Papers › iPIC-XAI: Improving PIC-XAI for Enhanced Image Captioning Explanation
iPIC-XAI: Improving PIC-XAI for Enhanced Image Captioning Explanation
Modafar Al-Shouha, Gábor Szűcs
Image captioning task with its complexity has taken advantage of the recent developments in Deep learning (DL). However, DL-models are fundamentally abstruse and explaining their behaviour is a challenge. In this paper we present an algorithm to explain an image captioning model behavior. We enhanced PIC-XAI performance by introducing various components; (1) we utilize CLIP multimodal similarity for more efficiency, (2) we consider the query dependency tag as a clue for elements with bigger size, (3) we provide an algorithm to automatically set the preprocessing blurring kernel size, and (4) we use a similarity comparison technique to get more relevant answers. Additionally, we provide an improved version of XIC metric, aiming for more consistent objective evaluation for XAI methods in image captioning field.
Code
Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.
Code Syntology ran Syntology
Not run by Syntology. Nothing on this page verifies that the listed code works.
Tasks
Results from the paper archive 2025-07-28
No leaderboard rows for this paper in the archive.
Methods
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections