Knowledge catalogue
arXiv:2512.12643v2 Announce Type: replace Abstract: Legal relations serve as an important analytical framework for dispute resolution in civil cases. However, legal relations in Chinese civil cases re
arXiv:2604.17062v1 Announce Type: new Abstract: Zero-shot action recognition is challenging due to the semantic gap between seen and unseen classes. We present a novel framework that enhances CLIP wit
// Multi-Agent Synthesis RAG // Nice paper on improving RAG systems with multiple agents. (bookmark it) The paper introduces MASS-RAG, a multi-agent synthesis framework for retrieval-augmented generat
arXiv:2604.16468v1 Announce Type: new Abstract: Accurate phase equilibria are foundational to alloy design because they encode the underlying thermodynamics governing stability, transformations, and p
arXiv:2604.18019v1 Announce Type: new Abstract: Sketch-based 3D shape retrieval (SBSR) aims to retrieve 3D shapes that are consistent with the category of the input hand-drawn sketch. The core challen
arXiv:2604.17122v1 Announce Type: new Abstract: Breast cancer is a leading cause of cancer-related mortality worldwide, and timely accurate diagnosis is critical to improving survival outcomes. While
arXiv:2604.18564v1 Announce Type: new Abstract: Video world models have achieved remarkable success in simulating environmental dynamics in response to actions by users or agents. They are modeled as
arXiv:2604.16581v1 Announce Type: new Abstract: Neural Combinatorial Optimization (NCO) has emerged as a powerful framework for solving combinatorial optimization problems by integrating deep learning
arXiv:2604.17052v1 Announce Type: new Abstract: Streaming video reasoning requires models to operate in a setting where history grows without bound while meaningful evidence remains scarce. In such a
arXiv:2604.00131v2 Announce Type: replace Abstract: Human memory adapts through selective forgetting: experiences become less accessible over time but can be reactivated by reinforcement or contextual
arXiv:2604.16878v1 Announce Type: new Abstract: Early prediction of severe clinical deterioration and remaining length of stay can enable timely intervention and better resource allocation in high-acu
arXiv:2604.17706v1 Announce Type: new Abstract: Visual-Language-Action (VLA) models represent a paradigm shift in embodied AI, yet existing frameworks often struggle with imprecise spatial perception,
arXiv:2604.17802v1 Announce Type: cross Abstract: Generative Semantic Communication (GSC) is a promising solution for image transmission over narrow-band and high-noise channels. However, existing GSC
arXiv:2604.16515v1 Announce Type: new Abstract: The rapid proliferation of Multimodal Large Language Models (MLLMs) has enabled mobile agents to execute high-stakes financial transactions, but their a
arXiv:2604.17543v1 Announce Type: new Abstract: Large language models (LLMs) have achieved remarkable success in general-domain tasks, yet their direct application to the legal domain remains challeng
arXiv:2604.17163v1 Announce Type: new Abstract: We propose PPEDCRF, a calibrated selective perturbation framework that protects background-based location privacy in released video frames against galle
arXiv:2510.16054v2 Announce Type: replace-cross Abstract: When users submit queries to Large Language Models (LLMs), their prompts can often contain sensitive data, forcing a difficult choice: Send th
arXiv:2506.01770v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have achieved tremendous success in various tasks, yet concerns about their safety and security have emerged. In
arXiv:2604.16606v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed in high-stakes domains, yet a unified treatment of their overlapping safety challenges remains
arXiv:2604.17527v1 Announce Type: new Abstract: Safe and agile trajectory planning is essential for autonomous systems, especially during complex aerobatic maneuvers. Motivated by the recent success o
arXiv:2604.16424v1 Announce Type: cross Abstract: State-Space Models (SSMs) -- structured SSMs (S4, S4D, DSS, S5), selective SSMs (Mamba, Mamba-2), and hybrid architectures (Jamba) -- are deployed in
arXiv:2505.21471v2 Announce Type: replace Abstract: With the rapid advancement of post-training techniques for reasoning and information seeking, large language models (LLMs) can incorporate a large q
arXiv:2510.02034v2 Announce Type: replace Abstract: We introduce METHODNAME, a novel framework for semantic-aware 3D shape and texture morphing directly from multi-view images. While 3D Gaussian Splat
arXiv:2505.19237v2 Announce Type: replace-cross Abstract: Self-recognition -- the ability to maintain an internal representation of one's own body within the environment -- underpins intelligent, auto
arXiv:2604.02908v2 Announce Type: replace Abstract: We present SentiAvatar, a framework for building expressive interactive 3D digital humans, and use it to create SuSu, a virtual character that speak
arXiv:2506.08013v2 Announce Type: replace Abstract: Multi-task learning for dense prediction is limited by the need for extensive annotation for every task, though recent works have explored training
arXiv:2601.01248v4 Announce Type: replace-cross Abstract: In this work, we investigate a stochastic control framework for global optimization over both Euclidean spaces and the Wasserstein space of pr
arXiv:2604.17773v1 Announce Type: new Abstract: Three-dimensional (3D) medical image enhancement, including denoising and super-resolution, is critical for clinical diagnosis in CT, PET, and MRI. Alth
arXiv:2604.16585v1 Announce Type: new Abstract: We present the Global Neural World Model (GNWM), a self-stabilizing framework that achieves topological quantization through balanced continuous entropy
arXiv:2509.02547v5 Announce Type: replace-cross Abstract: The emergence of agentic reinforcement learning (Agentic RL) marks a paradigm shift from conventional reinforcement learning applied to large
arXiv:2604.17674v1 Announce Type: new Abstract: Legal practitioners and judicial institutions face an ever-growing volume of case-law documents characterised by formalised language, lengthy sentence s
arXiv:2603.08096v3 Announce Type: replace Abstract: Localizing objects and parts from natural language in 3D space is essential for robotics, AR, and embodied AI, yet existing methods face a trade-off
arXiv:2602.11893v3 Announce Type: replace Abstract: We introduce a universal diffusion-based downscaling framework that lifts deterministic low-resolution weather forecasts into probabilistic high-res
arXiv:2509.16538v3 Announce Type: replace-cross Abstract: We propose VC-Inspector, a lightweight, open-source large multimodal model (LMM) for reference-free evaluation of video captions, with a focus
arXiv:2508.15229v3 Announce Type: replace Abstract: Small Language Models (SLMs) provide computational advantages in resource-constrained environments, yet memory limitations remain a critical bottlen
arXiv:2604.15609v1 Announce Type: cross Abstract: Test-Time Adaptation (TTA) for black-box models accessible only via APIs remains a largely unexplored challenge. Existing approaches such as post-hoc
arXiv:2311.00656v4 Announce Type: replace-cross Abstract: Spatial-temporal estimation of signals on graph edges is challenging because most conventional Graph Signal Processing techniques are defined
This post references @dexhorthy quoting the Z/L continuum concept at an AIE Miami event, suggesting the idea is gaining traction in AI discussions. The Z/L continuum appears to be a framework or model
arXiv:2604.15709v1 Announce Type: new Abstract: Agent exttt{skills} are structured collections of instructions, tools, and supporting resources that help large language model (LLM) agents perform part
arXiv:2604.16011v1 Announce Type: new Abstract: Borehole breakouts are stress-induced spalling on the borehole wall, which are identifiable in acoustic image logs as paired zones with near-symmetry az
arXiv:2604.15875v1 Announce Type: new Abstract: We present Cloth-HUGS, a Gaussian Splatting based neural rendering framework for photorealistic clothed human reconstruction that explicitly disentangle
arXiv:2604.15840v1 Announce Type: new Abstract: Reinforcement learning for LLM agents is typically conducted on a static data distribution, which fails to adapt to the agent's evolving behavior and le
arXiv:2604.15573v1 Announce Type: cross Abstract: In recent years, neural networks and other complex models have dominated recommender systems, often setting new benchmarks for state-of-the-art perfor
arXiv:2604.15547v1 Announce Type: cross Abstract: The fundamental challenge of using Large Language Models (LLMs) for reliable, enterprise-grade analytics, such as sentiment prediction, is the conflic
arXiv:2604.15456v1 Announce Type: new Abstract: Trustworthiness and transparency are essential for the clinical adoption of artificial intelligence (AI) in healthcare and biomedical research. Recent d
arXiv:2604.16231v1 Announce Type: new Abstract: Panoramic radiography is a fundamental diagnostic tool in dentistry, offering a comprehensive view of the entire dentition with minimal radiation exposu
arXiv:2604.16284v1 Announce Type: new Abstract: Atmospheric haze significantly degrades wildlife imagery, impeding computer vision applications critical for conservation, such as animal detection, tra
arXiv:2510.13220v2 Announce Type: replace Abstract: A fundamental limitation of current AI agents is their inability to learn complex skills on the fly at test time, often behaving like 'clever but cl
arXiv:2510.13920v2 Announce Type: replace Abstract: Query-focused table summarization requires generating natural language summaries of tabular data conditioned on a user query, enabling users to acce
arXiv:2604.15795v1 Announce Type: new Abstract: 3D object detection models trained in one server plays an important role in autonomous driving, robotics manipulation, and augmented reality scenarios.
arXiv:2604.15775v1 Announce Type: new Abstract: Learning with large-scale datasets and information-critical applications, such as in High Energy Physics (HEP), demands highly complex, large-scale mode
arXiv:2604.15990v1 Announce Type: cross Abstract: This paper traces a conceptual shift from understanding vulnerability as a static, essentialized property of data subjects to examining how it is acti
arXiv:2604.15782v1 Announce Type: new Abstract: Traffic simulations, essential for planning urban transit infrastructure interventions, require vehicle-category-specific origin-destination (OD) data.
arXiv:2604.15482v1 Announce Type: cross Abstract: Large Language Models (LLMs) unlearning is crucial for removing hazardous or privacy-leaking information from the model. Practical LLM unlearning dema
arXiv:2604.15679v1 Announce Type: cross Abstract: Active inference, a neurally-inspired model for inferring actions based on the free energy principle (FEP), has been proposed as a unifying framework
arXiv:2604.16247v1 Announce Type: cross Abstract: We propose HILBERT (HIerarchical Long-sequence Balanced Embedding with Reciprocal contrastive Training), a cross-attentive multimodal framework for le
arXiv:2602.07303v3 Announce Type: replace-cross Abstract: Log anomaly detection is crucial for uncovering system failures and security risks. Although logs originate from nested component executions w
arXiv:2604.15529v1 Announce Type: new Abstract: Current large language models reason in isolation. Although it is common to sample multiple reasoning paths in parallel, these trajectories do not inter
arXiv:2604.16175v1 Announce Type: new Abstract: Automated 3D radiology report generation often suffers from clinical hallucinations and a lack of the iterative verification found in human practice. Wh
arXiv:2604.14518v2 Announce Type: replace Abstract: We present Mind DeepResearch (MindDR), an efficient multi-agent deep research framework that achieves leading performance with only ~30B-parameter m