5 papers
Evaluating Modern Large Language Models on Low-Resource and Morphologically Rich Languages:A Cross-Lingual Benchmark Across Cantonese, Japanese, and Turkish
Chengxuan Xia, Qianye Wu, Hongbin Guan +3
Large language models (LLMs) have achieved impressive results in high-resource languages like English, yet their effectiveness in low-resource and morphologically rich languages re…
MLVTG: Mamba-Based Feature Alignment and LLM-Driven Purification for Multi-Modal Video Temporal Grounding
Zhiyi Zhu, Xiaoyu Wu, Zihao Liu +1
Video Temporal Grounding (VTG), which aims to localize video clips corresponding to natural language queries, is a fundamental yet challenging task in video understanding. Existing…
TableEval: A Real-World Benchmark for Complex, Multilingual, and Multi-Structured Table Question Answering
Junnan Zhu, Jingyi Wang, Bohan Yu +4
LLMs have shown impressive progress in natural language processing. However, they still face significant challenges in TableQA, where real-world complexities such as diverse table…
Enhancing Video Memorability Prediction with Text-Motion Cross-modal Contrastive Loss and Its Application in Video Summarization
Zhiyi Zhu, Xiaoyu Wu, Youwei Lu
Video memorability refers to the ability of videos to be recalled after viewing, playing a crucial role in creating content that remains memorable. Existing models typically focus…
A Survey on Data Synthesis and Augmentation for Large Language Models
Ke Wang, Jiahui Zhu, Minjie Ren +8
The success of Large Language Models (LLMs) is inherently linked to the availability of vast, diverse, and high-quality data for training and evaluation. However, the growth rate o…