IE-MAS: Internal-External Multi-Agent Steering for Controllable Image Captioning
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View abstract on PubMed
Summary
This summary is machine-generated.This study introduces Internal-External Multi-Agent Steering (IE-MAS) to improve Controllable Image Captioning (CIC). IE-MAS effectively manages multiple constraints like length and sentiment for better image descriptions.
Area Of Science
- Artificial Intelligence
- Computer Vision
- Natural Language Processing
Background
- Controllable Image Captioning (CIC) aims to generate image descriptions adhering to specific user constraints.
- Existing methods struggle to simultaneously satisfy multiple constraints due to interference.
- Challenges include balancing semantic faithfulness, affective expression, and length control.
Purpose Of The Study
- To propose a novel method, Internal-External Multi-Agent Steering (IE-MAS), for addressing the limitations of current CIC approaches.
- To enable the generation of image captions that satisfy multiple, potentially interacting, constraints.
- To improve the coherence, faithfulness, and expressiveness of generated captions.
Main Methods
- IE-MAS employs an internal multimodal steering (IMS) strategy for affective coherence control.
- An external multi-agent collaboration system (EMCS) is utilized for visual grounding and contextual alignment.
- The approach balances internal linguistic control and external perceptual grounding via adaptive steering.
Main Results
- IE-MAS effectively coordinates multiple constraints in image caption generation.
- Generated captions satisfy length constraints while being sentimentally expressive and visually faithful.
- The method demonstrates improved performance in balancing semantic consistency, affective expression, and length control.
Conclusions
- IE-MAS offers a robust solution for multi-constraint Controllable Image Captioning.
- The proposed IMS and EMCS strategies successfully manage complex control interactions.
- This work advances the state-of-the-art in generating contextually relevant and stylistically controlled image descriptions.
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