2 citations · 2 across the 2 of their papers we have counts for
4 papers
LPFQA: A Long-Tail Professional Forum-based Benchmark for LLM Evaluation
Liya Zhu, Peizhuang Cong, Jingzhe Ding +17
Large Language Models (LLMs) perform well on standard reasoning and question-answering benchmarks, yet such evaluations often fail to capture their ability to handle long-tail, exp…
IV-Bench: A Benchmark for Image-Grounded Video Perception and Reasoning in Multimodal LLMs
David Ma, Yuanxing Zhang, Jincheng Ren +17
Existing evaluation frameworks for Multimodal Large Language Models (MLLMs) primarily focus on image reasoning or general video understanding tasks, largely overlooking the signifi…
Aligning Instruction Tuning with Pre-training
Yiming Liang, Tianyu Zheng, Xinrun Du +12
Instruction tuning enhances large language models (LLMs) to follow human instructions across diverse tasks, relying on high-quality datasets to guide behavior. However, these datas…
HelloBench: Evaluating Long Text Generation Capabilities of Large Language Models
Haoran Que, Feiyu Duan, Liqun He +11
In recent years, Large Language Models (LLMs) have demonstrated remarkable capabilities in various tasks (e.g., long-context understanding), and many benchmarks have been proposed.…