9 citations · 11 across the 6 of their papers we have counts for
6 papers
MATEval: A Multi-Agent Discussion Framework for Advancing Open-Ended Text Evaluation
Yu Li, Shenyu Zhang, Rui Wu +5
Recent advancements in generative Large Language Models(LLMs) have been remarkable, however, the quality of the text generated by these models often reveals persistent issues. Eval…
DEE: Dual-stage Explainable Evaluation Method for Text Generation
Shenyu Zhang, Yu Li, Rui Wu +4
Automatic methods for evaluating machine-generated texts hold significant importance due to the expanding applications of generative systems. Conventional methods tend to grapple w…
MIKE: A New Benchmark for Fine-grained Multimodal Entity Knowledge Editing
Jiaqi Li, Miaozeng Du, Chuanyi Zhang +6
Multimodal knowledge editing represents a critical advancement in enhancing the capabilities of Multimodal Large Language Models (MLLMs). Despite its potential, current benchmarks…
Exploring the Impact of Table-to-Text Methods on Augmenting LLM-based Question Answering with Domain Hybrid Data
Dehai Min, Nan Hu, Rihui Jin +8
Augmenting Large Language Models (LLMs) for Question Answering (QA) with domain specific data has attracted wide attention. However, domain data often exists in a hybrid format, in…
Incorporating Domain Knowledge Graph into Multimodal Movie Genre Classification with Self-Supervised Attention and Contrastive Learning
Jiaqi Li, Guilin Qi, Chuanyi Zhang +4
Multimodal movie genre classification has always been regarded as a demanding multi-label classification task due to the diversity of multimodal data such as posters, plot summarie…
Parameterizing Context: Unleashing the Power of Parameter-Efficient Fine-Tuning and In-Context Tuning for Continual Table Semantic Parsing
Yongrui Chen, Shenyu Zhang, Guilin Qi +1
Continual table semantic parsing aims to train a parser on a sequence of tasks, where each task requires the parser to translate natural language into SQL based on task-specific ta…