20 citations · 37 across the 7 of their papers we have counts for
7 papers
MLDebugging: Towards Benchmarking Code Debugging Across Multi-Library Scenarios
Jinyang Huang, Xiachong Feng, Qiguang Chen +6
Code debugging is a crucial task in software engineering, which attracts increasing attention. While remarkable success has been made in the era of large language models (LLMs), cu…
CoMT: A Novel Benchmark for Chain of Multi-modal Thought on Large Vision-Language Models
Zihui Cheng, Qiguang Chen, Jin Zhang +5
Large Vision-Language Models (LVLMs) have recently demonstrated amazing success in multi-modal tasks, including advancements in Multi-modal Chain-of-Thought (MCoT) reasoning. Despi…
What Factors Affect Multi-Modal In-Context Learning? An In-Depth Exploration
Libo Qin, Qiguang Chen, Hao Fei +3
Recently, rapid advancements in Multi-Modal In-Context Learning (MM-ICL) have achieved notable success, which is capable of achieving superior performance across various tasks with…
AutoCAP: Towards Automatic Cross-lingual Alignment Planning for Zero-shot Chain-of-Thought
Yongheng Zhang, Qiguang Chen, Min Li +2
Cross-lingual chain-of-thought can effectively complete reasoning tasks across languages, which gains increasing attention. Recently, dominant approaches in the literature improve…
Large Language Models Meet NLP: A Survey
Libo Qin, Qiguang Chen, Xiachong Feng +6
While large language models (LLMs) like ChatGPT have shown impressive capabilities in Natural Language Processing (NLP) tasks, a systematic investigation of their potential in this…
Multilingual Large Language Model: A Survey of Resources, Taxonomy and Frontiers
Libo Qin, Qiguang Chen, Yuhang Zhou +6
Multilingual Large Language Models are capable of using powerful Large Language Models to handle and respond to queries in multiple languages, which achieves remarkable success in…
End-to-end Task-oriented Dialogue: A Survey of Tasks, Methods, and Future Directions
Libo Qin, Wenbo Pan, Qiguang Chen +5
End-to-end task-oriented dialogue (EToD) can directly generate responses in an end-to-end fashion without modular training, which attracts escalating popularity. The advancement of…