From the 1 of 5 linked papers with an AI index.
5 papers
NeMo: Needle in a Montage for Video-Language Understanding
Zi-Yuan Hu, Shuo Liang, Duo Zheng +10
The paper introduces the Needle in a Montage (NeMo) task and the NeMoBench benchmark to evaluate temporal understanding in video-language models, using an automated pipeline to gen…
MuRating: A High Quality Data Selecting Approach to Multilingual Large Language Model Pretraining
Zhixun Chen, Ping Guo, Wenhan Han +10
Data quality is a critical driver of large language model performance, yet existing model-based selection methods focus almost exclusively on English. We introduce MuRating, a scal…
MuBench: Assessment of Multilingual Capabilities of Large Language Models Across 61 Languages
Wenhan Han, Yifan Zhang, Zhixun Chen +7
Multilingual large language models (LLMs) are advancing rapidly, with new models frequently claiming support for an increasing number of languages. However, existing evaluation dat…
LLMs Assist NLP Researchers: Critique Paper (Meta-)Reviewing
Jiangshu Du, Yibo Wang, Wenting Zhao +37
This work is motivated by two key trends. On one hand, large language models (LLMs) have shown remarkable versatility in various generative tasks such as writing, drawing, and ques…
MathOdyssey: Benchmarking Mathematical Problem-Solving Skills in Large Language Models Using Odyssey Math Data
Meng Fang, Xiangpeng Wan, Fei Lu +2
Large language models (LLMs) have significantly advanced natural language understanding and demonstrated strong problem-solving abilities. Despite these successes, most LLMs still…