Emergent communication via Metropolis-Hastings Naming Game within Collective Predictive Coding produces aligned emotion categories between agents despite divergent interoceptive dynamics.
A coefficient of agreement for nominal scales
6 Pith papers cite this work. Polarity classification is still indexing.
6
Pith papers citing it
citation-role summary
background 1
method 1
citation-polarity summary
verdicts
UNVERDICTED 6representative citing papers
LLM agents make collective belief dynamics programmable, with simulations showing coordinated agents induce stable belief shifts, and four structural properties that complicate detection and defense.
Simulator experiments revealed correlations between steering conflicts, reaction times, and drivers' sense of control in partial automation, highlighting design needs for better intention alignment and intervention ease.
LLM judges for human-AI coding co-creation show moderate performance (ROC-AUC 0.59) and low agreement, with co-creation success concentrating early in interactions.
A systematic review that introduces a framework for feature extraction in remote sensing, traces its evolution in the data value chain, and synthesizes trends toward unified representations and foundation models.
The Sleepal AI Lamp achieves 92.8% accuracy on sleep-wake detection and 78.5% on four-stage classification using radar signals, showing high agreement with PSG on 1022 recordings.
citing papers explorer
-
Emergent Communication for Co-constructed Emotion Between Embodied Agents via Collective Predictive Coding
Emergent communication via Metropolis-Hastings Naming Game within Collective Predictive Coding produces aligned emotion categories between agents despite divergent interoceptive dynamics.
-
LLM Agents Make Collective Belief Dynamics Programmable: Challenges and Research Directions
LLM agents make collective belief dynamics programmable, with simulations showing coordinated agents induce stable belief shifts, and four structural properties that complicate detection and defense.
-
Linking Behaviour and Perception to Evaluate Meaningful Human Control over Partially Automated Driving
Simulator experiments revealed correlations between steering conflicts, reaction times, and drivers' sense of control in partial automation, highlighting design needs for better intention alignment and intervention ease.
-
LLM-as-a-Judge for Human-AI Co-Creation: A Reliability-Aware Evaluation Framework for Coding
LLM judges for human-AI coding co-creation show moderate performance (ROC-AUC 0.59) and low agreement, with co-creation success concentrating early in interactions.
-
Feature Extraction in the Remote Sensing Data Value Chain: A Systematic Review of Methods and Applications
A systematic review that introduces a framework for feature extraction in remote sensing, traces its evolution in the data value chain, and synthesizes trends toward unified representations and foundation models.
-
The Breakthrough of Sleep: A Contactless Approach for Accurate Sleep Stage Detection Using the Sleepal AI Lamp
The Sleepal AI Lamp achieves 92.8% accuracy on sleep-wake detection and 78.5% on four-stage classification using radar signals, showing high agreement with PSG on 1022 recordings.