[Question]: LongBench BM25 reproduce

Describe the issue

I'm interested in your longllmlingua results on LongBench.
I reproduced LongBench BM25 2,000-token constraint using ChatGPT.
Unlike the your paper's results, the performance is too high.
trec task score is 72.5 and most of the other tasks are also high.
I would like to know how you produced the bm25 result.
I'll show you the parameter I used to reproduce bm25 so I'd appreciate it if you could tell me which one is different.
I use same split and parameters other tasks.(only q_format and first inst changing according to original LongBench config)

Thank you

first_inst="Please determine the type of the question below. Here are some examples of questions."
q_format="{input}"
question= q_format.format(input=input)
instruction=first_inst
contexts_list = df['ctxs'][i].split("\n")
contexts_list = [
"\n".join(contexts_list[ii : ii + 4]) for ii in range(0, len(contexts_list), 4)
]
compressed_prompt = llm_lingua.compress_prompt(
contexts_list,
instruction=instruction,
question=question,
target_token=1800,
condition_compare=True,
condition_in_question="after",
rank_method="bm25",
use_sentence_level_filter=False,
use_token_level_filter=False,
context_budget="+100",
dynamic_context_compression_ratio=0.4, # enable dynamic_context_compression_ratio
)