5 citations · 5 across the 3 of their papers we have counts for
3 papers
cs.CL2025
COIG-P: A High-Quality and Large-Scale Chinese Preference Dataset for Alignment with Human Values
P Team, Siwei Wu, Jincheng Ren +29
Aligning large language models (LLMs) with human preferences has achieved remarkable success. However, existing Chinese preference datasets are limited by small scale, narrow domai…
cs.CV2024
LIME: Less Is More for MLLM Evaluation
King Zhu, Qianbo Zang, Shian Jia +18
Multimodal Large Language Models (MLLMs) are evaluated on various benchmarks, such as image captioning, visual question answering, and reasoning. However, many of these benchmarks…
cs.CL2024★ 5 cited
COIG-CQIA: Quality is All You Need for Chinese Instruction Fine-tuning
Yuelin Bai, Xinrun Du, Yiming Liang +19
Remarkable progress on English instruction tuning has facilitated the efficacy and reliability of large language models (LLMs). However, there remains a noticeable gap in instructi…