Papers › LININ: Logic Integrated Neural Inference Network for Explanatory Visual Question Answering
LININ: Logic Integrated Neural Inference Network for Explanatory Visual Question Answering
Dizhan Xue, Shengsheng Qian, Quan Fang, Changsheng Xu
Explanatory Visual Question Answering (EVQA) is a recently proposed multimodal reasoning task consisting of answering the visual question and generating multimodal explanations for the reasoning processes. Unlike traditional Visual Question Answering (VQA) task that only aims at predicting answers for visual questions, EVQA also aims to generate userfriendly explanations to improve the explainability and credibility of reasoning models. To date, existing methods for VQA and EVQA ignore the prompt in the question and enforce the model to predict the probabilities of all answers. Moreover, existing EVQA methods ignore the complex relationships among question words, visual regions, and explanation tokens. Therefore, in this work, we propose a Logic Integrated Neural Inference Network (LININ) to restrict the range of candidate answers based on first-order-logic (FOL) and capture cross-modal relationships to generate rational explanations. Firstly, we design a FOLbased question analysis program to fetch a small number of candidate answers. Secondly, we utilize a multimodal transformer encoder to extract visual and question features, and conduct the prediction on candidate answers. Finally, we design a multimodal explanation transformer to construct cross-modal relationships and generate rational explanations. Comprehensive experiments on benchmark datasets demonstrate the superiority of LININ compared with the state-of-the-art methods for EVQA.
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.
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