Knowledge catalogue
arXiv:2604.15037v1 Announce Type: cross Abstract: Recent advancements in LLM agents are gradually shifting from reactive, text-based paradigms toward proactive, multimodal interaction. However, existi
arXiv:2604.14933v1 Announce Type: new Abstract: Skeleton-based human action recognition is a powerful approach for understanding human behaviour from pose data, but collecting large-scale, diverse, an
arXiv:2604.14800v1 Announce Type: cross Abstract: Objective. Standard Magnetic Resonance Imaging (MRI) reconstruction pipelines discard phase information captured during acquisition, despite evidence
arXiv:2604.15284v1 Announce Type: new Abstract: The efficient spatial allocation of primitives serves as the foundation of 3D Gaussian Splatting, as it directly dictates the synergy between representa
arXiv:2604.14928v1 Announce Type: new Abstract: We introduce a hybrid Gaussian-hash-grid radiance representation for reconstructing 2D Gaussian scene models from multi-view images. Similar to NeST spl
arXiv:2604.14240v1 Announce Type: cross Abstract: The simulation of complex systems increasingly relies on sophisticated but fundamentally opaque computational black-box simulators. Surrogate models p
arXiv:2604.14922v1 Announce Type: cross Abstract: Reinforcement Learning (RL) has emerged as a critical driver for enhancing the reasoning capabilities of Large Language Models (LLMs). While recent ad
arXiv:2604.15203v1 Announce Type: new Abstract: Machine learning in high-stakes domains such as healthcare requires not only strong predictive performance but also reliable uncertainty quantification
arXiv:2509.26007v2 Announce Type: replace-cross Abstract: Research on audio generation has progressively developed along both waveform-based and spectrogram-based directions, giving rise to diverse st
arXiv:2604.14953v1 Announce Type: new Abstract: Gesture recognition research, unlike NLP, continues to face acute data scarcity, with progress constrained by the need for costly human recordings or im
arXiv:2511.19204v3 Announce Type: replace Abstract: We present a sampling-based model predictive control (MPC) framework that enables emergent locomotion without relying on handcrafted gait patterns o
arXiv:2603.27833v2 Announce Type: cross Abstract: In this work, we first prove that the separation principle holds for communication-constrained LQR problems under i.i.d. zero-mean disturbances with a
arXiv:2604.13041v1 Announce Type: cross Abstract: Table Structure Recognition (TSR) requires the logical reasoning ability of large language models (LLMs) to handle complex table layouts, but current
arXiv:2604.14197v1 Announce Type: new Abstract: Large language model (LLM) performance depends heavily on prompt design, yet prompt construction is often described and applied inconsistently. Our purp
arXiv:2510.27420v3 Announce Type: replace Abstract: Multi-embodiment grasping focuses on developing approaches that exhibit generalist behavior across diverse gripper designs. Existing methods often l
arXiv:2604.13488v1 Announce Type: new Abstract: Autonomous Graphical User Interface (GUI) agents powered by Multimodal Large Language Models (MLLMs) enable digital automation on end-user devices. Whil
arXiv:2604.15074v1 Announce Type: new Abstract: This paper presents a two-stage trajectory planning framework for a multi-UAV rigid-payload cascaded transportation system, aiming to address planning c
arXiv:2604.14906v1 Announce Type: cross Abstract: The SARS-CoV-2 RNA pseudoknot is a promising target for antiviral intervention, as it regulates the efficiency of -1 programmed ribosomal frameshiftin
arXiv:2604.13171v1 Announce Type: new Abstract: The human face is central to communication. For immersive applications, the digital presence of a person should mirror the physical reality, capturing t
arXiv:2604.06168v2 Announce Type: replace Abstract: World action models (WAMs) have emerged as a promising direction for robot policy learning, as they can leverage powerful video backbones to model t
This r/StableDiffusion thread likely discusses methods and AI tools for adding AI-generated or sourced audio — including voice, sound effects, and ambient sound — to existing videos created with Stabl
arXiv:2604.13924v1 Announce Type: cross Abstract: Time-series anomaly detection (TSAD) is critical in domains such as industrial monitoring, healthcare, and cybersecurity, but it remains challenging d
arXiv:2604.13938v1 Announce Type: new Abstract: Subject-driven image generation has shown great success in creating personalized content, but its capabilities are largely confined to single subjects i
arXiv:2604.13459v1 Announce Type: new Abstract: Turbofan engine degradation under sustained operational stress necessitates robust prognostic systems capable of accurately estimating the Remaining Use
arXiv:2604.13891v1 Announce Type: new Abstract: Automated driving at unsignalized intersections is challenging due to complex multi-vehicle interactions and the need to balance safety and efficiency.
arXiv:2604.13325v1 Announce Type: new Abstract: Safety filters provide a practical approach for enforcing safety constraints in autonomous systems. While learning-based tools scale to high-dimensional
arXiv:2603.27064v2 Announce Type: replace-cross Abstract: Understanding charts requires models to jointly reason over geometric visual patterns, structured numerical data, and natural language -- a ca
arXiv:2604.13471v1 Announce Type: new Abstract: In silico tools are important for generating novel hypotheses and exploring alternatives in de novo metabolic pathway design. However, while many comput
arXiv:2604.13065v1 Announce Type: new Abstract: LLMs can execute every step of chain-of-thought reasoning correctly and still produce wrong final answers. We introduce the Novel Operator Test, a bench
arXiv:2604.13543v1 Announce Type: cross Abstract: Long Short-Term Memory (LSTM) neural networks have penetrated healthcare applications where real-time requirements and edge computing capabilities are
arXiv:2604.13509v1 Announce Type: new Abstract: Recent advances in video generation models has significantly accelerated video generation and related downstream tasks. Among these, video stylization h
arXiv:2604.13800v1 Announce Type: new Abstract: Embodied AI research is increasingly moving beyond single-task, single-environment policy learning toward multi-task, multi-scene, and multi-model setti
arXiv:2601.08605v2 Announce Type: replace Abstract: Experience intervention in web agents emerges as a promising technical paradigm, enhancing agent interaction capabilities by providing valuable insi
arXiv:2604.13667v1 Announce Type: new Abstract: DNA-based storage has emerged as a promising approach to the global data crisis, offering molecular-scale density and millennial-scale stability at low
arXiv:2507.13942v2 Announce Type: replace Abstract: Forecasting future events is a fundamental capability for general-purpose systems that plan or act across different levels of abstraction. Yet, eval
arXiv:2604.13288v1 Announce Type: new Abstract: We present a unified pipeline for synthesizing high-quality Quechua and Spanish speech for the Peruvian Constitution using three state-of-the-art text-t
arXiv:2603.28554v2 Announce Type: replace Abstract: Visual document understanding typically requires separate retrieval and generation models, doubling memory and system complexity. We present Hydra,
This paper was accepted at the Workshop on Navigating and Addressing Data Problems for Foundation Models (NADPFM) at ICLR 2026. Principled domain reweighting can substantially improve sample efficienc
arXiv:2604.13579v1 Announce Type: new Abstract: Conventional Retrieval-Augmented Generation (RAG) systems often struggle with complex multi-hop queries over long documents due to their single-pass ret
arXiv:2604.14062v1 Announce Type: new Abstract: Human-Object Interaction (HOI) modelling captures how humans act upon and relate to objects, typically expressed as triplets. Existing approaches split
arXiv:2604.13863v1 Announce Type: new Abstract: Image generation technology can synthesize condition-specific images to supplement real-world industrial anomaly data and enhance anomaly detection mode
arXiv:2604.13236v1 Announce Type: new Abstract: Semiconductor failure analysis (FA) requires engineers to examine inspection images, correlate equipment telemetry, consult historical defect records, a
arXiv:2604.13333v1 Announce Type: new Abstract: We present SSD-GS, a physically-based relighting framework built upon 3D Gaussian Splatting (3DGS) that achieves high-quality reconstruction and photore
There's a broadly held misconception in AI that methods that scale well are simple methods -- even, that simple methods usually scale. This is completely wrong. Pretty much none of the truly simple me
arXiv:2604.14069v1 Announce Type: new Abstract: Human-Object Interaction (HOI) detection is a longstanding computer vision problem concerned with predicting the interaction between humans and objects.
arXiv:2604.12811v1 Announce Type: cross Abstract: Dense Associative Memory (DAM) generalizes Hopfield networks through higher-order interactions and achieves storage capacity that scales as O(N^{n-1})
arXiv:2604.12255v1 Announce Type: cross Abstract: Dynamic facial expression recognition in the wild remains challenging due to data scarcity and long-tail distributions, which hinder models from effec
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: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: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:2602.15355v3 Announce Type: replace Abstract: The emergence of 3D Gaussian Splatting has fundamentally redefined the capabilities of photorealistic neural rendering by enabling high-throughput s
arXiv:2601.21297v2 Announce Type: replace Abstract: We introduce Deep QP Safety Filter, a fully data-driven safety layer for black-box dynamical systems. Our method learns a Quadratic-Program (QP) saf
arXiv:2510.03323v2 Announce Type: replace Abstract: Integrating textual graphs into Large Language Models (LLMs) is promising for complex graph-based QA. However, a key bottleneck is retrieving inform
arXiv:2509.16806v4 Announce Type: replace Abstract: Endoluminal endoscopic procedures are essential for diagnosing colorectal cancer and other severe conditions in the digestive tract, urogenital syst
arXiv:2604.12766v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) typically relies on a flat retrieval paradigm that maps queries directly to static, isolated text segments. This ap
arXiv:2410.04960v5 Announce Type: replace Abstract: The Segment Anything Model (SAM) is a foundational model for image segmentation tasks, known for its strong generalization across diverse applicatio
arXiv:2604.12856v1 Announce Type: new Abstract: Audio-driven bimanual piano motion generation requires precise modeling of complex musical structures and dynamic cross-hand coordination. However, exis
arXiv:2604.12867v1 Announce Type: new Abstract: As agentic foundation models continue to evolve, how to further improve their performance in vertical domains has become an important challenge. To this
arXiv:2506.14512v4 Announce Type: replace Abstract: Large Language Models (LLMs) have undergone rapid progress, largely attributed to reinforcement learning on complex reasoning tasks. In contrast, wh