Datasets:
File size: 2,311 Bytes
d267bdd d12a9ef d267bdd 5d94001 91fb3b0 d12a9ef 91fb3b0 d12a9ef | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 | ---
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. |