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Can Large Language Models Understand Internet Buzzwords Through User-Generated Content

Accepted by ACL 2025 (Main)

Paper Link: our paper

drawing

Dataset

The datasets(raw and filtered) are stored in folder ./data/data_cheating_filtered.py is the final version.

Here's the format & stat. of our data:

"流行词名字": {
"examples": "例句",
"definition": "定义",
"ground_truth": "流行词介绍",
        
"Gemini_15_pro_KEY": "Gemini 1.5 Pro对该词的定义(没有使用例句的情况)",
"Gemini_15_flash_KEY": "Gemini 1.5 Flash对该词的定义(没有使用例句的情况)",
"Qwen2_7b_KEY": "Qwen2 7b对该词的定义(没有使用例句的情况)",
"Qwen2_72b_KEY": "Qwen2 72b对该词的定义(没有使用例句的情况)"
"GPT_4o_KEY": "GPT_4o对该词的定义(没有使用例句的情况)",
"GPT_4o_mini_KEY": "GPT_4o_mini对该词的定义(没有使用例句的情况)",
        
"Gemini_15_pro_KEY_score": "LLM对Gemini_15_pro_KEY定义的评价", 
"Gemini_15_flash_KEY_score": "LLM对Gemini_15_flash_KEY定义的评价", 
"Qwen2_7b_KEY_score": "LLM对Qwen2_7b_KEY定义的评价", 
"Qwen2_72b_KEY_score": "LLM对Qwen2_72b_KEY定义的评价", 
"GPT_4o_KEY_score": "LLM对GPT_4o_KEY定义的评价", 
"GPT_4o_mini_KEY_score": "LLM对GPT_4o_mini_KEY定义的评价", 

}

drawing

drawing

File Structure

./main.py: Entry point and framework of our algorithm.

./dataUtil.py Used to process the raw data and load data

./ToolUtil.py Contains code for evaluation

./Agent LLM agents

./baselines Code for Focus

./classifier_and_its_attachments Code for sentence method "waus"(see appendix)

./data Stores our dataset(raw and filtered)

Quick Start

1. Install the necessary requirements

2. Run the following code:

python main.py

3. There are three parameters to set:

sentence_method: "all", "random", "waus", "gdex"
backbone_method: "Qwen/Qwen2-7B-Instruct", "Qwen/Qwen2-72B-Instruct", "gpt-4o", "gpt-4o-mini"
top_k: 50 by default

Benchmark Results

benchmark results

Reference

If you make advantage of our paper, please cite the following in your manuscript:

@inproceedings{buzz2025huang,
  title={Can Large Language Models Understand Internet Buzzwords Through User-Generated Content},
  author={Chen Huang, Junkai Luo, Xinzuo Wang, Wenqiang Lei, Jiancheng Lv},
  booktitle = {Annual Meeting of the Association for Computational Linguistics},
  year      = {2025}
}

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