research note
This paper addresses the critical challenge of forecasting future scene states from video sequences for autonomous robotic navigation.
research note
This paper addresses the challenging problem of small object detection (SOD), where limited visual cues and label ambiguity impede accurate localization.
research note
This paper investigates a novel, near-real-time semantic object removal attack targeting video-based perception systems commonly used in intelligent.
research note
This paper addresses the challenges that arise in achieving extremely high precision (better than 0.3%) in accelerator physics experiments, specifically.
research note
KC-Agent addresses the critical challenge of maintaining and improving ML models in production under data drift by introducing a novel dual-process.
research note
This paper addresses a critical gap in AI misuse detection arising from cross-session statelessness in agentic AI deployments.
research note
MedPRESS addresses a critical gap in medical large language model (LLM) evaluation by focusing on patient-pressure-induced sycophancy—where models.
research note
This paper addresses two central challenges in the theory of binary Goppa codes: precisely determining their minimum distances and constructing Goppa.
research note
NeuroInspector addresses the increasing challenges faced by neuroscience researchers in inspecting and understanding large, hierarchical datasets stored.
research note
This paper addresses the limitations of current visual text tampering detectors in handling open-set and unseen forgery patterns enabled by evolving.
research note
Qwen-CUA addresses the challenge of creating large-scale AI agents that can operate native desktop and web software solely through visual input.
research note
RealWeather addresses the challenge of translating driving videos between clear and adverse weather conditions in a way that is both highly realistic and.
