This paper investigates whether adults' struggles with conjunctive causal rules persist when they have agency through active exploration.

The paper introduces ActiveVision, a benchmark to measure active observation in multimodal large language models, and shows that current models lack robust active visual perception.

This paper provides a detailed message-passing scheme for EFE-based planning and clarifies the corrections needed for cross-entropy planning and full EFE-based planning.

A hybrid active-online learning framework is proposed for label-efficient concept drift adaptation in optical network failure detection, achieving high accuracy and AUC scores with minimal samples and…

The paper introduces PInVerify, an offline embodied benchmark for Active Instance Verification (AIV), a task requiring agents to actively select viewpoints to confirm if a candidate object matches a f…

This paper analyzes interaction data from touch-enabled exhibits at a science center to derive a behavioral signature called interaction density and uses it to distinguish between fast-paced games and…

The paper introduces MOV-Bench, a challenging benchmark for multi-hop audio-visual reasoning, and proposes AOP-Agent, an agentic framework that significantly improves open-source Omni-LLMs' ability to…

The paper proposes using geometric metrics, specifically eigenspace alignment, to monitor the structural integrity of large behavioral populations, demonstrating its effectiveness in detecting network…

This paper introduces ATLAS, an active learning framework for discovering interpretable behavioral models in cognitive science.

The paper introduces CAFOSat, a large-scale, strongly annotated, and infrastructure-aware dataset designed to improve the accuracy of mapping Concentrated Animal Feeding Operations (CAFOs) from high-r…

This paper proposes a novel volumetric change detection sub-task for monitoring slope instabilities using time-lapse cameras, demonstrating that dense and semi-dense feature matching techniques are ro…

The paper proposes a novel active learning framework using Linearized Optimal Transport to strategically select measurement timepoints, thereby minimizing uncertainty when inferring continuous probabi…

The paper introduces TeachObs, a comprehensive, human-validated benchmark for multimodal teaching observation, and evaluates frontier LLMs, finding that no single model consistently outperforms others…

The paper proposes a decentralized, privacy-aware framework enabling smart cameras to autonomously coordinate their view coverage in public spaces while explicitly excluding sensitive regions, achievi…

A-Live is a passive liveness detection framework that uses subtle neuromuscular micro-motion signatures captured by commodity IMU sensors to distinguish human users from non-human agents with high acc…

This paper proposes a simple real-time monitor for LLMs that turns an external verifier signal into an alarm decision by thresholding, showing competitiveness with advanced monitors in mathematical re…

This paper demonstrates that fusing multi-viewpoint data from multiple satellites significantly enhances the accuracy of space object detection in congested LEO constellations, establishing multi-view…

SAFARI is a framework that decouples diagnostic accuracy from context limits in autonomous agents by equipping them with a toolbox to read and search trajectory segments and a persistent STM for cross…