Knowledge catalogue
arXiv:2607.07852v1 Announce Type: cross Abstract: Automated segmentation of cervical-spine MRI is increasingly used in clinical workflows, yet no fairness audit exists for this anatomy. We show that a
arXiv:2509.10757v2 Announce Type: replace Abstract: The tracking module of a visual-inertial SLAM system processes incoming image frames and IMU data to estimate the position of the frame in relation
arXiv:2607.08595v1 Announce Type: new Abstract: Cardiovascular disease risk prediction models often rely on data from a single institution or centrally pooled datasets. Extending these models across i
arXiv:2607.08368v1 Announce Type: new Abstract: With the widespread deployment of basic models in edge intelligence, communication bandwidth has become a core bottleneck restricting the scalability of
arXiv:2607.08014v1 Announce Type: new Abstract: Federated learning (FL) is a collaborative learning scheme to train deep learning models, where collaborating parties can consolidate their models witho
arXiv:2607.07859v1 Announce Type: new Abstract: Reinforcement learning (RL) research has increasingly shifted focus towards alignment, ensuring agents learn behaviors adhering to human values. While h
arXiv:2607.07952v1 Announce Type: cross Abstract: Motion and emotion are core parts of intelligent, expressive behavior. In this paper, we introduce fog, a function composition framework for implement
arXiv:2607.08652v1 Announce Type: new Abstract: Self-interested agents, left unconstrained, tend toward defection in repeated social dilemmas, causing cooperative gains from trade to collapse. This pa
arXiv:2607.08427v1 Announce Type: cross Abstract: Achieving nanosecond-scale inference latency for deep neural networks (DNNs) has become a primary architectural concern for latency-critical applicati
arXiv:2607.08475v1 Announce Type: new Abstract: Multi-modality transportation refers to urban systems composed of multiple transportation modes, such as traffic flow and public transit, whose dynamics
arXiv:2607.08009v1 Announce Type: new Abstract: We introduce a Bloom-aligned framework for measuring educational control in Large Language Models (LLMs): the ability to preserve a task's instructional
arXiv:2607.08288v1 Announce Type: cross Abstract: In critical infrastructure, operational technology environments often cannot be actively scanned, and yet active system feedback is needed for risk as
arXiv:2607.08028v1 Announce Type: new Abstract: Enterprise large language model (LLM) applications often begin as prototypes whose behavior is carried by prompts and retrieval context. Productization
arXiv:2607.07779v1 Announce Type: cross Abstract: Recent developments in AI for Mathematics (AI4Math), especially Large Language Model (LLM)-driven theorem provers, has achieved remarkable success in
arXiv:2503.05598v3 Announce Type: replace-cross Abstract: This review examines neural operator architectures for learning solution operators of parametric partial differential equations (PDEs), with a
arXiv:2607.07824v1 Announce Type: cross Abstract: Large Language Models (LLMs) have substantially advanced persona-based dialogue agents for emotion-sensitive role simulation in healthcare, education,
arXiv:2607.08359v1 Announce Type: cross Abstract: Vision-Language Navigation (VLN) enables UAV autonomous navigation in unknown environments by mapping language instructions to real-time visual inputs
arXiv:2607.07881v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used for code generation, but they struggle to generate functional code free of security vulnerabilities
arXiv:2502.20805v3 Announce Type: replace-cross Abstract: Hand-object interaction(HOI) is the fundamental link between human and environment, yet its dexterous and complex pose significantly challenge
arXiv:2607.08403v1 Announce Type: new Abstract: The application of lightweight Large Language Models in rule-based scientific domains remains severely limited by their tendency to mimic linguistic pat
arXiv:2601.11440v3 Announce Type: replace-cross Abstract: Urban wind flow reconstruction is essential for assessing air quality, heat dispersion, and pedestrian comfort, yet remains challenging when o
arXiv:2607.08144v1 Announce Type: cross Abstract: Through-the-wall radar (TWR) human activity recognition (HAR) is important for non-line-of-sight indoor sensing, security monitoring, and emergency re
arXiv:2512.01803v3 Announce Type: replace Abstract: Despite rapid advances in video generative models, robust metrics for evaluating visual and temporal correctness of complex human actions remain elu
arXiv:2607.08769v1 Announce Type: new Abstract: Scaling 3D Gaussian Splatting (3DGS) to large outdoor scenes is costly in both data acquisition and computation. Adopting panoramic images with equirect
arXiv:2511.18940v3 Announce Type: replace Abstract: Cross-subject motor imagery decoding remains a fundamental challenge in EEG-based brain-computer interfaces due to substantial inter-subject variabi
arXiv:2412.03259v3 Announce Type: replace Abstract: Event-based vision sensors offer high temporal resolution, high dynamic range, and low power consumption, yet event-based vision models lag behind c
arXiv:2607.07880v1 Announce Type: new Abstract: Synthesizing realistic full-body human interactions with articulated objects is a fundamental challenge for embodied AI and graphics, with applications
arXiv:2607.08319v1 Announce Type: cross Abstract: We present GitLake, a Git-for-data design for an agent-first lakehouse. The system lifts single-table Iceberg snapshots into lakehouse-wide commits, b
arXiv:2412.07259v5 Announce Type: replace Abstract: DatalogMTL is a powerful rule-based language for temporal reasoning. Due to its high expressive power and flexible modeling capabilities, it is suit
arXiv:2607.07840v1 Announce Type: cross Abstract: Gradient estimation -- the task of computing the gradient of the expected value of a probabilistic program -- has diverse applications in scientific c
arXiv:2602.08417v2 Announce Type: replace Abstract: Map-based LiDAR pose tracking is essential for long-term autonomous operation, where onboard map priors need be compact for scalable storage and fas
arXiv:2607.07773v1 Announce Type: cross Abstract: EEG-based emotion recognition is critical for mental health monitoring and affective brain-computer interfaces, yet existing deep learning approaches
arXiv:2607.08086v1 Announce Type: new Abstract: Designing functional and aesthetically coherent floor plans requires exploring a vast space of possible room arrangements, a task that quickly becomes o
arXiv:2607.08346v1 Announce Type: new Abstract: Form 8-K filings are the primary channel through which U.S. public companies disclose material events, but the SEC item codes attached to them are coars
arXiv:2411.15723v4 Announce Type: replace Abstract: High-fidelity surface reconstruction from multi-view images is a core problem in 3D computer vision. While neural implicit surfaces like SDFs offer
arXiv:2602.11117v2 Announce Type: replace Abstract: We present HairWeaver, a diffusion-based pipeline that animates a single human image with realistic and expressive hair dynamics. While existing met
arXiv:2607.07993v1 Announce Type: new Abstract: Identifying faithfulness hallucinations in LLM-generated outputs remains challenging due to the scarcity of high-quality annotated data. Recent work rel
arXiv:2607.08448v1 Announce Type: new Abstract: Language-conditioned manipulation requires both precise contact-rich control and robust reasoning over language, scenes, and long horizons. End-to-end V
arXiv:2601.22448v2 Announce Type: replace-cross Abstract: RLVR has become a standard recipe for training LLMs on reasoning tasks with verifiable outcomes, but when rollout generation dominates the cos
arXiv:2503.08394v5 Announce Type: replace-cross Abstract: Multi-task optimization is typically characterized by a fixed and finite set of tasks. The present paper relaxes this condition by considering
arXiv:2607.08186v1 Announce Type: new Abstract: Scaling Large Language Models (LLMs) has been driven mainly by enlarging the Transformer backbone, but for an already-strong model this requires another
arXiv:2607.08538v1 Announce Type: cross Abstract: Suppose we observe two sets of n Gaussian vectors in R^d, with the promise that, after applying a permutation of [n] and a rotation of R^d, the two se
arXiv:2607.08063v1 Announce Type: new Abstract: Unsupervised constituency parsing aims to accurately induce latent tree structures from raw text alone. Recent neural parameterizations of PCFGs achieve
arXiv:2607.08398v1 Announce Type: cross Abstract: Standard pipelines for physics-ready 3D reconstruction rely on a decoupled two-stage paradigm: extracting surface geometry followed by an error-prone
arXiv:2508.11214v2 Announce Type: replace-cross Abstract: Explanations of cognitive behavior often appeal to computations over representations. What does it take for a system to implement a given comp
arXiv:2607.07891v1 Announce Type: cross Abstract: Roy Harris's Integrationist linguistics offers a compelling critique of the referentialist tradition embedded deep at the heart of computational appro
arXiv:2607.08249v1 Announce Type: new Abstract: Slot attention is a powerful framework for object-centric learning, decomposing visual scenes into latent slots through iterative competitive attention.
arXiv:2607.08705v1 Announce Type: new Abstract: Rapid advancements in video diffusion models and temporal editing tools have enabled the generation of highly realistic human-centric videos, posing unp
arXiv:2607.08143v1 Announce Type: cross Abstract: We present the results of HIPE-OCRepair-2026, an ICDAR competition on LLM-assisted OCR post-correction of historical documents. OCR post-correction re
arXiv:2607.08758v1 Announce Type: new Abstract: Scientific ideas rarely start from a blank page. They inherit mechanisms, repair known limitations, and recombine pieces of earlier work, much like biol
arXiv:2607.07775v1 Announce Type: new Abstract: The human body is at the center of a growing family of technologies designed to tightly and persistently couple biological and digital systems. Robotic
arXiv:2409.05559v2 Announce Type: replace Abstract: Large language models (LLMs) have developed rapidly, and their reasoning capabilities have become a hot research topic. However, there is still limi
arXiv:2607.07754v1 Announce Type: new Abstract: Pattern recognition problems arise in a variety of physical image processing situations, and convolutional neural networks are a popular scheme for the
arXiv:2509.26076v2 Announce Type: replace Abstract: As the mathematical capabilities of large language models (LLMs) improve, it becomes increasingly important to evaluate their performance on researc
arXiv:2607.08540v1 Announce Type: cross Abstract: Conversational information retrieval is challenging since it requires the consideration of the conversation history which potentially gives rise to to
arXiv:2606.21887v2 Announce Type: replace-cross Abstract: During hot tests on a production line, engine-sound analysis is crucial to ensuring product quality and performance. However, background noise
arXiv:2603.19186v3 Announce Type: replace Abstract: Randomized controlled trials (RCTs) are the gold standard for estimating treatment effects, yet they are often underpowered for detecting effect het
arXiv:2607.08579v1 Announce Type: cross Abstract: Missing data is a persistent obstacle in scientific, social science, and public health research, often biasing analyses and placing accountability on
arXiv:2607.07972v1 Announce Type: new Abstract: Recent advances in actuation, control and learning have rapidly pushed humanoid robots from a distant vision towards near-term real-world deployment. He
arXiv:2607.07836v1 Announce Type: new Abstract: We present Infinity-Parser2, a large multimodal model that couples a controllable data-synthesis pipeline with multi-task reinforcement learning for end