4 papers · 1 filter
RICo: Refined In-Context Contribution for Automatic Instruction-Tuning Data Selection
Yixin Yang, Qingxiu Dong, Linli Yao +2
Data selection for instruction tuning is crucial for improving the performance of large language models (LLMs) while reducing training costs. In this paper, we propose Refined Cont…
SCoRE: Benchmarking Long-Chain Reasoning in Commonsense Scenarios
Weidong Zhan, Yue Wang, Nan Hu +12
Currently, long-chain reasoning remains a key challenge for large language models (LLMs) because natural texts lack sufficient explicit reasoning data. However, existing benchmarks…
Beyond Single Frames: Can LMMs Comprehend Temporal and Contextual Narratives in Image Sequences?
Xiaochen Wang, Heming Xia, Jialin Song +9
Large Multimodal Models (LMMs) have achieved remarkable success across various visual-language tasks. However, existing benchmarks predominantly focus on single-image understanding…
Can Large Multimodal Models Uncover Deep Semantics Behind Images?
Yixin Yang, Zheng Li, Qingxiu Dong +2
Understanding the deep semantics of images is essential in the era dominated by social media. However, current research works primarily on the superficial description of images, re…