5 papers
CR-Seg: Attention-Guided and CoT-Enhanced Coarse-to-Refined Reasoning Segmentation
Yifan Cao, Xiaocui Yang, Faxian Wan +3
Reasoning segmentation aims to segment target objects described by complex language through joint visual-textual reasoning. Existing methods typically rely on either learned semant…
T-COL: Generating Counterfactual Explanations for General User Preferences on Variable Machine Learning Systems
Ming Wang, Daling Wang, Wenfang Wu +2
To address the interpretability challenge in machine learning (ML) systems, counterfactual explanations (CEs) have emerged as a promising solution. CEs are unique as they provide w…
Affective Computing in the Era of Large Language Models: A Survey from the NLP Perspective
Yiqun Zhang, Xiaocui Yang, Xingle Xu +8
Affective Computing (AC) integrates computer science, psychology, and cognitive science to enable machines to recognize, interpret, and simulate human emotions across domains such…
Generative Emotion Cause Explanation in Multimodal Conversations
Lin Wang, Xiaocui Yang, Shi Feng +3
Multimodal conversation, a crucial form of human communication, carries rich emotional content, making the exploration of the causes of emotions within it a research endeavor of si…
Pixel-Level Reasoning Segmentation via Multi-turn Conversations
Dexian Cai, Xiaocui Yang, Yongkang Liu +4
Existing visual perception systems focus on region-level segmentation in single-turn dialogues, relying on complex and explicit query instructions. Such systems cannot reason at th…