32 citations · 63 across the 64 of their papers we have counts for
5 papers · 1 filter
MM-BigBench: Evaluating Multimodal Models on Multimodal Content Comprehension Tasks
Xiaocui Yang, Wenfang Wu, Shi Feng +7
The popularity of multimodal large language models (MLLMs) has triggered a recent surge in research efforts dedicated to evaluating these models. Nevertheless, existing evaluation…
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…
RoCar: A Relationship Network-based Evaluation Method for Large Language Models
Ming Wang, Wenfang Wu, Chongyun Gao +3
Large language models (LLMs) have received increasing attention. However, due to the complexity of its capabilities, how to rationally evaluate the capabilities of LLMs is still a…
Few-shot Joint Multimodal Aspect-Sentiment Analysis Based on Generative Multimodal Prompt
Xiaocui Yang, Shi Feng, Daling Wang +5
We have witnessed the rapid proliferation of multimodal data on numerous social media platforms. Conventional studies typically require massive labeled data to train models for Mul…
Evaluate What You Can't Evaluate: Unassessable Quality for Generated Response
Yongkang Liu, Shi Feng, Daling Wang +2
LLMs (large language models) such as ChatGPT have shown remarkable language understanding and generation capabilities. Although reference-free evaluators based on LLMs show better…