README.md

---
license: cc-by-4.0
task_categories:
- summarization
- text-generation
language:
- en
tags:
- croissant
# viewer: false
size_categories:
- 10K<n<100K
dataset_info:
- config_name: title_10K
  features:
  - name: url
    dtype: string
  - name: published
    dtype: string
  - name: title
    dtype: string
  - name: abstract
    dtype: string
  - name: gt
    dtype: string
  - name: primary_cat
    dtype: string
  - name: paper_cat
    dtype: string
  - name: updated
    dtype: string
  - name: main_content
    dtype: string
  - name: authors
    dtype: string
  - name: label
    dtype: string
  - name: cats
    sequence: string
# - config_name: title_30K
#   features:
#   - name: url
#     dtype: string
#   - name: published
#     dtype: string
#   - name: title
#     dtype: string
#   - name: abstract
#     dtype: string
#   - name: gt
#     dtype: string
#   - name: primary_cat
#     dtype: string
#   - name: paper_cat
#     dtype: string
#   - name: updated
#     dtype: string
#   - name: main_content
#     dtype: string
#   - name: authors
#     dtype: string
#   - name: label
#     dtype: string
#   - name: cats
#     sequence: string
# - config_name: title_31K_G
#   features:
#   - name: url
#     dtype: string
#   - name: published
#     dtype: string
#   - name: title
#     dtype: string
#   - name: abstract
#     dtype: string
#   - name: gt
#     dtype: string
#   splits:
#   - name: test
# - config_name: abs_28K
#   features:
#   - name: url
#     dtype: string
#   - name: published
#     dtype: string
#   - name: title
#     dtype: string
#   - name: abstract
#     dtype: string
#   - name: gt
#     dtype: string
#   splits:
#   - name: test
- config_name: abs_9K
  features:
  - name: url
    dtype: string
  - name: published
    dtype: string
  - name: title
    dtype: string
  - name: abstract
    dtype: string
  - name: gt
    dtype: string
  - name: primary_cat
    dtype: string
  - name: paper_cat
    dtype: string
  - name: updated
    dtype: string
  - name: main_content
    dtype: string
  - name: authors
    dtype: string
  - name: label
    dtype: string
  - name: cats
    sequence: string
# - config_name: abs_29K_G
#   features:
#   - name: url
#     dtype: string
#   - name: published
#     dtype: string
#   - name: title
#     dtype: string
#   - name: abstract
#     dtype: string
#   - name: gt
#     dtype: string
#   splits:
#   - name: test
- config_name: intro_8K
  features:
  - name: url
    dtype: string
  - name: published
    dtype: string
  - name: title
    dtype: string
  - name: abstract
    dtype: string
  - name: gt
    dtype: string
  - name: primary_cat
    dtype: string
  - name: paper_cat
    dtype: string
  - name: updated
    dtype: string
  - name: main_content
    dtype: string
  - name: authors
    dtype: string
  - name: label
    dtype: string
  - name: cats
    sequence: string
# - config_name: intro_28K
#   features:
#   - name: url
#     dtype: string
#   - name: published
#     dtype: string
#   - name: title
#     dtype: string
#   - name: abstract
#     dtype: string
#   - name: gt
#     dtype: string
#   splits:
#   - name: test
# - config_name: intro_28K_G
#   features:
#   - name: url
#     dtype: string
#   - name: published
#     dtype: string
#   - name: title
#     dtype: string
#   - name: abstract
#     dtype: string
#   - name: gt
#     dtype: string
#   splits:
#   - name: test
# - config_name: related_34K
#   features:
#   - name: url
#     dtype: string
#   - name: published
#     dtype: string
#   - name: title
#     dtype: string
#   - name: abstract
#     dtype: string
#   - name: gt
#     dtype: string
#   splits:
#   - name: test
# - config_name: related_53K
#   features:
#   - name: url
#     dtype: string
#   - name: published
#     dtype: string
#   - name: title
#     dtype: string
#   - name: abstract
#     dtype: string
#   - name: gt
#     dtype: string
#   splits:
#   - name: test
# - config_name: related_53K_G
#   features:
#   - name: url
#     dtype: string
#   - name: published
#     dtype: string
#   - name: title
#     dtype: string
#   - name: abstract
#     dtype: string
#   - name: gt
#     dtype: string
#   splits:
#   - name: test
configs:
- config_name: title_10K
  data_files:
  - split: test
    path: title_10K/test_*.json
# - config_name: title_30K
#   data_files:
#   - split: test
#     path: title_30K/test_*.json
# - config_name: title_31K_G
#   data_files:
#   - split: test
#     path: title_31K_G/test_*.json
- config_name: abs_9K
  data_files:
  - split: test
    path: abs_9K/test_*.json
# - config_name: abs_28K
#   data_files:
#   - split: test
#     path: abs_28K/test_*.json
# - config_name: abs_29K_G
#   data_files:
#   - split: test
#     path: abs_29K_G/test_*.json
- config_name: intro_8K
  data_files:
  - split: test
    path: intro_8K/test_*.json
# - config_name: intro_28K
#   data_files:
#   - split: test
#     path: intro_28K/test_*.json
# - config_name: intro_28K_G
#   data_files:
#   - split: test
#     path: intro_28K_G/test_*.json
# - config_name: related_34K
#   data_files:
#   - split: test
#     path: related_34K/test_*.json
# - config_name: related_53K
#   data_files:
#   - split: test
#     path: related_53K/test_*.json
# - config_name: related_53K_G
#   data_files:
#   - split: test
#     path: related_53K_G/test_*.json
pretty_name: AcademicEval
---


# **AcademicEval Benchmark Introduction**


<!-- <img src="./model.png" width="75%" height="75%" /> -->
<div align=center> <img src="./model.png" width = 75% height="75%"/> </div>


We proposed <b><i>AcademicEval</i></b>, a live benchmark for evaluating LLMs over long-context generation tasks. <b><i>AcademicEval</i></b> adopts papers on arXiv to introduce several acadeic writing tasks with long-context inputs, <i>i.e.</i>, <b><i>Title, Abstract, Introduction, Related Work</i></b>, wich covers a wide range of abstraction levels and require no manual labeling. 

Comparing to existing long-context LLM benchmarks, our Comparing to existing long-context LLM benchmarks, our AcademicEval offers flexible length, automatic annotation, hierarchical abstraction, few-shot demonstrations, and live updates without data leakage risks.


**🌟Note🌟: currently, for the ease of downloading, we only uploaded the test set of AcademicEval (The rest of AcademicEval, i.e., train and val set, can be accessed via [AcademicEval Full](https://huggingface.co/datasets/ulab-ai/AcademicEval_Full)). The data viewer above shows the preview data information of **title-10K**, **abs-9K**, and **intro-8K**. For the complete test set data, please check "Files and versions" in this page.**




<table class="comparison-table">
  <thead>
    <tr>
      <th>Benchmark</th>
      <th>Avg Len</th>
      <th>Automatic Annotation</th>
      <th>Hierarchical Abstraction</th>
      <th>Few-shot Demonstrations</th>
      <th>Live Update</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <td>ZeroSCROLLS (Shaham et al., 2023)</td>
      <td>~10K</td>
      <td><span style="color: green;">&#x2713;</td>
      <td><span style="color: red;">&#x2718;</td>
      <td><span style="color: red;">&#x2718;</td>
      <td><span style="color: red;">&#x2718;</td>
    </tr>
    <tr>
      <td>L-Eval (An et al., 2023)</td>
      <td>~8K</td>
      <td><span style="color: red;">&#x2718;</td>
      <td><span style="color: red;">&#x2718;</td>
      <td><span style="color: red;">&#x2718;</td>
      <td><span style="color: red;">&#x2718;</td>
    </tr>
    <tr>
      <td>BAMBOO (Dong et al., 2023)</td>
      <td>~16K</td>
      <td><span style="color: red;">&#x2718;</td>
      <td><span style="color: red;">&#x2718;</td>
      <td><span style="color: red;">&#x2718;</td>
      <td><span style="color: red;">&#x2718;</td>
    </tr>
    <tr>
      <td>LongBench (Bai et al., 2023)</td>
      <td>~8K</td>
      <td><span style="color: red;">&#x2718;</td>
      <td><span style="color: red;">&#x2718;</td>
      <td><span style="color: green;">&#x2713;</td>
      <td><span style="color: red;">&#x2718;</td>
    </tr>
    <tr>
      <td>LooGLE (Li et al., 2023)</td>
      <td>~20K</td>
      <td><span style="color: red;">&#x2718;</td>
      <td><span style="color: red;">&#x2718;</td>
      <td><span style="color: red;">&#x2718;</td>
      <td><span style="color: red;">&#x2718;</td>
    </tr>
    <tr>
      <td>∞Bench (Zhang et al., 2024)</td>
      <td>~200K</td>
      <td><span style="color: red;">&#x2718;</td>
      <td><span style="color: red;">&#x2718;</td>
      <td><span style="color: red;">&#x2718;</td>
      <td><span style="color: red;">&#x2718;</td>
    </tr>
    <tr>
      <td><strong>AcademicEval (ours)</strong></td>
      <td><strong>Flexible</strong></td>
      <td><span style="color: green;">&#x2713;</td>
      <td><span style="color: green;">&#x2713;</td>
      <td><span style="color: green;">&#x2713;</td>
      <td><span style="color: green;">&#x2713;</td>
    </tr>
  </tbody>
</table>
<style>
  .comparison-table td:nth-child(3) span {
    color: green;
  }
  .comparison-table td:nth-child(4) span {
    color: red;
  }
  .comparison-table td {
  text-align: center;
}
</style>


# **Dataset Structure**

## Data Settings

- ***Title Writing***

  - **title_10K**

  - **title_30K**

  - **title_31K_G**

- ***Abstract Writing***

  - **abs_9K**

  - **abs_28K**

  - **abs_29K_G**

- ***Introduction Writing***

  - **intro_8K**

  - **intro_28K**

  - **intro_28K_G**

- ***Related Work Writing***

  - **related_34K**

  - **related_53K**

  - **related_53K_G**


## Main Data Fields

  + **url:** the url of the original paper on arXiv

  + **title:** the title of the paper

  + **abstract:** the abstract of the paper

  + **authors:** the authors of the paper

  + **published:** the publication timestamp of the paper

  + **primary_cat:** arXiv category

  + **gt:** the ground truth of the corresponding task

  + **main_content:** the main body of the paper (w/o the corresponding section content)

  + **additional_info:** the few-shot demonstrations from randomly selected papers (the data fields of each demonstration are the same as above)

  + **additional_graph_info:** the few-shot demonstrations with the co-author subgraph structure from co-author papers (the data fields of each demonstration are the same as above)