type: new Abstract: Founders face two linked decisions: whether to pursue an idea before founding, and which operating actions and capital partners fit afterward. We presen
arXiv:2405.00065v4 Announce Type: replace-cross Abstract: This paper introduces the notion of upper-linearizable/quadratizable functions, a class that extends concavity and DR-submodularity in various
arXiv:2609.13260v1 Announce Type: cross Abstract: This paper proposes SpecAugment-Patch Merging, a simple yet effective method to accelerate Audio Spectrogram Transformer (AST) training. We first appl
arXiv:2609.15649v1 Announce Type: new Abstract: Compositional Zero Shot Learning aims to recognize unseen compositions by recombining learned primitives. Recent methods rely on vision language models
arXiv:2609.13206v1 Announce Type: cross Abstract: Marine ecosystems are increasingly impacted by climate change, necessitating tools to identify and predict spatial habitat information. To build such
arXiv:2609.13703v1 Announce Type: cross Abstract: In the best-arm identification problem, we are given n stochastic arms with unknown means and wish to identify the arm with the largest mean with prob
arXiv:2609.13282v1 Announce Type: new Abstract: Industrial anomaly localization has advanced rapidly with feature-based, reconstruction-based, and distillation-based methods. Most of these methods sco
arXiv:2511.09665v1 Announce Type: cross Abstract: Deep tabular modelling increasingly relies on in-context learning where, during inference, a model receives a set of (x,y) pairs as context and predic
arXiv:2609.13875v1 Announce Type: cross Abstract: We introduce cvxgenrust, an open-source tool for generating custom Rust code that solves families of parameterized convex optimization problems modele
arXiv:2609.14917v1 Announce Type: cross Abstract: We introduce document embedding geometry as a quantitative observable of conceptual reorganization and develop a counterfactual ablation framework for
arXiv:2609.13332v1 Announce Type: new Abstract: Automated landslide segmentation on Mars is one of the important tasks for understanding its surface processes, and all will aid in future space explora
arXiv:2609.14534v1 Announce Type: new Abstract: Predictive Process Monitoring (PPM) aims at predicting at runtime and as early as possible the future states of a process execution. Common tasks includ
arXiv:2603.13044v2 Announce Type: replace-cross Abstract: Medical image segmentation (MIS) is a fundamental component of computer-assisted diagnosis and clinical decision support. Over the past decade
arXiv:2609.13204v1 Announce Type: cross Abstract: Neural ordinary differential equations use numerical solvers inside the training loop. The solver determines the forward trajectory and also affects t
arXiv:2609.15483v1 Announce Type: new Abstract: Unsupervised multivariate time series anomaly detection methods typically identify anomalies through forecasting, reconstruction, or representation disc
arXiv:2410.15359v2 Announce Type: replace Abstract: Multimodal Foundation Models represent a significant leap in artificial intelligence. Among them, Large Vision-Language Models (LVLMs) serve as the
arXiv:2609.13947v1 Announce Type: cross Abstract: In-sensor computing reduces the cost of transmitting high-resolution image data by performing early-stage processing near the sensor. However, the log
arXiv:2609.14425v1 Announce Type: cross Abstract: Generative artificial intelligence raises a central question for scientific training and organization. Is research shifting from deep specialization t
arXiv:2609.14735v1 Announce Type: cross Abstract: Deep Learning (DL)-based channel estimation has shown high accuracy and low latency in terrestrial 5G NR, but Low Earth Orbit (LEO) Non-Terrestrial Ne
arXiv:2609.13306v1 Announce Type: new Abstract: Real-time aerial small object detection is an important visual signal and image processing problem, requiring a detector to preserve fine-grained locali
arXiv:2609.15001v1 Announce Type: new Abstract: Density-based topology optimization is typically structured as a nested sequence of material updates, structural analyses, and sensitivity assessments.
arXiv:2305.17327v4 Announce Type: replace Abstract: Imperfect Information Games (IIGs) are used to model games under uncertainty or lack complete information. Counterfactual Regret Minimization (CFR)
arXiv:2603.23803v2 Announce Type: replace-cross Abstract: In this paper, we present DROP, high-Density Relocation-free sequential OPerations in automated valet parking. DROP addresses the challenges i
arXiv:2609.14770v1 Announce Type: cross Abstract: Generalisations are common in scientific communication, even though they are semantically ambiguous. An automated method is needed to identify and cat
arXiv:2603.09232v2 Announce Type: replace-cross Abstract: While Contrastive Decoding (CD) has been proposed to enhance Large Audio Language Models (LALMs), it has not been evaluated at scale, and the
arXiv:2609.13254v1 Announce Type: cross Abstract: Bistable images such as the duck-rabbit are classic stimuli in which one image supports multiple mutually incompatible interpretations, typically repo
arXiv:2609.15504v1 Announce Type: cross Abstract: Orthrus is a hybrid autoregressive-diffusion architecture that accelerates autoregressive language-model inference by generating multiple tokens in pa
arXiv:2609.13747v1 Announce Type: new Abstract: Large language models solve hard problems through intermediate computations across multi-step reasoning. Traditional chain-of-thought encodes these comp
arXiv:2609.15640v1 Announce Type: cross Abstract: Long-text image--text congruence scoring is increasingly important for vision-language systems that must evaluate whether detailed textual description
arXiv:2503.02908v2 Announce Type: replace-cross Abstract: Hyperspectral imaging is a powerful bioimaging tool which can uncover novel insights, thanks to its sensitivity to the intrinsic properties of
arXiv:2601.19847v3 Announce Type: replace Abstract: Despite the strong reasoning capabilities of recent large language models (LLMs), achieving reliable performance on challenging tasks often requires
arXiv:2609.15145v1 Announce Type: new Abstract: The reasoning ability of large language models (LLMs) is a critical factor for practical LLM-based applications. To investigate the current reasoning ca
arXiv:2609.15257v1 Announce Type: cross Abstract: We analyze a stochastic algorithm with Halpern anchoring for constrained convex-concave problems and monotone variational inequalities. This algorithm
arXiv:2609.15284v1 Announce Type: new Abstract: Missing values are ubiquitous in heterogeneous data mining, where numerical, categorical, and binary variables often coexist. Many imputation methods, e
arXiv:2609.15833v1 Announce Type: new Abstract: Cultural heritage documentation increasingly relies on image-based 3D surface reconstruction, with photogrammetry software making such workflows accessi
arXiv:2609.14870v1 Announce Type: cross Abstract: Counting equivalent pairs is a common way to report transformation-audit coverage, but it can substantially overstate the constraints imposed by an au
arXiv:2609.14638v1 Announce Type: cross Abstract: This paper is an encore submission of our 2026 journal article 'Expertise and Information Seeking in the Age of Generative AI: New Procedures, New Pro
arXiv:2509.23043v2 Announce Type: replace-cross Abstract: Generative models have been extensively used to accelerate MCMC mixing for sampling and optimization, but their effective integration with sta
arXiv:2609.15713v1 Announce Type: new Abstract: Recent approaches to 30-day hospital readmission prediction rely on pre-trained language models applied to discharge summaries. Although these methods a
arXiv:2502.21279v2 Announce Type: replace-cross Abstract: Deep residual networks (ResNets) have demonstrated outstanding success in computer vision tasks, attributed to their ability to maintain gradi
arXiv:2609.13437v1 Announce Type: new Abstract: Scientific research is a continuous process that emphasizes inheritance. Methods developed by predecessors are often expanded upon by new researchers to
arXiv:2609.13281v1 Announce Type: cross Abstract: Ocean-bottom seismometers (OBS), originally deployed for geophysical research, continuously record low-frequency sound for months to years across broa
arXiv:2609.13701v1 Announce Type: cross Abstract: Accurate job runtime prediction can improve scheduling-aware resource management in grid and distributed computing environments, but prediction models
arXiv:2609.14990v1 Announce Type: cross Abstract: A finite-difference bowed-string model with implicitly resolved Stribeck friction is presented, with a regime diagnostic, the Schelleng bow-force limi
arXiv:2609.15268v1 Announce Type: new Abstract: We revisit Valiant's algorithm (Commun. ACM'84) for learning n-variable CNF formulas with clause size k and variable degree d from i.i.d. uniform random
arXiv:2609.14316v1 Announce Type: new Abstract: Advances in image generation have made synthetic images increasingly difficult to distinguish from real photographs, raising concerns about the trustwor
arXiv:2602.08370v2 Announce Type: replace-cross Abstract: Realizing versatile and human-like performance in high-demand sports like badminton remains a formidable challenge for humanoid robotics. Unli