68 citations · 71 across the 7 of their papers we have counts for
7 papers
CofiPara: A Coarse-to-fine Paradigm for Multimodal Sarcasm Target Identification with Large Multimodal Models
Hongzhan Lin, Zixin Chen, Ziyang Luo +3
Social media abounds with multimodal sarcasm, and identifying sarcasm targets is particularly challenging due to the implicit incongruity not directly evident in the text and image…
BehAVExplor: Behavior Diversity Guided Testing for Autonomous Driving Systems
Mingfei Cheng, Yuan Zhou, Xiaofei Xie
Testing Autonomous Driving Systems (ADSs) is a critical task for ensuring the reliability and safety of autonomous vehicles. Existing methods mainly focus on searching for safety v…
A Unified Contrastive Transfer Framework with Propagation Structure for Boosting Low-Resource Rumor Detection
Hongzhan Lin, Jing Ma, Ruichao Yang +2
The truth is significantly hampered by massive rumors that spread along with breaking news or popular topics. Since there is sufficient corpus gathered from the same domain for mod…
A Joint Framework Towards Class-aware and Class-agnostic Alignment for Few-shot Segmentation
Kai Huang, Mingfei Cheng, Yang Wang +4
Few-shot segmentation (FSS) aims to segment objects of unseen classes given only a few annotated support images. Most existing methods simply stitch query features with independent…
Detect Rumors in Microblog Posts for Low-Resource Domains via Adversarial Contrastive Learning
Hongzhan Lin, Jing Ma, Liangliang Chen +3
Massive false rumors emerging along with breaking news or trending topics severely hinder the truth. Existing rumor detection approaches achieve promising performance on the yester…
Rumor Detection on Twitter with Claim-Guided Hierarchical Graph Attention Networks
Hongzhan Lin, Jing Ma, Mingfei Cheng +3
Rumors are rampant in the era of social media. Conversation structures provide valuable clues to differentiate between real and fake claims. However, existing rumor detection metho…