You are provided with a research question, keyphrases about the question, a description of candidate datasets and dataset options. Read the description of popular datasets provided below and select the ones that can be used to validate the following research question. Use your knowledge of machine learning datasets to make the best judgement.
Your response should be formatted as a `json` array. For instance, for the query "Semi supervised image classification", a sample response might be: ["CIFAR-10", "CIFAR-100"]. Do not include any extra text in the response other than the answer array.

Query: I want to improve fill-in-the-blank multiple

Keyphrases: fill-in-the-blank multiple choice question answering images paragraph-level

Dataset description:
ChID: ChID is a large-scale Chinese IDiom dataset for cloze test. ChID contains 581K passages and 729K blanks, and covers multiple domains.
CNN/Daily Mail: CNN/Daily Mail is a dataset for text summarization. Human generated abstractive summary bullets were generated from news stories in CNN and Daily Mail websites as questions (with one of the entities hidden), and stories as the corresponding passages from which the system is expected to answer the fill-in the-blank question.
COCO: The MS COCO (Microsoft Common Objects in Context) dataset is a large-scale object detection, segmentation, key-point detection, and captioning dataset. The dataset consists of 328K images.
HICO: HICO is a benchmark for recognizing human-object interactions (HOI). Key features:   A diverse set of interactions with common object categories A list of well-defined, sense-based HOI categories An exhaustive labeling of co-occurring interactions with an object category in each image The annotation of each HOI instance (i.e.
MovieFIB: A quantitative benchmark for developing and understanding video of fill-in-the-blank question-answering dataset with over 300,000 examples, based on descriptive video annotations for the visually impaired.

Options:- A: ChID  B: CNN/Daily Mail  C: COCO  D: HICO  E: MovieFIB
["COCO", "HICO"]