Knowledge catalogue
arXiv:2607.12122v1 Announce Type: new Abstract: We present an agentic approach to autonomous neural operator discovery based on an AI scientific community, which consists of a swarm of virtual laborat
arXiv:2607.12048v1 Announce Type: cross Abstract: Deploying medical visual question answering (MedVQA) systems in real-world clinical settings requires models that adapt to new clinical tasks without
arXiv:2607.12468v1 Announce Type: cross Abstract: We describe our submission to Task 1 of the 2nd MLCSLM Challenge: a cascaded diarization-then-recognition system that combines DiariZen-Large-s80 (Wav
arXiv:2607.12054v1 Announce Type: cross Abstract: Breast ultrasound is widely used for screening, yet automated analysis remains challenging due to speckle noise, acquisition variability, and weak sep
arXiv:2607.11987v1 Announce Type: new Abstract: Perineural invasion (PNI) is associated with poor postoperative outcomes in intrahepatic cholangiocarcinoma, but it is confirmed by surgical pathology.
arXiv:2607.07652v1 Announce Type: cross Abstract: Search engines have long allocated attention on the web by routing users from queries to websites. AI search changes this arrangement because informat
arXiv:2603.08862v2 Announce Type: replace-cross Abstract: Autonomous navigation in highly constrained environments remains challenging for mobile robots. Classical navigation approaches offer safety a
arXiv:2607.11997v1 Announce Type: cross Abstract: Multi-task model merging combines separately trained expert models into a single model that handles all tasks without co-training. Standard practice m
arXiv:2607.13013v1 Announce Type: new Abstract: Automatic speech recognition is dominated by autoregressive decoders that emit one token at a time. We ask whether a discrete diffusion language model c
LLMs handle speech well once you run speech-to-text. They don't hear the rest: a bird outside, a glass breaking two rooms away, a smoke alarm two floors down. I've been working on an experimental open
arXiv:2511.23276v2 Announce Type: replace Abstract: Effective HFMD surveillance requires forecasts capturing both time-series patterns and contextual drivers such as school calendars, weather, and pol
arXiv:2607.10183v2 Announce Type: replace-cross Abstract: Running large language models on consumer devices such as laptops and desktops is challenging because model weights often exceed GPU memory ca
arXiv:2607.11943v1 Announce Type: cross Abstract: Long-horizon physics-based simulations of battery degradation provide mechanistic insight but remain computationally expensive, limiting their use for
arXiv:2607.12383v1 Announce Type: new Abstract: Cancer-related discussions on social media provide an important space for information exchange and peer support, but also facilitate the spread of misin
arXiv:2607.12214v1 Announce Type: new Abstract: Reconstructing 4D driving scenes in the wild (e.g., internet and AI-generated videos) is critical for diverse autonomous driving simulation. While recen
arXiv:2607.12818v1 Announce Type: new Abstract: Visual place recognition (VPR) is a key enabler of accurate localization and long-term autonomous navigation in robotics applications, such as loop clos
arXiv:2607.11263v2 Announce Type: replace Abstract: Two competing perspectives on fluid intelligence (gf) measures propose that performance is primarily constrained either by working memory capacity o
Built partnered with the AWS Generative AI Innovation Center (GenAIIC), AWS Partner AND Digital, and AWS account teams to create a scalable, AI-powered document processing engine that can classify, sp
arXiv:2607.12556v1 Announce Type: new Abstract: Weakly supervised whole-slide image (WSI) classification is widely used in computational pathology because slide-level labels are easier to obtain than
arXiv:2607.12857v1 Announce Type: cross Abstract: A generated rhythm-game chart need not reproduce one official note sequence: many note choices can fit the same song and difficulty. Reference-note ag
arXiv:2607.12193v1 Announce Type: cross Abstract: While generative AI has unlocked new opportunities for 3D content creation, current workflows often rely on multiple regenerations, which provides lim
arXiv:2607.12763v1 Announce Type: cross Abstract: Federated Reinforcement Learning (FedRL) enables coordination of distributed energy resources without sharing raw local data, but standard aggregation
arXiv:2506.08121v2 Announce Type: replace-cross Abstract: We introduce a continuous policy-value iteration algorithm where the approximations of the value function of a stochastic control problem and
arXiv:2607.12220v1 Announce Type: new Abstract: Synthesizing deployable robot behavior trees (BTs) from natural language (NL) requires grounding to ensure every generated BT references only skills a r
arXiv:2607.11962v1 Announce Type: new Abstract: Self-supervised learning offers a compelling approach for medical imaging, where labeled data are scarce and acquisition costs are high. We present COJE
arXiv:2607.12165v1 Announce Type: new Abstract: Recently, the societal implementation of high-performance image classification models has expanded rapidly. While these models require vast amounts of t
arXiv:2602.11198v2 Announce Type: replace-cross Abstract: Multi-agent frameworks (MAFs) promise to simplify LLM-driven software development, yet no principled metric captures how well AI coding assist
arXiv:2607.12602v1 Announce Type: new Abstract: Automatic voxel-level grounding of free-text findings in 3D chest Computed Tomography (CT) is critical for clinical interpretability. However, this task
arXiv:2607.12868v1 Announce Type: cross Abstract: Deep learning systems often fail due to subtle implementation faults that alter training behavior. Recent work has studied how to detect and diagnose
arXiv:2509.21842v2 Announce Type: replace Abstract: Travel planning (TP) agent has recently worked as an emerging building block to interact with external tools/resources for travel itinerary generati
arXiv:2607.13033v1 Announce Type: new Abstract: Reinforcement learning holds great promise for improving robot policies beyond the limits of imitation learning. However, its practical adoption remains
arXiv:2607.12265v1 Announce Type: new Abstract: Radar sensing is increasingly used in mobile systems because it operates reliably under poor lighting, adverse weather, and privacy-sensitive settings w
arXiv:2607.12784v1 Announce Type: cross Abstract: Reinforcement Learning has revolutionized the landscape of robotic research, allowing robust learning of complex robotic skills in simulation. However
arXiv:2607.12934v1 Announce Type: new Abstract: Remote sensing change detection (RSCD) models are prone to catastrophic forgetting when incrementally adapted to new domains. Existing domain-incrementa
arXiv:2607.12095v1 Announce Type: cross Abstract: Sensor-rich data-driven applications increasingly use Bayesian approaches to infer latent states of dynamic systems from noisy sensor measurements and
arXiv:2607.12544v1 Announce Type: new Abstract: Thermal infrared (TIR) imaging is essential for UAV swarm operations in visually degraded environments. However, tracking tiny UAVs remains challenging
arXiv:2509.15120v2 Announce Type: replace Abstract: In high-stakes scenarios, such as medical imaging applications, it is critical to equip the predictions of a regression model with reliable confiden
arXiv:2607.12527v1 Announce Type: new Abstract: Musculoskeletal diseases are among the leading causes of disability worldwide and create the greatest global need for rehabilitation. Because recovery,
arXiv:2509.22415v3 Announce Type: replace-cross Abstract: Multimodal large language models (MLLMs) have achieved strong vision-language performance, yet their token-level visual evidence remains diffi
arXiv:2607.12455v1 Announce Type: new Abstract: Quantitative strategy optimization remains largely manual, requiring domain experts to identify weak signals, tune risk-control rules, and repeatedly va
arXiv:2607.11956v1 Announce Type: cross Abstract: Data Shapley is the standard principled answer to which training points are worth what, and its k-nearest-neighbor (KNN) specialization is the version
arXiv:2603.05842v2 Announce Type: replace Abstract: Reinforcement learning has demonstrated significant potential in the field of autonomous driving. However, it suffers from defects such as training
arXiv:2607.12454v1 Announce Type: new Abstract: Multivariate Time Series Anomaly Detection (MTSAD) is essential for reliability and safety in domains such as industrial process monitoring and financia
arXiv:2607.12215v1 Announce Type: new Abstract: Accurately assessing personality from text is challenging because traits are latent, context-dependent, and often subtly expressed across long narrative
arXiv:2607.11588v2 Announce Type: replace Abstract: We present FoundationGeo, a two-stage framework that explicitly bridges relative and metric prediction via spatial calibration and principled data d
arXiv:2607.12175v1 Announce Type: cross Abstract: X-ray tomography enables nondestructive characterization of material microstructures, while advances in micro-CT imaging have accelerated volumetric d
arXiv:2606.20751v2 Announce Type: replace Abstract: Advanced Air Mobility (AAM) is an emerging low-altitude transportation system whose successful deployment depends on both technological progress and
arXiv:2607.11892v1 Announce Type: cross Abstract: Human-factor event diagnosis is essential for learning from operational events in nuclear power plants, yet its quality depends strongly on expert int
arXiv:2607.11978v1 Announce Type: cross Abstract: Precision molecular design aims to discover personalized drug candidates through joint control of multiple conditions, such as biological relevance an
arXiv:2603.13421v2 Announce Type: replace-cross Abstract: Generative models based on the Flow Matching objective, particularly Rectified Flow, have emerged as a dominant paradigm for efficient, high-f
Generic AI models are not built for medicine. Doximity Ask, trained and served on Fireworks, outperformed GPT-5.6 Sol, Claude Fable 5, and OpenEvidence in a Stanford-Harvard clinical AI safety study.
arXiv:2607.12284v1 Announce Type: new Abstract: Image geolocation aims to infer the geographic origin of an image from visual content alone. However, this task remains challenging in regions where cou
arXiv:2607.09224v2 Announce Type: replace-cross Abstract: Version control systems are essential for collaborative software development, yet tools like git remain challenging for many practitioners. Re
arXiv:2607.12626v1 Announce Type: cross Abstract: Closed-loop wall control learnt by multi-agent reinforcement learning can lower skin-friction drag in turbulent channels, but these gradient-based pol
arXiv:2607.11954v1 Announce Type: cross Abstract: Clinical code prediction maps unstructured discharge summaries to ICD-10-CM leaf codes in a large, sparse, and deeply hierarchical label space. Most s
arXiv:2601.10199v2 Announce Type: replace Abstract: Multivariate data often exhibit complex dependencies that violate the assumption of isotropic residual noise. For such cases, we introduce Graph Reg
arXiv:2607.12752v1 Announce Type: cross Abstract: While recent advances in 3D generation have enabled impressive visual synthesis, existing methods often rely on 2D diffusion supervision without expli
Deploying the Gemini Enterprise app across an organization marks a transformative leap forward in workforce productivity, providing employees with an amazing, high-performance suite of agentic AI tool
arXiv:2607.11893v1 Announce Type: cross Abstract: Large Language Models (LLMs) perform strongly on many language tasks, but their capability in structurally constrained, accessibility-critical modalit
arXiv:2509.24863v2 Announce Type: replace Abstract: Deep neural networks surpass humans on many vision benchmarks, yet remain far less robust to distribution shifts such as illumination and weather ch