Model Hub

RPC-Bench: A Fine-grained Benchmark for Research Paper Comprehension 🌐 Project Page • 💻 GitHub • 📖 Paper RPC-Bench is a fine-grained benchmark for research paper comprehension. It is built from review-rebuttal exchanges of high-quality academic papers and supports both text-only and visual evaluation through complementary paper representations. Data Structure RPC-Bench is organized into train, dev, and test subsets. Split assignments… See the full description on the dataset page: https://huggingface.co/datasets/zai-org/RPC-Bench.

LongBench v2: Towards Deeper Understanding and Reasoning on Realistic Long-context Multitasks 🌐 Project Page: https://longbench2.github.io 💻 Github Repo: https://github.com/THUDM/LongBench 📚 Arxiv Paper: https://arxiv.org/abs/2412.15204 LongBench v2 is designed to assess the ability of LLMs to handle long-context problems requiring deep understanding and reasoning across real-world multitasks. LongBench v2 has the following features: (1) Length: Context length ranging from 8k to… See the full description on the dataset page: https://huggingface.co/datasets/zai-org/LongBench-v2.

LongBench is a comprehensive benchmark for multilingual and multi-task purposes, with the goal to fully measure and evaluate the ability of pre-trained language models to understand long text. This dataset consists of twenty different tasks, covering key long-text application scenarios such as multi-document QA, single-document QA, summarization, few-shot learning, synthetic tasks, and code completion.