README.md

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license: apache-2.0
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# Difficult Long-context Retrieval-like Tasks
This is the Dataset used in the paper "Hyper-multi-step: The Truth Behind Difficult Long-context Tasks"

The tasks we provide are:

Simple tasks which are easy for Long-Context LMs:
* ``simple_k2v``: Direct key-to-value retrieval. The key is given and the model needs to retrieve the corresponding value.
* ``simple_v2k``: Direct value-to-key retrieval. The value is given and the model needs to retrieve the corresponding key.
* ``multi_step(kv)``: multi-step (formal) KV retrieval. The model needs to retrieve multiple values with multiple queries. Then concatenate the values to form a new key, and finally retrieve the corresponding value.

Difficult tasks which are nearly unsolvable for Long-Context LMs:
* ``logic(kv)``: logic-based KV retrieval. All the values are in range 0-9. We give the range of the value and the model needs to retrieve the corresponding key.
* ``logic(resume)``: logic-based student resume retrieval. We give the range of the GPA and the model needs to retrieve the corresponding student whose GPA is in the range.
* ``multi_match(kv)``: multi-match KV retrieval. The value is given and the model needs to retrieve multiple corresponding keys.
* ``multi_match(resume)``: multi-match student resume retrieval. A university name is given and the model needs to retrieve multiple corresponding students who are from this university.
* ``multi_match_last(kv)``: multi-match KV retrieval. The value is given and the model needs to retrieve multiple corresponding keys. The other gold keys are already given in the prompt, except the last one.


## The meaning of file names
For example:
* ``logic_kv_10`` means logic-based KV retrieval task with the context containing 10 KV items.
* ``3_match_resume_100`` means multi-match student resume retrieval task with the context containing 100 students and the model needs to retrieve 3 students.
* ``concat_3_kv_100_cot`` means multi-step KV retrieval task with the context containing 100 KV items and the model needs to concatenate 3 values retrieved with 3 queries. And the prompt style is Chain-of-Thought (CoT).

## Columns in the dataset
* ``prompt``: the full prompt of the task
* ``gold_keys``: the gold keys of the KV retrieval task. It's a string if there is only one gold key, otherwise it's a list of strings. In student resume retrieval, it's the student name (or a list of student names).
* ``gold_values``: the gold values of the KV retrieval task. It's a string if there is only one gold value, otherwise it's a list of strings. In student resume retrieval, it's the student's GPA or University (or a list of them).

Note that, in logic-based retrieval and multi-match retrieval tasks, ``gold_keys`` are actually the answer to the prompt.