Knowledge catalogue
arXiv:2606.01640v1 Announce Type: new Abstract: Human mobility generation aims to synthesize realistic trip chains for target populations based on individual features. Existing paradigms, including de
arXiv:2606.00844v1 Announce Type: cross Abstract: Bounding-box regression is a fundamental component of object detection, playing a critical role in precise object localization. Existing Intersection-
arXiv:2606.02491v1 Announce Type: new Abstract: We present MORPHOS, a novel autoregressive framework that generates dynamic 3D assets from videos across diverse representations, including meshes, 3D G
arXiv:2606.01846v1 Announce Type: new Abstract: Mosquito-borne infectious diseases cause more than 700000 deaths worldwide each year. The long-term use of conventional chemical insecticides has induce
arXiv:2601.22900v2 Announce Type: replace Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) is widely used to improve reasoning across domains, but outcome-only scalar rewards are often
arXiv:2606.02352v1 Announce Type: new Abstract: Robust self-supervised learning of multi-modal video representations is critical for real-world applications such as driver distraction detection, where
arXiv:2512.07806v2 Announce Type: replace Abstract: We propose Multi-view Pyramid Transformer (MVP), a scalable multi-view transformer architecture that directly reconstructs large 3D scenes from tens
arXiv:2601.16884v3 Announce Type: replace Abstract: We study multigrade deep learning (MGDL) as a principled framework for structured error refinement in deep neural networks. While the approximation
arXiv:2606.01483v1 Announce Type: cross Abstract: Long-form automatic speech recognition (ASR) requires both high accuracy and low latency, but existing systems force a trade-off between the two. Chun
arXiv:2606.01084v1 Announce Type: cross Abstract: Combinatorial routing problems such as the Traveling Salesman Problem (TSP) and the Capacitated Vehicle Routing Problem (CVRP) are fundamental NP-hard
arXiv:2606.00174v1 Announce Type: cross Abstract: Electromyography (EMG) directly reflects muscle activation and is a key sensing modality for gesture recognition, prosthetic control, and wearable int
arXiv:2510.14025v2 Announce Type: replace Abstract: Adversarial purification has achieved great success in combating adversarial image perturbations, which are usually assumed to be additive. However,
arXiv:2606.00809v1 Announce Type: new Abstract: Many real-world conversational settings for knowledge discovery, including podcasts, hiring screens, and marketplaces, require a purpose-driven understa
arXiv:2606.01364v1 Announce Type: cross Abstract: The attack surface of a modern operating system is a haystack: thousands of signed binaries and millions of functions, almost none relevant to any giv
arXiv:2602.17737v2 Announce Type: replace-cross Abstract: Mutual adaptation is a central challenge in human-AI teaming, as humans naturally adjust their strategies in response to an AI agent's behavio
arXiv:2606.02292v1 Announce Type: new Abstract: We present a method to acquire and estimate the sub-surface scattering properties of light transport at a highly detailed level by learning the pixel fo
arXiv:2606.00557v1 Announce Type: new Abstract: To understand how a neural network (NN) functions and makes predictions, it has become increasingly clear that analyzing only the input domain is insuff
arXiv:2511.20409v2 Announce Type: replace Abstract: Text normalization methods such as stemming and lemmatization are fundamental components of NLP pipelines. As new normalization tools are developed
arXiv:2606.01839v1 Announce Type: cross Abstract: LLM-based agents resolve a user task through many turns of dependent inference and tool calls, producing a workload whose total cost is unknown when t
arXiv:2606.02433v1 Announce Type: cross Abstract: The rapid development of LLMs has significantly advanced tabular question answering, but most systems cannot perform future-oriented numerical predict
arXiv:2602.22101v3 Announce Type: replace-cross Abstract: Many real-world applications generate continuous data streams for regression. Hoeffding trees and their variants have a long-standing traditio
arXiv:2602.09474v2 Announce Type: replace Abstract: We study reinforcement learning in MDPs whose transition function is stochastic at most steps but may behave adversarially at a fixed subset of Lamb
arXiv:2606.01399v1 Announce Type: new Abstract: We present PAI-Studio, a new reference-conditioned video synthesis task that addresses a long-standing challenge in cinematic background replacement: ge
arXiv:2606.01192v1 Announce Type: new Abstract: Evaluating the performance of visual perception systems for autonomous driving is essential to ensure reliable operation across diverse environmental sc
arXiv:2602.12080v2 Announce Type: replace Abstract: Despite recent advances in AI, event data collection in soccer still relies heavily on labor-intensive manual annotation. Although prior work has ex
arXiv:2606.01188v1 Announce Type: cross Abstract: Translating natural-language hardware requirements into correct printed circuit board (PCB) schematics remains difficult in embedded, IoT, and wearabl
arXiv:2606.01649v1 Announce Type: new Abstract: Generating physically consistent 3D tabletop scenes is a fundamental yet underexplored problem for interactive and generalist robotic learning. The chal
arXiv:2606.01894v1 Announce Type: new Abstract: Accurate Remaining Useful Life prediction is critical for industrial predictive maintenance. However, real-world deployment is challenging due to the ir
arXiv:2606.01757v1 Announce Type: new Abstract: Real-time 3D object detection is a critical component for the safe operation of autonomous driving systems and robotics. While LiDAR point clouds provid
arXiv:2606.01572v1 Announce Type: cross Abstract: Predicting patient-specific facial soft-tissue deformation is critical for iterative orthognathic surgery planning. However, current computational met
arXiv:2606.02481v1 Announce Type: new Abstract: Large image datasets have accelerated progress in cognitive neuroscience and computer vision. However, most datasets are low-resolution, internet-source
arXiv:2606.02010v1 Announce Type: cross Abstract: PlanarBench tests whether LLMs can draw planar graphs as ASCII art given only an edge list -- a spatial reasoning task that resists memorization becau
arXiv:2606.01788v1 Announce Type: new Abstract: Embodied visual navigation, where an agent perceives a complex environment and acts to reach a goal from raw sensory input, underpins a wide range of ap
arXiv:2606.01042v1 Announce Type: cross Abstract: Perturbation experiments are central to understanding cellular mechanisms, but remain costly and sparse, motivating prediction of gene expression resp
arXiv:2606.01920v1 Announce Type: new Abstract: Diffusion-based dataset distillation has recently emerged as a promising paradigm for condensing large-scale datasets into compact synthetic sets. By le
arXiv:2508.08337v3 Announce Type: replace-cross Abstract: Algorithmic fairness research has largely framed unfairness as discrimination along sensitive attributes. However, this approach limits visibi
arXiv:2606.00124v1 Announce Type: new Abstract: Positional embeddings (PEs) in Vision Transformers (ViTs) are known to impact performance and robustness, but their role in shaping internal spatial rep
arXiv:2606.02366v1 Announce Type: new Abstract: We present PRIMA (*PRI*ors for *M*esh *A*daptation), a framework for robust 3D quadruped mesh recovery under severe species and pose imbalance. Existing
arXiv:2606.02117v1 Announce Type: cross Abstract: Probabilistic time series forecasting has attracted increasing attention in financial applications due to the need to quantify risk and uncertainty in
arXiv:2606.01012v1 Announce Type: new Abstract: AI for materials science is a critical topic within AI for science, aiming to accelerate materials discovery and produce accurate property predictions.
arXiv:2606.00970v1 Announce Type: new Abstract: We study risk-neutral control in Markov decision processes with an absorbing catastrophic state. Even though rewards are linear and the agent has no uti
arXiv:2606.02008v1 Announce Type: cross Abstract: Pre-training has become a fundamental paradigm in modern machine learning, with one of its key empirical benefits being reduced downstream sample comp
arXiv:2601.22813v2 Announce Type: replace Abstract: The NVFP4 lower-precision format, supported in hardware by NVIDIA Blackwell GPUs, promises to allow, for the first time, end-to-end fully-quantized
arXiv:2606.02022v1 Announce Type: cross Abstract: Multi-view object association is an important computer vision problem that underlies many multi-camera perception tasks. While this task is naturally
arXiv:2508.19191v3 Announce Type: replace Abstract: Intraocular foreign body removal demands millimeter-level precision in confined intraocular spaces, yet existing robotic systems predominantly rely
arXiv:2512.18333v2 Announce Type: replace-cross Abstract: This paper proposes a new Reinforcement Learning (RL) based control architecture for quadrotors. With the literature focusing on controlling t
arXiv:2606.00367v1 Announce Type: cross Abstract: Reinforcement learning problems typically define the goal as maximizing the expected value of a scalar reward function. But, pairwise preferences are
arXiv:2606.02328v1 Announce Type: new Abstract: We explore Riemannian optimization techniques for rank-factored matrix parameters, targeting contemporary deep learning applications. We examine ten poi
arXiv:2606.01281v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) has emerged as a powerful paradigm for enhancing the reasoning capabilities of large language mo
arXiv:2602.19126v2 Announce Type: replace Abstract: We propose a robust Bayesian formulation of random feature (RF) regression that accounts explicitly for prior and likelihood misspecification via Hu
arXiv:2602.20807v2 Announce Type: replace Abstract: Combining 3D Gaussian splatting with Simultaneous Localization and Mapping (SLAM) has gained popularity as it enables continuous 3D environment reco
// Scaling Behavior of Single LLM-Driven Multi-Agent Systems // Does adding more agents actually make a multi-agent system better? It's possible that collective intelligence emerges from interaction d
arXiv:2307.05213v3 Announce Type: replace-cross Abstract: Many real-world optimization problems contain parameters that are unknown before deployment time, either due to stochasticity or to lack of in
arXiv:2606.01741v1 Announce Type: cross Abstract: Distributed event-based systems have become a common substrate for Internet-scale publish/subscribe services, IoT telemetry, cloud-native microservice
Seeing Martin Scorsese using FLUX for storyboarding and scene exploration was absolutely insane. Experiencing how one of the absolute masters of cinema & filmmaking uses the technology that we develop
arXiv:2606.00098v1 Announce Type: new Abstract: We introduce segmentation-guided spatial indexing for generalizable and explainable deepfake detection. The key idea reverses the standard design order:
arXiv:2411.17790v3 Announce Type: replace-cross Abstract: Accurate 3D mapping in endoscopy enables quantitative, holistic lesion characterization within the gastrointestinal (GI) tract, requiring reli
arXiv:2606.01746v1 Announce Type: new Abstract: Modern neural networks are highly susceptible to adversarial perturbations. In this work, we identify that part of this vulnerability stems from the sen
arXiv:2606.00688v1 Announce Type: new Abstract: Single-stage fully sparse 3D object detectors rely on point clouds data to detect objects in autonomous driving scenarios. However, the sparsity and inc
arXiv:2512.09065v2 Announce Type: replace-cross Abstract: Many indoor workspaces are quasi-static: their global geometric layout is stable, but local semantics change continually, producing repetitive