Datasets:
| dataset_info: | |
| features: | |
| - name: idx | |
| dtype: int64 | |
| - name: names | |
| dtype: string | |
| - name: parallel_chain | |
| dtype: string | |
| - name: parallel_total_val | |
| dtype: float64 | |
| - name: parallel_lastname | |
| dtype: string | |
| - name: parallel_single_val | |
| dtype: float64 | |
| - name: forward_chain | |
| dtype: string | |
| - name: forward_total_val | |
| dtype: float64 | |
| - name: forward_lastname | |
| dtype: string | |
| - name: forward_single_val | |
| dtype: float64 | |
| - name: backward_chain | |
| dtype: string | |
| - name: backward_total_val | |
| dtype: float64 | |
| - name: backward_lastname | |
| dtype: string | |
| - name: backward_single_val | |
| dtype: float64 | |
| - name: chaotic_chain | |
| dtype: string | |
| - name: chaotic_total_val | |
| dtype: float64 | |
| - name: chaotic_lastname | |
| dtype: string | |
| - name: chaotic_single_val | |
| dtype: float64 | |
| splits: | |
| - name: k5 | |
| num_bytes: 178184 | |
| num_examples: 200 | |
| - name: k10 | |
| num_bytes: 333938 | |
| num_examples: 200 | |
| - name: k20 | |
| num_bytes: 647136 | |
| num_examples: 200 | |
| - name: k50 | |
| num_bytes: 1582289 | |
| num_examples: 200 | |
| - name: k100 | |
| num_bytes: 3142590 | |
| num_examples: 200 | |
| - name: k200 | |
| num_bytes: 6266799 | |
| num_examples: 200 | |
| download_size: 4072876 | |
| dataset_size: 12150936 | |
| configs: | |
| - config_name: default | |
| data_files: | |
| - split: k5 | |
| path: data/k5-* | |
| - split: k10 | |
| path: data/k10-* | |
| - split: k20 | |
| path: data/k20-* | |
| - split: k50 | |
| path: data/k50-* | |
| - split: k100 | |
| path: data/k100-* | |
| - split: k200 | |
| path: data/k200-* | |
| task_categories: | |
| - question-answering | |
| language: | |
| - en | |
| tags: | |
| - llm-evaluation | |
| - long-context | |
| - reasoning | |
| - benchmark | |
| ## NeedleChain: Measuring Intact Long-Context Reasoning Capability of Large Language Models | |
| <p align="center"> | |
| Github: <a href="https://github.com/hyeonseokk/NeedleChain"> Official github repository </a> | |
| <br> | |
| Paper: <a href="https://arxiv.org/abs/2507.22411"> Official Paper </a> | |
| <br> | |
| --- | |
| <p align="center"> | |
| <img src="needlechain.png" width="500"/> | |
| </p> | |
| NeedleChain is a benchmark designed to evaluate LLMs' intact long-context understanding. | |
| Every provided context consists of query-relevant information, requiring a comprehensive understanding to answer the given query. | |
| --- | |
| For manual creation of NeedleChain datasets, please refer to our official github repository. |