Knowledge catalogue
arXiv:2609.27560v1 Announce Type: cross Abstract: Avatar-streaming systems are commonly evaluated with image and video quality assessment (IQA/VQA) metrics, implicitly treating visual fidelity as a pr
arXiv:2609.28467v1 Announce Type: cross Abstract: Social navigation typically assumes a specified goal and focuses on reaching it while respecting social conventions, whereas robot group joining requi
arXiv:2609.26929v1 Announce Type: new Abstract: People hold diverse, sometimes conflicting values, so no single aligned model can satisfy everyone. Pluralistic alignment therefore calls for steerable
arXiv:2609.27033v1 Announce Type: cross Abstract: Reward fine-tuning aims to update a pre-trained flow-based generative model to improve the downstream reward of its generated samples. Existing method
arXiv:2609.27449v1 Announce Type: new Abstract: Generalist robot manipulation policies have developed rapidly, yet their reliable evaluation remains challenging due to fundamental flaws in existing si
arXiv:2609.27203v1 Announce Type: new Abstract: xlog is a CUDA-native logic programming engine integrating neural perception with deterministic Datalog, probabilistic inference, and epistemic world vi
arXiv:2609.28342v1 Announce Type: new Abstract: Removing an object from a real image requires more than synthesizing plausible content within a mask: the method must suppress residual object features,
arXiv:2609.27199v1 Announce Type: new Abstract: Sparse communication in decentralized zeroth-order learning requires compatible peer-state coordinates. We characterize this one-hop condition and devel
arXiv:2609.28083v1 Announce Type: new Abstract: Digital zoom transitions between dual cameras often exhibit conspicuous discontinuities in geometric structure and chromatic consistency, degrading the
arXiv:2609.25470v1 Announce Type: new Abstract: Bioinspired feedback controls for pursuit, tracking, and collective motion are often expressed in terms of the relative configuration between interactin
arXiv:2609.22956v1 Announce Type: new Abstract: Parkinson's disease alters gait and bilateral coordination, but machine-learning performance also depends on how continuous gait signals are represented
arXiv:2609.25012v1 Announce Type: new Abstract: Diachronic word embeddings have become the modern standard for tracking semantic change, yet they have been largely validated on modern, high-resource,
arXiv:2609.26623v1 Announce Type: new Abstract: Diffusion-based synthetic data generation offers a promising route for sharing medical imaging data without releasing sensitive patient records. However
arXiv:2609.26783v1 Announce Type: cross Abstract: We study decentralized partially observable team decision problems with low-rank latent dynamics and unknown system models. The proposed framework com
arXiv:2609.25614v1 Announce Type: new Abstract: This article presents a bimanual teleoperation pipeline and conceptual design of a deployable four-finger payload for intra-vehicular free-flyers. Futur
arXiv:2609.25511v1 Announce Type: new Abstract: Vision-based gesture control accepts commands from any hand in the camera field of view, which is unsafe in shared indoor spaces. This paper presents IG
arXiv:2609.24725v1 Announce Type: cross Abstract: Head-and-neck anatomy changes over a six-to-seven-week proton course, and the anatomy of a later week cannot be imaged when the plan is made. We prese
arXiv:2609.24883v1 Announce Type: new Abstract: Artificial intelligence (AI) registers and inventories aim to make governmental AI visible, but their institutional scope, schemas, and reporting practi
arXiv:2609.22476v1 Announce Type: cross Abstract: Transmission system operators face rising complexity from renewable integration, reduced inertia, and tighter security margins. Large language models
arXiv:2512.09443v3 Announce Type: replace-cross Abstract: We investigate how large language models can be used as research tools in scientific computing while preserving mathematical rigor. We propose
arXiv:2609.26243v1 Announce Type: cross Abstract: The rapidly increasing student population has posed serious challenges to the traditional academic advising process. This study designs and implements
arXiv:2609.25541v1 Announce Type: new Abstract: Tabular foundation models learn to predict cell values in context, whereas world-model self-supervision asks for prediction in representation space (LeC
arXiv:2609.24348v1 Announce Type: cross Abstract: AI coding agents increasingly support software development beyond code completion, including planning, implementation, testing, and repository-level t
arXiv:2609.25781v1 Announce Type: new Abstract: Graph Incremental Learning has garnered increasing attention as dynamic graph data continues to emerge across diverse fields. Conventional approaches pr
arXiv:2609.26244v1 Announce Type: cross Abstract: Accurately forecasting river runoff is key to managing water resources, controlling floods, and planning agriculture. This study examines the Ajichay
arXiv:2602.01163v2 Announce Type: replace Abstract: Safe UAV emergency landing requires more than just identifying flat terrain; it demands understanding complex semantic risks (e.g., crowds, temporar
arXiv:2609.26445v1 Announce Type: cross Abstract: This manuscript formalizes the most popular model validation tools used in general insurance actuarial modeling. These include graphical tools like ca
arXiv:2609.25471v1 Announce Type: new Abstract: Semi-supervised federated learning (SSFL) trains models on clients' unlabeled data using a teacher to generate pseudo-labels, with a small labeled seed
arXiv:2609.25639v1 Announce Type: new Abstract: Hip exoskeletons provide an important hardware basis for lower-limb rehabilitation and locomotor assistance. Laboratory rehabilitation assessment and sy
arXiv:2609.26539v1 Announce Type: new Abstract: Large language models (LLMs) have increasingly been used to investigate how children acquire syntax at an early stage of development. This is notably th
arXiv:2609.26218v1 Announce Type: cross Abstract: Structural graph analysis of the academic publishing network captures the topological relationships between entities but does not see the content of w
arXiv:2609.26527v1 Announce Type: new Abstract: When two texts describe the same expression, standard metrics based on lexical overlap or whole-text similarity may fail to detect meaningful difference
arXiv:2609.26679v1 Announce Type: new Abstract: In grokking an early fit to the training data separates from a much later improvement in generalization. During this delay, training can move from a fix
arXiv:2609.22695v1 Announce Type: new Abstract: The term 'linear representation hypothesis' (LRH) has appeared across diverse subfields of artificial intelligence, neuroscience, and cognitive science.
arXiv:2609.26237v1 Announce Type: cross Abstract: We present the ABAI submission to COLIEE 2026 Task 1, case law retrieval, together with a controlled study of why it underperformed. The task suppress
arXiv:2609.25624v1 Announce Type: cross Abstract: Large language model (LLM) outputs are expected to be reproducible under greedy decoding, yet in practice the same model, prompt, and software stack p
arXiv:2609.23989v1 Announce Type: new Abstract: Building general-purpose agents for industrial deployment requires integrating multiple capabilities, each typically acquired at a distinct stage of tra
arXiv:2609.26085v1 Announce Type: new Abstract: Inspired by the flight and song of birds, we propose an approach that enables cooperating agents to effectively identify obstacles in their environment
arXiv:2609.24446v2 Announce Type: cross Abstract: Large language model (LLM) agents increasingly execute long-horizon workflows through external tools, allowing untrusted outputs to influence subseque
arXiv:2609.26167v1 Announce Type: new Abstract: Activation-energy pruning -- removing weights whose product of magnitude and cumulative pre-synaptic spike count falls below a threshold -- was establis
arXiv:2504.20106v4 Announce Type: replace Abstract: Ensuring that large language models (LLMs) are both helpful and harmless is a critical challenge, as overly strict constraints can lead to excessive
arXiv:2508.05229v2 Announce Type: replace-cross Abstract: EEG based multi-dimension emotion recognition has attracted substantial research interest in affective computing. However, the high dimensiona
arXiv:2609.26781v1 Announce Type: new Abstract: A multi-agent system can reduce latency on complex tasks by executing work concurrently. Several pioneering harness frameworks support multi-agent syste
arXiv:2511.16043v2 Announce Type: replace Abstract: Large Language Model (LLM) Agents, often trained with Reinforcement Learning (RL), are constrained by a dependency on human-curated data, limiting s
arXiv:2609.23512v1 Announce Type: new Abstract: Large language model agents are typically deployed with predefined configurations, although the required model capability, context, tools, permissions,
arXiv:2609.25578v1 Announce Type: new Abstract: Urban-scale 3D reconstruction from satellite imagery supports disaster response, city monitoring, and geospatial digital twins, yet neural rendering met
arXiv:2512.21066v4 Announce Type: replace Abstract: Explainable artificial intelligence (XAI) reveals how explanatory variables relate to a response variable, yet communicating XAI outputs to layperso
arXiv:2609.23953v1 Announce Type: new Abstract: AI agents that carry a multi-step computer task through on their own became ordinary tools in the past year, and the same autonomy is available to anyon
arXiv:2609.22512v1 Announce Type: new Abstract: Consensus among LLM judges is often taken as strong evidence that a decision is correct. This assumes that judges make their errors independently. In pr
arXiv:2609.25725v1 Announce Type: new Abstract: Agricultural robotics is advancing rapidly, yet progress remains constrained by limited field access, lack of control over field conditions, geographic
arXiv:2609.25047v1 Announce Type: new Abstract: Autonomous agents that automatically build artificial intelligence (AI) models could broaden access to AI across science and engineering. A popular line
arXiv:2609.26274v1 Announce Type: new Abstract: The rapid evolution of generative AI (e.g., Sora, Hunyuan) makes it essential to develop effective detection strategies that can generalize across ever-
arXiv:2609.25088v1 Announce Type: cross Abstract: Survival prediction for glioblastoma multiforme (GBM) demands models that are both accurate and interpretable, yet existing approaches treat these obj
arXiv:2609.25961v1 Announce Type: new Abstract: Generative visual models offer a foundation for learning representations of physical dynamics, yet their extension to continuous control raises a fundam
arXiv:2609.25634v1 Announce Type: new Abstract: We trained 64 independently seeded networks in four configurations, continuing each to sustained convergence or a 40,000-epoch ceiling. We then asked wh
arXiv:2609.22207v1 Announce Type: cross Abstract: High-rate neural telemetry requires an implant-towearable link whose circuit partition, waveform mapping, packet processing, and failure semantics are
arXiv:2609.25374v1 Announce Type: new Abstract: Human gait in reality extends beyond straight-line walking, with some situations even requiring drastic back-and-forth rotations. A smooth and stable ex
arXiv:2609.24644v1 Announce Type: cross Abstract: As people turn to generative AI for financial advice, these systems can personalize how they communicate and what they say. Whether these forms of per
arXiv:2609.25731v1 Announce Type: new Abstract: Medium-resolution (10-30 m) burned area mapping is vital for monitoring wildfires and their impacts, but remains difficult to scale. Existing methods re
arXiv:2609.24165v1 Announce Type: new Abstract: Synchrotron data reduction, detector calibration followed by azimuthal integration of terabyte-scale diffraction series, is a multi-step, expert-bound b