Knowledge catalogue
arXiv:2606.21734v1 Announce Type: new Abstract: Understanding long videos requires fine-grained perception and multi-step, higher-order reasoning over complex, long-range spatio-temporal dynamics. Vis
arXiv:2606.22486v1 Announce Type: new Abstract: Medical expert annotators are scarce, and blind reliance on artificial intelligence (AI) can be misleading, motivating approaches in which humans, parti
arXiv:2510.17525v3 Announce Type: replace Abstract: Safe and efficient robotic navigation among humans is essential for integrating robots into everyday environments. Most existing approaches focus on
arXiv:2509.17125v2 Announce Type: replace Abstract: Relational object rearrangement (ROR) tasks (e.g., insert flower to vase) require a robot to manipulate objects with precise semantic and geometric
arXiv:2606.22158v1 Announce Type: new Abstract: Achieving human-like reasoning in Vision-Language Models (VLMs) remains a long-standing challenge. Recent approaches leverage Chain-of-Thought (CoT) rat
arXiv:2603.25857v2 Announce Type: replace Abstract: The capabilities of large language models (LLMs) have expanded beyond natural language processing to scientific prediction tasks, including molecula
arXiv:2606.20655v1 Announce Type: cross Abstract: Physics-informed and data-driven surrogates are increasingly used to approximate mechanics-governed flow fields, but the target quantities assigned to
arXiv:2606.22905v1 Announce Type: new Abstract: Recent diffusion-based models have enabled realistic audio-driven avatar generation in real-time streaming. However, existing approaches struggle to mai
arXiv:2606.22353v1 Announce Type: new Abstract: Fidelity and perceptual quality are two inherently competing and conflicting objectives in the image super-resolution (SR) task. Different loss function
arXiv:2606.23425v1 Announce Type: new Abstract: Accurate electricity load forecasting is a crucial prerequisite for stable power system operations. While prevalent deep learning models present competi
arXiv:2512.09021v3 Announce Type: replace-cross Abstract: Stellar and AGN-driven feedback processes affect the distribution of gas on a wide range of scales, from within galaxies well into the interga
arXiv:2606.23177v1 Announce Type: new Abstract: Deep learning-based medical image segmentation models are trained using annotations that exhibit systematic bias and variability across raters. While pr
arXiv:2606.21256v1 Announce Type: new Abstract: Quantum pure-state ensembles live on complex projective space, making flat Euclidean generative modeling geometrically mismatched. We introduce Intrinsi
arXiv:2412.00143v2 Announce Type: replace-cross Abstract: Oracle pruning, which selects unimportant weights by minimizing the pruned train loss, has served as the foundation for most neural network pr
arXiv:2511.14310v2 Announce Type: replace Abstract: Multi-source stationary computed tomography (CT) has recently attracted attention for its ability to achieve rapid image reconstruction, making it s
arXiv:2606.22892v1 Announce Type: cross Abstract: The clinical diagnosis of skin diseases is susceptible to interference from inter-class similarity of skin lesions, and over-reliance on clinicians'ex
arXiv:2509.22307v2 Announce Type: replace Abstract: Lightweight 3D medical image segmentation remains constrained by a fundamental extit{``efficiency / robustness conflict''}, particularly when proces
arXiv:2603.05663v2 Announce Type: replace Abstract: Video Temporal Grounding (VTG) localizes the temporal boundaries of query-relevant moments in long videos, making video-language-model prohibitively
arXiv:2606.23589v1 Announce Type: new Abstract: Long-horizon robot manipulation remains challenging because similar observations may occur at different execution stages, while the appropriate action d
arXiv:2509.23650v3 Announce Type: replace Abstract: Vision-based locomotion has shown great promise in enabling legged robots to perceive and adapt to complex environments. However, visual information
arXiv:2606.22369v1 Announce Type: cross Abstract: In this paper, we present Kiwano, an open-source toolkit designed to advance research and evaluation for speaker verification. Kiwano provides a light
arXiv:2606.23144v1 Announce Type: new Abstract: Optical Character Recognition (OCR) for low-resource languages is often constrained by the lack of annotated training data and the complexity of script-
arXiv:2508.12270v2 Announce Type: replace-cross Abstract: End-to-end deep learning has achieved impressive results but remains limited by its reliance on large labeled datasets, poor generalization to
arXiv:2606.20627v1 Announce Type: cross Abstract: Planning with world models is bottlenecked by compounding prediction errors and the difficulty of defining optimizable goals. Visual targets provide p
arXiv:2606.22801v1 Announce Type: new Abstract: Image restoration aims to recover high-quality images from degraded observations. Recent Mamba-based image restoration models have demonstrated strong p
arXiv:2606.20958v1 Announce Type: new Abstract: Modeling soft robot dynamics is challenging due to their continuum structure and typically nonlinear dynamics. Creating models based on first-order prin
arXiv:2510.09898v2 Announce Type: replace Abstract: Large language models (LLMs) have shown strong performance on code translation between widely used programming languages. However, translation becom
arXiv:2606.21957v1 Announce Type: new Abstract: Supervised learning demands large quantities of labeled data, a bottleneck that is expensive and reliant on domain-specific expertise. Self-supervised l
arXiv:2411.19468v4 Announce Type: replace Abstract: The random feature (RF) method is a powerful kernel approximation technique, but it typically uses fixed activation functions, limiting its adaptabi
arXiv:2606.22895v1 Announce Type: new Abstract: Graph theory is inherently descriptive, capturing what relationships exist but not why they arise, because it treats edges as primitive constructs. This
arXiv:2606.21718v1 Announce Type: cross Abstract: Detecting online polarization remains a critical challenge, particularly in multilingual and multicultural contexts where intergroup hostility is prev
arXiv:2606.23688v1 Announce Type: new Abstract: Reconstructing dynamic non-rigid objects from monocular video requires integrating visual cues from direct observations with data-driven priors over geo
arXiv:2606.23539v1 Announce Type: new Abstract: Visual document retrieval requires rapidly locating relevant pages from large multi-modal corpora in response to user queries. While recent methods powe
arXiv:2606.21018v1 Announce Type: cross Abstract: As artificial intelligence advances into the era of Embodied AI, live musical interaction urgently needs to break free from the limitations of offline
arXiv:2606.22013v1 Announce Type: new Abstract: Machine learning (ML) model serving has become a dominant consumer of GPU infrastructure, yet capacity planning in these systems remains largely ad hoc.
arXiv:2603.14343v2 Announce Type: replace Abstract: Large Audio-Language Models (LALMs) have shown strong performance in speech understanding, making speech a natural interface for accessing factual i
arXiv:2606.22772v1 Announce Type: new Abstract: Lip-syncing deepfakes are among the most challenging forms of manipulated media because their artifacts are localized almost exclusively to the mouth re
arXiv:2606.21968v1 Announce Type: new Abstract: Vision-Language Models (VLMs) struggle as query-relevant objects become smaller. To address this, recent training-free approaches dynamically retrieve a
arXiv:2606.23249v1 Announce Type: new Abstract: Humanoid local navigation in cluttered environments must jointly resolve obstacle avoidance, sparse-goal recovery, and stable whole-body locomotion unde
arXiv:2606.23126v1 Announce Type: new Abstract: While recent advancements in anomaly detection have demonstrated the efficacy of CNN- and Transformer-based approaches, these architectures face inheren
arXiv:2606.21194v1 Announce Type: new Abstract: Medical Vision-Language Models (Med-VLMs) achieve strong expert-level performance, yet their ability to generate patient-accessible descriptions remains
arXiv:2606.21329v1 Announce Type: new Abstract: Medical time series (MedTS) signals such as electroencephalography (EEG) and electrocardiography (ECG) support many clinical applications. However, subs
arXiv:2606.21047v1 Announce Type: new Abstract: Acoustic microrobots have emerged as a promising frontier for targeted drug delivery and minimally invasive medicine due to their high-power density and
arXiv:2606.21898v1 Announce Type: cross Abstract: 3D Gaussian Splatting (3DGS) has emerged as a promising method for high-quality, real-time 3D reconstruction. To associate 3DGS with mesh representati
arXiv:2606.23096v1 Announce Type: new Abstract: Minimax risk and regret are expectation-based criteria and do not capture rare but consequential failures. To address this concern, we develop a elta-ex
arXiv:2606.20906v1 Announce Type: new Abstract: Molecular message-passing neural networks commonly propagate chemically diverse interactions through a single graph, which may mix interaction-specific
arXiv:2602.20208v2 Announce Type: replace Abstract: Model merging aims to integrate multiple task-specific fine-tuned models derived from a shared pre-trained checkpoint into a single multi-task model
arXiv:2606.21943v1 Announce Type: new Abstract: Reinforcement learning (RL) has become central to LLM post-training, yet the methods that dominate current pipelines, PPO and GRPO, represent only a nar
arXiv:2606.21033v1 Announce Type: cross Abstract: Image compression for machines calls for a unified codec that serves multiple downstream vision tasks. Existing approaches either adopt task-specific
This post from Ethan Mollick likely explores how organizations can effectively implement AI through three key dimensions: leadership approaches to AI adoption, lab-based experimentation and testing, a
arXiv:2606.23000v1 Announce Type: new Abstract: Human motion follows a temporal hierarchical structure, transitioning from low-frequency global trajectories to high-frequency details. Inspired by the
arXiv:2606.21115v1 Announce Type: new Abstract: Remote photoplethysmography (rPPG) is a camera-based technique for measuring physiological signals, particularly cardiac activity. From the remotely mea
arXiv:2606.22400v1 Announce Type: new Abstract: This study introduces a computationally efficient convolutional neural network (CNN) architecture enhanced with transfer learning for multi-cancer detec
arXiv:2606.22197v1 Announce Type: new Abstract: Dynamic 3D Gaussian splatting faces a fundamental tension between motion consistency and visual fidelity. Deformation-based approaches preserve temporal
arXiv:2606.22220v1 Announce Type: new Abstract: Memorization in machine learning models enables high performance on rare in-distribution samples by capturing their atypical patterns. However, it also
arXiv:2606.21605v1 Announce Type: new Abstract: Vision foundation models have substantially advanced computer vision, enabling state-of-the-art performance in zero- and few-shot settings. They have be
arXiv:2606.21088v1 Announce Type: new Abstract: Achieving robust and generalizable manipulation across diverse environments remains a fundamental challenge in embodied robotics. Recent world action mo
arXiv:2606.21297v1 Announce Type: new Abstract: Augmenting model-free reinforcement learning (RL) with representations learned through observation dynamics prediction (observation-predictive RL) can i
arXiv:2606.22537v1 Announce Type: new Abstract: Out-of-Distribution (OOD) detection is essential for ensuring the robustness and reliability of object detection systems deployed in safety-critical app
arXiv:2606.20689v1 Announce Type: new Abstract: Neonatal jaundice (hyperbilirubinemia) is one of the most common conditions affecting newborns worldwide, with India alone recording roughly 15 million