Knowledge catalogue
arXiv:2604.12762v1 Announce Type: cross Abstract: We introduce ARGOS, the first benchmark and framework that reformulates multi-camera person search as an interactive reasoning problem requiring an ag
arXiv:2509.25749v2 Announce Type: cross Abstract: Virtual try-on (VITON) aims to generate realistic images of a person wearing a target garment, requiring precise garment alignment in try-on regions a
arXiv:2604.12251v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) delivers high-fidelity real-time rendering but suffers from geometric and photometric degradations under sparse-view constr
arXiv:2604.12857v1 Announce Type: new Abstract: Autonomous vehicles (AVs) are now operating on public roads, which makes their testing and validation more critical than ever. Simulation offers a safe
arXiv:2509.25843v2 Announce Type: replace Abstract: Large language models (LLMs), despite being safety-aligned, exhibit brittle refusal behaviors that can be circumvented by simple linguistic changes.
arXiv:2510.01186v2 Announce Type: replace Abstract: While existing video editing methods excel with single subjects, they struggle in dense, multi-subject scenes, frequently suffering from attention d
arXiv:2604.12274v1 Announce Type: new Abstract: A class of planar bipedal robots with unique mechanical properties has been proposed, where all links are balanced around the hip joint, preventing natu
arXiv:2604.12480v1 Announce Type: cross Abstract: In Gaussian model-based multichannel audio source separation, the likelihood of observed mixtures of source signals is parametrized by source spectral
arXiv:2507.11081v3 Announce Type: replace-cross Abstract: Ground penetrating radar (GPR) has become a rapid and non-destructive solution for road subsurface distress (RSD) detection. However, recogniz
arXiv:2604.11945v1 Announce Type: cross Abstract: High-fidelity numerical simulation of subsurface flow is computationally intensive, especially for many-query tasks such as uncertainty quantification
arXiv:2604.12221v1 Announce Type: new Abstract: Gait recognition, as a reliable biometric technology, has seen rapid development in recent years while it faces significant challenges caused by diverse
arXiv:2604.12005v1 Announce Type: cross Abstract: Bayesian optimization (BO) has for sequential optimization of expensive black-box functions demonstrated practicality and effectiveness in many real-w
arXiv:2602.18899v3 Announce Type: replace-cross Abstract: Self-supervised speech models (S3Ms) are known to encode rich phonetic information, yet how this information is structured remains underexplor
arXiv:2604.12898v1 Announce Type: new Abstract: Large Language Model-based Hyper Heuristic (LHH) has recently emerged as an efficient way for automatic heuristic design. However, most existing LHHs ju
arXiv:2604.12033v1 Announce Type: cross Abstract: Large Vision-Language Models (LVLMs) increasingly rely on retrieval to answer knowledge-intensive multimodal questions. Existing benchmarks overlook c
arXiv:2510.00919v3 Announce Type: replace-cross Abstract: Retrieval-augmented generation (RAG) with foundation models has achieved strong performance across diverse tasks, but their capacity for exper
arXiv:2604.12138v1 Announce Type: new Abstract: RAG systems have transformed how LLMs access external knowledge, but we find that current implementations exhibit a bias toward factual, objective conte
arXiv:2604.12196v1 Announce Type: new Abstract: Large language models (LLMs) frequently generate multiple candidate responses for a given prompt, yet selecting the most reliable one remains challengin
arXiv:2604.12379v1 Announce Type: cross Abstract: Large language models (LLMs) increasingly rely on explicit reasoning to solve coding tasks, yet evaluating the quality of this reasoning remains chall
arXiv:2604.12119v1 Announce Type: new Abstract: Large vision-language models (VLMs) often rely on familiar semantic priors, but existing evaluations do not cleanly separate perception failures from ru
arXiv:2604.12210v1 Announce Type: new Abstract: Simulating Standardized Patients with cognitive impairment offers a scalable and ethical solution for clinical training. However, existing methods rely
arXiv:2603.08819v3 Announce Type: replace-cross Abstract: Retrieval-augmented generation (RAG) systems combine document retrieval with a generative model to address complex information seeking tasks l
arXiv:2604.12191v1 Announce Type: new Abstract: Current evaluations of large language models aggregate performance across diverse tasks into single scores. This obscures fine-grained ability variation
arXiv:2604.12471v1 Announce Type: cross Abstract: Scientific novelty drives advances at the research frontier, yet it is also associated with heightened uncertainty and potential resistance from incum
arXiv:2604.11839v1 Announce Type: cross Abstract: Autonomous AI agents built on open-source runtimes such as OpenClaw expose every available tool to every session by default, regardless of the task. A
arXiv:2604.12506v1 Announce Type: new Abstract: Recent Audio Large Language Models (AudioLLMs) exhibit a striking performance inversion: while excelling at complex reasoning tasks, they consistently u
arXiv:2604.12304v1 Announce Type: new Abstract: Accurate short-term residential energy consumption forecasting at sub-hourly resolution is critical for smart grid management, demand response programme
arXiv:2604.12686v1 Announce Type: cross Abstract: Recent advances in deep learning underscore the need for systems that can not only acquire new knowledge through Continual Learning (CL) but also remo
arXiv:2604.13013v1 Announce Type: new Abstract: This paper tackles the Electric Capacitated Vehicle Routing Problem (E-CVRP) through a bilevel optimization framework that handles routing and charging
arXiv:2604.11861v1 Announce Type: new Abstract: Accurate and continuous localization of Autonomous Underwater Vehicles (AUVs) in GPS-denied environments is a persistent challenge in marine robotics. I
arXiv:2511.22364v2 Announce Type: replace-cross Abstract: Open-vocabulary mobile manipulation (OVMM) requires robots to follow language instructions, navigate, and manipulate while updating their worl
arXiv:2604.11981v1 Announce Type: new Abstract: Bipeds have demonstrated high agility and mobility in unstructured environments such as sand. The yielding of such granular media brings significant sin
arXiv:2604.12325v1 Announce Type: cross Abstract: We consider the problem of offline black-box optimization, where the goal is to discover optimal designs (e.g., molecules or materials) from past expe
arXiv:2603.27552v2 Announce Type: replace Abstract: Multimodal federated learning (FL) is essential for real-world applications such as autonomous systems and healthcare, where data is distributed acr
arXiv:2604.12307v1 Announce Type: new Abstract: The proliferation of highly realistic AI-Generated Image (AIGI) has necessitated the development of practical detection methods. While current AIGI dete
arXiv:2604.12966v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) perform well on many vision-language tasks but often struggle with vision-centric problems that require fine-gr
arXiv:2508.18187v2 Announce Type: replace-cross Abstract: Memory decay makes it harder for the human brain to recognize visual objects and retain details. Consequently, recorded brain signals become w
arXiv:2604.12683v1 Announce Type: new Abstract: Current fMRI foundation models primarily rely on a limited range of brain states and mismatched pretraining tasks, restricting their ability to learn ge
arXiv:2604.12341v1 Announce Type: new Abstract: As generative image editing advances, image manipulation localization (IML) must handle both traditional manipulations with conspicuous forensic artifac
arXiv:2604.12660v1 Announce Type: new Abstract: In nonmonotonic reasoning from conditional belief bases, an inference operator satisfying syntax splitting postulates allows for taking only the relevan
arXiv:2603.28325v3 Announce Type: replace-cross Abstract: Biomedical knowledge resources often either preserve evidence as unstructured text or compress it into flat triples that omit study design, pr
arXiv:2604.12491v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed for tabular question answering, yet calibration on structured data is largely unstudied. This pap
arXiv:2604.12632v1 Announce Type: cross Abstract: Group Relative Policy Optimization (GRPO) enhances LLM reasoning but often induces overconfidence, where incorrect responses yield lower perplexity th
arXiv:2602.00181v3 Announce Type: replace-cross Abstract: Understanding camera dynamics is a fundamental pillar of video spatial intelligence. However, existing multimodal models predominantly treat t
arXiv:2604.11915v1 Announce Type: cross Abstract: Modern machine learning methods have been proposed to detect life in extraterrestrial samples, drawing on their ability to distinguish biotic from abi
arXiv:2604.12743v1 Announce Type: new Abstract: While recent research has explored AI tools' ability to classify the quality of mathematical tasks (arXiv:2603.03512), little is known about their capac
arXiv:2603.24647v4 Announce Type: replace Abstract: The autoresearch repository enables an LLM agent to optimize hyperparameters by editing training code directly. We use it as a testbed to compare cl
arXiv:2604.12262v1 Announce Type: cross Abstract: Cascaded LLM systems coordinate models of varying sizes with human experts to balance accuracy, cost, and abstention under uncertainty. However, singl
arXiv:2604.12992v1 Announce Type: cross Abstract: Predicting counterfactual outcomes in longitudinal data, where sequential treatment decisions heavily depend on evolving patient states, is critical y
arXiv:2509.15406v2 Announce Type: replace Abstract: AI generative models leave implicit traces in their generated images, which are commonly referred to as model fingerprints and are exploited for sou
arXiv:2604.12305v1 Announce Type: cross Abstract: Pneumonia remains a leading cause of childhood mortality worldwide, with a heavy burden in low-resource settings such as Bangladesh where radiologist
arXiv:2604.12318v1 Announce Type: new Abstract: Existing cell instance segmentation pipelines typically combine deterministic predictions with post-processing, which imposes limited explicit constrain
arXiv:2604.12391v1 Announce Type: cross Abstract: In this paper, we present Chain-of-Models Pre-Training (CoM-PT), a novel performance-lossless training acceleration method for vision foundation model
arXiv:2604.12833v1 Announce Type: new Abstract: Vision-Language Models (VLMs) have shown remarkable performance, yet their security remains insufficiently understood. Existing adversarial studies focu
arXiv:2503.14333v4 Announce Type: replace-cross Abstract: Brains construct not only 'first-order' representations of the environment but also 'higher-order' representations about those representations
arXiv:2602.05971v2 Announce Type: replace Abstract: Semantic representations can be framed as a structured, dynamic knowledge space through which humans navigate to retrieve and manipulate meaning. To
arXiv:2604.12190v1 Announce Type: cross Abstract: Many malicious actors responsible for disseminating synthetic non-consensual intimate imagery (SNCII) operate within internet forums to exchange resou
arXiv:2507.21990v4 Announce Type: replace-cross Abstract: Atomized chemical knowledge, such as functional group information of molecules and reactions, plays a pivotal intermediate role in the reasoni
arXiv:2604.12461v1 Announce Type: new Abstract: LLM-based Multi-Agent Systems (MAS) have demonstrated remarkable capabilities in solving complex tasks. Central to MAS is the communication topology whi
arXiv:2604.13024v1 Announce Type: new Abstract: The explosive growth of system logs makes streaming compression essential, yet existing log anomaly detection (LAD) methods incur severe pre-processing