diff --git a/.gitattributes b/.gitattributes
new file mode 100755
index 0000000000000000000000000000000000000000..ca5fc1c222ab867d149b69d5a5d8978beb96b55e
--- /dev/null
+++ b/.gitattributes
@@ -0,0 +1,60 @@
+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ckpt filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.lz4 filter=lfs diff=lfs merge=lfs -text
+*.mlmodel filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.npy filter=lfs diff=lfs merge=lfs -text
+*.npz filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pickle filter=lfs diff=lfs merge=lfs -text
+*.pkl filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tar filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
+*.tgz filter=lfs diff=lfs merge=lfs -text
+*.wasm filter=lfs diff=lfs merge=lfs -text
+*.xz filter=lfs diff=lfs merge=lfs -text
+*.zip filter=lfs diff=lfs merge=lfs -text
+*.zst filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text
+# Audio files - uncompressed
+*.pcm filter=lfs diff=lfs merge=lfs -text
+*.sam filter=lfs diff=lfs merge=lfs -text
+*.raw filter=lfs diff=lfs merge=lfs -text
+# Audio files - compressed
+*.aac filter=lfs diff=lfs merge=lfs -text
+*.flac filter=lfs diff=lfs merge=lfs -text
+*.mp3 filter=lfs diff=lfs merge=lfs -text
+*.ogg filter=lfs diff=lfs merge=lfs -text
+*.wav filter=lfs diff=lfs merge=lfs -text
+# Image files - uncompressed
+*.bmp filter=lfs diff=lfs merge=lfs -text
+*.gif filter=lfs diff=lfs merge=lfs -text
+*.png filter=lfs diff=lfs merge=lfs -text
+*.tiff filter=lfs diff=lfs merge=lfs -text
+# Image files - compressed
+*.jpg filter=lfs diff=lfs merge=lfs -text
+*.jpeg filter=lfs diff=lfs merge=lfs -text
+*.webp filter=lfs diff=lfs merge=lfs -text
+raw/review_categories/*.jsonl filter=lfs diff=lfs merge=lfs -text
+raw/meta_categories/*.jsonl filter=lfs diff=lfs merge=lfs -text
+group_by_user/*.jsonl filter=lfs diff=lfs merge=lfs -text
+benchmark/*/*/*.csv filter=lfs diff=lfs merge=lfs -text
+asin2category.json filter=lfs diff=lfs merge=lfs -text
diff --git a/Amazon-Reviews-2023.py b/Amazon-Reviews-2023.py
new file mode 100644
index 0000000000000000000000000000000000000000..bfab97121711c51da6d5a018260f48b1400e42ab
--- /dev/null
+++ b/Amazon-Reviews-2023.py
@@ -0,0 +1,557 @@
+import json
+
+import datasets
+
+
+_AMAZON_REVIEW_2023_DESCRIPTION = """\
+Amazon Review 2023 is an updated version of the Amazon Review 2018 dataset.
+This dataset mainly includes reviews (ratings, text) and item metadata (desc-
+riptions, category information, price, brand, and images). Compared to the pre-
+vious versions, the 2023 version features larger size, newer reviews (up to Sep
+2023), richer and cleaner meta data, and finer-grained timestamps (from day to 
+milli-second).
+
+"""
+
+
+class RawMetaAmazonReview2023Config(datasets.BuilderConfig):
+    def __init__(self, **kwargs):
+        super(RawMetaAmazonReview2023Config, self).__init__(**kwargs)
+
+        self.suffix = 'jsonl'
+        self.domain = self.name[len(f'raw_meta_'):]
+        self.description = f'This is a subset for items in domain: {self.domain}.'
+        self.data_dir = f'raw/meta_categories/meta_{self.domain}.jsonl'
+
+
+class RawReviewAmazonReview2023Config(datasets.BuilderConfig):
+    def __init__(self, **kwargs):
+        super(RawReviewAmazonReview2023Config, self).__init__(**kwargs)
+
+        self.suffix = 'jsonl'
+        self.domain = self.name[len(f'raw_review_'):]
+        self.description = f'This is a subset for reviews in domain: {self.domain}.'
+        self.data_dir = f'raw/review_categories/{self.domain}.jsonl'
+
+
+class RatingOnlyAmazonReview2023Config(datasets.BuilderConfig):
+    def __init__(self, **kwargs):
+        super(RatingOnlyAmazonReview2023Config, self).__init__(**kwargs)
+
+        self.suffix = 'csv'
+        self.kcore = self.name[:len('0core')]
+        self.domain = self.name[len(f'0core_rating_only_'):]
+        self.description = \
+            f'This is the preprocessed file that only contains <user, item, rating, timestamp> in domain: {self.domain}.\n' \
+            f'The preprocessing includes {self.kcore} filtering and <user, item> interaction deduplication'
+        self.data_dir = f'benchmark/{self.kcore}/rating_only/{self.domain}.csv'
+
+
+class BenchmarkAmazonReview2023Config(datasets.BuilderConfig):
+    def __init__(self, **kwargs):
+        super(BenchmarkAmazonReview2023Config, self).__init__(**kwargs)
+
+        self.suffix = 'csv'
+        self.split = None
+        for potential_split in ['last_out_w_his', 'timestamp_w_his', 'last_out', 'timestamp']:
+            if potential_split in self.name:
+                self.split = potential_split
+                break
+        if self.split is None:
+            ValueError(f'Cannot find valid split for {self.name}')
+        self.kcore = self.name[:len('0core')]
+        self.domain = self.name[len(f'0core_{self.split}_'):]
+        self.description = \
+            f'This is the preprocessed benchmark in domain: {self.domain}.' \
+            f'The preprocessing includes {self.kcore} filtering, <user, item> interaction deduplication, ' \
+            f'as well as split by {self.split}.'
+        self.data_dir = {
+            'train': f'benchmark/{self.kcore}/{self.split}/{self.domain}.train.csv',
+            'valid': f'benchmark/{self.kcore}/{self.split}/{self.domain}.valid.csv',
+            'test': f'benchmark/{self.kcore}/{self.split}/{self.domain}.test.csv'
+        }
+
+
+class AmazonReview2023(datasets.GeneratorBasedBuilder):
+    BUILDER_CONFIGS = [
+        # Raw item metadata
+        RawMetaAmazonReview2023Config(name='raw_meta_All_Beauty'),
+        RawMetaAmazonReview2023Config(name='raw_meta_Toys_and_Games'),
+        RawMetaAmazonReview2023Config(name='raw_meta_Cell_Phones_and_Accessories'),
+        RawMetaAmazonReview2023Config(name='raw_meta_Industrial_and_Scientific'),
+        RawMetaAmazonReview2023Config(name='raw_meta_Gift_Cards'),
+        RawMetaAmazonReview2023Config(name='raw_meta_Musical_Instruments'),
+        RawMetaAmazonReview2023Config(name='raw_meta_Electronics'),
+        RawMetaAmazonReview2023Config(name='raw_meta_Handmade_Products'),
+        RawMetaAmazonReview2023Config(name='raw_meta_Arts_Crafts_and_Sewing'),
+        RawMetaAmazonReview2023Config(name='raw_meta_Baby_Products'),
+        RawMetaAmazonReview2023Config(name='raw_meta_Health_and_Household'),
+        RawMetaAmazonReview2023Config(name='raw_meta_Office_Products'),
+        RawMetaAmazonReview2023Config(name='raw_meta_Digital_Music'),
+        RawMetaAmazonReview2023Config(name='raw_meta_Grocery_and_Gourmet_Food'),
+        RawMetaAmazonReview2023Config(name='raw_meta_Sports_and_Outdoors'),
+        RawMetaAmazonReview2023Config(name='raw_meta_Home_and_Kitchen'),
+        RawMetaAmazonReview2023Config(name='raw_meta_Subscription_Boxes'),
+        RawMetaAmazonReview2023Config(name='raw_meta_Tools_and_Home_Improvement'),
+        RawMetaAmazonReview2023Config(name='raw_meta_Pet_Supplies'),
+        RawMetaAmazonReview2023Config(name='raw_meta_Video_Games'),
+        RawMetaAmazonReview2023Config(name='raw_meta_Kindle_Store'),
+        RawMetaAmazonReview2023Config(name='raw_meta_Clothing_Shoes_and_Jewelry'),
+        RawMetaAmazonReview2023Config(name='raw_meta_Patio_Lawn_and_Garden'),
+        RawMetaAmazonReview2023Config(name='raw_meta_Unknown'),
+        RawMetaAmazonReview2023Config(name='raw_meta_Books'),
+        RawMetaAmazonReview2023Config(name='raw_meta_Automotive'),
+        RawMetaAmazonReview2023Config(name='raw_meta_CDs_and_Vinyl'),
+        RawMetaAmazonReview2023Config(name='raw_meta_Beauty_and_Personal_Care'),
+        RawMetaAmazonReview2023Config(name='raw_meta_Amazon_Fashion'),
+        RawMetaAmazonReview2023Config(name='raw_meta_Magazine_Subscriptions'),
+        RawMetaAmazonReview2023Config(name='raw_meta_Software'),
+        RawMetaAmazonReview2023Config(name='raw_meta_Health_and_Personal_Care'),
+        RawMetaAmazonReview2023Config(name='raw_meta_Appliances'),
+        RawMetaAmazonReview2023Config(name='raw_meta_Movies_and_TV'),
+        # Raw review
+        RawReviewAmazonReview2023Config(name='raw_review_All_Beauty'),
+        RawReviewAmazonReview2023Config(name='raw_review_Toys_and_Games'),
+        RawReviewAmazonReview2023Config(name='raw_review_Cell_Phones_and_Accessories'),
+        RawReviewAmazonReview2023Config(name='raw_review_Industrial_and_Scientific'),
+        RawReviewAmazonReview2023Config(name='raw_review_Gift_Cards'),
+        RawReviewAmazonReview2023Config(name='raw_review_Musical_Instruments'),
+        RawReviewAmazonReview2023Config(name='raw_review_Electronics'),
+        RawReviewAmazonReview2023Config(name='raw_review_Handmade_Products'),
+        RawReviewAmazonReview2023Config(name='raw_review_Arts_Crafts_and_Sewing'),
+        RawReviewAmazonReview2023Config(name='raw_review_Baby_Products'),
+        RawReviewAmazonReview2023Config(name='raw_review_Health_and_Household'),
+        RawReviewAmazonReview2023Config(name='raw_review_Office_Products'),
+        RawReviewAmazonReview2023Config(name='raw_review_Digital_Music'),
+        RawReviewAmazonReview2023Config(name='raw_review_Grocery_and_Gourmet_Food'),
+        RawReviewAmazonReview2023Config(name='raw_review_Sports_and_Outdoors'),
+        RawReviewAmazonReview2023Config(name='raw_review_Home_and_Kitchen'),
+        RawReviewAmazonReview2023Config(name='raw_review_Subscription_Boxes'),
+        RawReviewAmazonReview2023Config(name='raw_review_Tools_and_Home_Improvement'),
+        RawReviewAmazonReview2023Config(name='raw_review_Pet_Supplies'),
+        RawReviewAmazonReview2023Config(name='raw_review_Video_Games'),
+        RawReviewAmazonReview2023Config(name='raw_review_Kindle_Store'),
+        RawReviewAmazonReview2023Config(name='raw_review_Clothing_Shoes_and_Jewelry'),
+        RawReviewAmazonReview2023Config(name='raw_review_Patio_Lawn_and_Garden'),
+        RawReviewAmazonReview2023Config(name='raw_review_Unknown'),
+        RawReviewAmazonReview2023Config(name='raw_review_Books'),
+        RawReviewAmazonReview2023Config(name='raw_review_Automotive'),
+        RawReviewAmazonReview2023Config(name='raw_review_CDs_and_Vinyl'),
+        RawReviewAmazonReview2023Config(name='raw_review_Beauty_and_Personal_Care'),
+        RawReviewAmazonReview2023Config(name='raw_review_Amazon_Fashion'),
+        RawReviewAmazonReview2023Config(name='raw_review_Magazine_Subscriptions'),
+        RawReviewAmazonReview2023Config(name='raw_review_Software'),
+        RawReviewAmazonReview2023Config(name='raw_review_Health_and_Personal_Care'),
+        RawReviewAmazonReview2023Config(name='raw_review_Appliances'),
+        RawReviewAmazonReview2023Config(name='raw_review_Movies_and_TV'),
+        # Rating only - 0core
+        RatingOnlyAmazonReview2023Config(name='0core_rating_only_All_Beauty'),
+        RatingOnlyAmazonReview2023Config(name='0core_rating_only_Toys_and_Games'),
+        RatingOnlyAmazonReview2023Config(name='0core_rating_only_Cell_Phones_and_Accessories'),
+        RatingOnlyAmazonReview2023Config(name='0core_rating_only_Industrial_and_Scientific'),
+        RatingOnlyAmazonReview2023Config(name='0core_rating_only_Gift_Cards'),
+        RatingOnlyAmazonReview2023Config(name='0core_rating_only_Musical_Instruments'),
+        RatingOnlyAmazonReview2023Config(name='0core_rating_only_Electronics'),
+        RatingOnlyAmazonReview2023Config(name='0core_rating_only_Handmade_Products'),
+        RatingOnlyAmazonReview2023Config(name='0core_rating_only_Arts_Crafts_and_Sewing'),
+        RatingOnlyAmazonReview2023Config(name='0core_rating_only_Baby_Products'),
+        RatingOnlyAmazonReview2023Config(name='0core_rating_only_Health_and_Household'),
+        RatingOnlyAmazonReview2023Config(name='0core_rating_only_Office_Products'),
+        RatingOnlyAmazonReview2023Config(name='0core_rating_only_Digital_Music'),
+        RatingOnlyAmazonReview2023Config(name='0core_rating_only_Grocery_and_Gourmet_Food'),
+        RatingOnlyAmazonReview2023Config(name='0core_rating_only_Sports_and_Outdoors'),
+        RatingOnlyAmazonReview2023Config(name='0core_rating_only_Home_and_Kitchen'),
+        RatingOnlyAmazonReview2023Config(name='0core_rating_only_Subscription_Boxes'),
+        RatingOnlyAmazonReview2023Config(name='0core_rating_only_Tools_and_Home_Improvement'),
+        RatingOnlyAmazonReview2023Config(name='0core_rating_only_Pet_Supplies'),
+        RatingOnlyAmazonReview2023Config(name='0core_rating_only_Video_Games'),
+        RatingOnlyAmazonReview2023Config(name='0core_rating_only_Kindle_Store'),
+        RatingOnlyAmazonReview2023Config(name='0core_rating_only_Clothing_Shoes_and_Jewelry'),
+        RatingOnlyAmazonReview2023Config(name='0core_rating_only_Patio_Lawn_and_Garden'),
+        RatingOnlyAmazonReview2023Config(name='0core_rating_only_Unknown'),
+        RatingOnlyAmazonReview2023Config(name='0core_rating_only_Books'),
+        RatingOnlyAmazonReview2023Config(name='0core_rating_only_Automotive'),
+        RatingOnlyAmazonReview2023Config(name='0core_rating_only_CDs_and_Vinyl'),
+        RatingOnlyAmazonReview2023Config(name='0core_rating_only_Beauty_and_Personal_Care'),
+        RatingOnlyAmazonReview2023Config(name='0core_rating_only_Amazon_Fashion'),
+        RatingOnlyAmazonReview2023Config(name='0core_rating_only_Magazine_Subscriptions'),
+        RatingOnlyAmazonReview2023Config(name='0core_rating_only_Software'),
+        RatingOnlyAmazonReview2023Config(name='0core_rating_only_Health_and_Personal_Care'),
+        RatingOnlyAmazonReview2023Config(name='0core_rating_only_Appliances'),
+        RatingOnlyAmazonReview2023Config(name='0core_rating_only_Movies_and_TV'),
+        # Rating only - 5core
+        RatingOnlyAmazonReview2023Config(name='5core_rating_only_All_Beauty'),
+        RatingOnlyAmazonReview2023Config(name='5core_rating_only_Toys_and_Games'),
+        RatingOnlyAmazonReview2023Config(name='5core_rating_only_Cell_Phones_and_Accessories'),
+        RatingOnlyAmazonReview2023Config(name='5core_rating_only_Industrial_and_Scientific'),
+        RatingOnlyAmazonReview2023Config(name='5core_rating_only_Gift_Cards'),
+        RatingOnlyAmazonReview2023Config(name='5core_rating_only_Musical_Instruments'),
+        RatingOnlyAmazonReview2023Config(name='5core_rating_only_Electronics'),
+        RatingOnlyAmazonReview2023Config(name='5core_rating_only_Arts_Crafts_and_Sewing'),
+        RatingOnlyAmazonReview2023Config(name='5core_rating_only_Baby_Products'),
+        RatingOnlyAmazonReview2023Config(name='5core_rating_only_Health_and_Household'),
+        RatingOnlyAmazonReview2023Config(name='5core_rating_only_Office_Products'),
+        RatingOnlyAmazonReview2023Config(name='5core_rating_only_Grocery_and_Gourmet_Food'),
+        RatingOnlyAmazonReview2023Config(name='5core_rating_only_Sports_and_Outdoors'),
+        RatingOnlyAmazonReview2023Config(name='5core_rating_only_Home_and_Kitchen'),
+        RatingOnlyAmazonReview2023Config(name='5core_rating_only_Tools_and_Home_Improvement'),
+        RatingOnlyAmazonReview2023Config(name='5core_rating_only_Pet_Supplies'),
+        RatingOnlyAmazonReview2023Config(name='5core_rating_only_Video_Games'),
+        RatingOnlyAmazonReview2023Config(name='5core_rating_only_Kindle_Store'),
+        RatingOnlyAmazonReview2023Config(name='5core_rating_only_Clothing_Shoes_and_Jewelry'),
+        RatingOnlyAmazonReview2023Config(name='5core_rating_only_Patio_Lawn_and_Garden'),
+        RatingOnlyAmazonReview2023Config(name='5core_rating_only_Unknown'),
+        RatingOnlyAmazonReview2023Config(name='5core_rating_only_Books'),
+        RatingOnlyAmazonReview2023Config(name='5core_rating_only_Automotive'),
+        RatingOnlyAmazonReview2023Config(name='5core_rating_only_CDs_and_Vinyl'),
+        RatingOnlyAmazonReview2023Config(name='5core_rating_only_Beauty_and_Personal_Care'),
+        RatingOnlyAmazonReview2023Config(name='5core_rating_only_Magazine_Subscriptions'),
+        RatingOnlyAmazonReview2023Config(name='5core_rating_only_Software'),
+        RatingOnlyAmazonReview2023Config(name='5core_rating_only_Movies_and_TV'),
+        # Benchmark - last_out - 0core
+        BenchmarkAmazonReview2023Config(name='0core_last_out_All_Beauty'),
+        BenchmarkAmazonReview2023Config(name='0core_last_out_Toys_and_Games'),
+        BenchmarkAmazonReview2023Config(name='0core_last_out_Cell_Phones_and_Accessories'),
+        BenchmarkAmazonReview2023Config(name='0core_last_out_Industrial_and_Scientific'),
+        BenchmarkAmazonReview2023Config(name='0core_last_out_Gift_Cards'),
+        BenchmarkAmazonReview2023Config(name='0core_last_out_Musical_Instruments'),
+        BenchmarkAmazonReview2023Config(name='0core_last_out_Electronics'),
+        BenchmarkAmazonReview2023Config(name='0core_last_out_Handmade_Products'),
+        BenchmarkAmazonReview2023Config(name='0core_last_out_Arts_Crafts_and_Sewing'),
+        BenchmarkAmazonReview2023Config(name='0core_last_out_Baby_Products'),
+        BenchmarkAmazonReview2023Config(name='0core_last_out_Health_and_Household'),
+        BenchmarkAmazonReview2023Config(name='0core_last_out_Office_Products'),
+        BenchmarkAmazonReview2023Config(name='0core_last_out_Digital_Music'),
+        BenchmarkAmazonReview2023Config(name='0core_last_out_Grocery_and_Gourmet_Food'),
+        BenchmarkAmazonReview2023Config(name='0core_last_out_Sports_and_Outdoors'),
+        BenchmarkAmazonReview2023Config(name='0core_last_out_Home_and_Kitchen'),
+        BenchmarkAmazonReview2023Config(name='0core_last_out_Subscription_Boxes'),
+        BenchmarkAmazonReview2023Config(name='0core_last_out_Tools_and_Home_Improvement'),
+        BenchmarkAmazonReview2023Config(name='0core_last_out_Pet_Supplies'),
+        BenchmarkAmazonReview2023Config(name='0core_last_out_Video_Games'),
+        BenchmarkAmazonReview2023Config(name='0core_last_out_Kindle_Store'),
+        BenchmarkAmazonReview2023Config(name='0core_last_out_Clothing_Shoes_and_Jewelry'),
+        BenchmarkAmazonReview2023Config(name='0core_last_out_Patio_Lawn_and_Garden'),
+        BenchmarkAmazonReview2023Config(name='0core_last_out_Unknown'),
+        BenchmarkAmazonReview2023Config(name='0core_last_out_Books'),
+        BenchmarkAmazonReview2023Config(name='0core_last_out_Automotive'),
+        BenchmarkAmazonReview2023Config(name='0core_last_out_CDs_and_Vinyl'),
+        BenchmarkAmazonReview2023Config(name='0core_last_out_Beauty_and_Personal_Care'),
+        BenchmarkAmazonReview2023Config(name='0core_last_out_Amazon_Fashion'),
+        BenchmarkAmazonReview2023Config(name='0core_last_out_Magazine_Subscriptions'),
+        BenchmarkAmazonReview2023Config(name='0core_last_out_Software'),
+        BenchmarkAmazonReview2023Config(name='0core_last_out_Health_and_Personal_Care'),
+        BenchmarkAmazonReview2023Config(name='0core_last_out_Appliances'),
+        BenchmarkAmazonReview2023Config(name='0core_last_out_Movies_and_TV'),
+        # Benchmark - last_out - 5core
+        BenchmarkAmazonReview2023Config(name='5core_last_out_All_Beauty'),
+        BenchmarkAmazonReview2023Config(name='5core_last_out_Toys_and_Games'),
+        BenchmarkAmazonReview2023Config(name='5core_last_out_Cell_Phones_and_Accessories'),
+        BenchmarkAmazonReview2023Config(name='5core_last_out_Industrial_and_Scientific'),
+        BenchmarkAmazonReview2023Config(name='5core_last_out_Gift_Cards'),
+        BenchmarkAmazonReview2023Config(name='5core_last_out_Musical_Instruments'),
+        BenchmarkAmazonReview2023Config(name='5core_last_out_Electronics'),
+        BenchmarkAmazonReview2023Config(name='5core_last_out_Arts_Crafts_and_Sewing'),
+        BenchmarkAmazonReview2023Config(name='5core_last_out_Baby_Products'),
+        BenchmarkAmazonReview2023Config(name='5core_last_out_Health_and_Household'),
+        BenchmarkAmazonReview2023Config(name='5core_last_out_Office_Products'),
+        BenchmarkAmazonReview2023Config(name='5core_last_out_Grocery_and_Gourmet_Food'),
+        BenchmarkAmazonReview2023Config(name='5core_last_out_Sports_and_Outdoors'),
+        BenchmarkAmazonReview2023Config(name='5core_last_out_Home_and_Kitchen'),
+        BenchmarkAmazonReview2023Config(name='5core_last_out_Tools_and_Home_Improvement'),
+        BenchmarkAmazonReview2023Config(name='5core_last_out_Pet_Supplies'),
+        BenchmarkAmazonReview2023Config(name='5core_last_out_Video_Games'),
+        BenchmarkAmazonReview2023Config(name='5core_last_out_Kindle_Store'),
+        BenchmarkAmazonReview2023Config(name='5core_last_out_Clothing_Shoes_and_Jewelry'),
+        BenchmarkAmazonReview2023Config(name='5core_last_out_Patio_Lawn_and_Garden'),
+        BenchmarkAmazonReview2023Config(name='5core_last_out_Unknown'),
+        BenchmarkAmazonReview2023Config(name='5core_last_out_Books'),
+        BenchmarkAmazonReview2023Config(name='5core_last_out_Automotive'),
+        BenchmarkAmazonReview2023Config(name='5core_last_out_CDs_and_Vinyl'),
+        BenchmarkAmazonReview2023Config(name='5core_last_out_Beauty_and_Personal_Care'),
+        BenchmarkAmazonReview2023Config(name='5core_last_out_Magazine_Subscriptions'),
+        BenchmarkAmazonReview2023Config(name='5core_last_out_Software'),
+        BenchmarkAmazonReview2023Config(name='5core_last_out_Movies_and_TV'),
+        # Benchmark - last_out_w_his - 0core
+        BenchmarkAmazonReview2023Config(name='0core_last_out_w_his_All_Beauty'),
+        BenchmarkAmazonReview2023Config(name='0core_last_out_w_his_Toys_and_Games'),
+        BenchmarkAmazonReview2023Config(name='0core_last_out_w_his_Cell_Phones_and_Accessories'),
+        BenchmarkAmazonReview2023Config(name='0core_last_out_w_his_Industrial_and_Scientific'),
+        BenchmarkAmazonReview2023Config(name='0core_last_out_w_his_Gift_Cards'),
+        BenchmarkAmazonReview2023Config(name='0core_last_out_w_his_Musical_Instruments'),
+        BenchmarkAmazonReview2023Config(name='0core_last_out_w_his_Electronics'),
+        BenchmarkAmazonReview2023Config(name='0core_last_out_w_his_Handmade_Products'),
+        BenchmarkAmazonReview2023Config(name='0core_last_out_w_his_Arts_Crafts_and_Sewing'),
+        BenchmarkAmazonReview2023Config(name='0core_last_out_w_his_Baby_Products'),
+        BenchmarkAmazonReview2023Config(name='0core_last_out_w_his_Health_and_Household'),
+        BenchmarkAmazonReview2023Config(name='0core_last_out_w_his_Office_Products'),
+        BenchmarkAmazonReview2023Config(name='0core_last_out_w_his_Digital_Music'),
+        BenchmarkAmazonReview2023Config(name='0core_last_out_w_his_Grocery_and_Gourmet_Food'),
+        BenchmarkAmazonReview2023Config(name='0core_last_out_w_his_Sports_and_Outdoors'),
+        BenchmarkAmazonReview2023Config(name='0core_last_out_w_his_Home_and_Kitchen'),
+        BenchmarkAmazonReview2023Config(name='0core_last_out_w_his_Subscription_Boxes'),
+        BenchmarkAmazonReview2023Config(name='0core_last_out_w_his_Tools_and_Home_Improvement'),
+        BenchmarkAmazonReview2023Config(name='0core_last_out_w_his_Pet_Supplies'),
+        BenchmarkAmazonReview2023Config(name='0core_last_out_w_his_Video_Games'),
+        BenchmarkAmazonReview2023Config(name='0core_last_out_w_his_Kindle_Store'),
+        BenchmarkAmazonReview2023Config(name='0core_last_out_w_his_Clothing_Shoes_and_Jewelry'),
+        BenchmarkAmazonReview2023Config(name='0core_last_out_w_his_Patio_Lawn_and_Garden'),
+        BenchmarkAmazonReview2023Config(name='0core_last_out_w_his_Unknown'),
+        BenchmarkAmazonReview2023Config(name='0core_last_out_w_his_Books'),
+        BenchmarkAmazonReview2023Config(name='0core_last_out_w_his_Automotive'),
+        BenchmarkAmazonReview2023Config(name='0core_last_out_w_his_CDs_and_Vinyl'),
+        BenchmarkAmazonReview2023Config(name='0core_last_out_w_his_Beauty_and_Personal_Care'),
+        BenchmarkAmazonReview2023Config(name='0core_last_out_w_his_Amazon_Fashion'),
+        BenchmarkAmazonReview2023Config(name='0core_last_out_w_his_Magazine_Subscriptions'),
+        BenchmarkAmazonReview2023Config(name='0core_last_out_w_his_Software'),
+        BenchmarkAmazonReview2023Config(name='0core_last_out_w_his_Health_and_Personal_Care'),
+        BenchmarkAmazonReview2023Config(name='0core_last_out_w_his_Appliances'),
+        BenchmarkAmazonReview2023Config(name='0core_last_out_w_his_Movies_and_TV'),
+        # Benchmark - last_out_w_his - 5core
+        BenchmarkAmazonReview2023Config(name='5core_last_out_w_his_All_Beauty'),
+        BenchmarkAmazonReview2023Config(name='5core_last_out_w_his_Toys_and_Games'),
+        BenchmarkAmazonReview2023Config(name='5core_last_out_w_his_Cell_Phones_and_Accessories'),
+        BenchmarkAmazonReview2023Config(name='5core_last_out_w_his_Industrial_and_Scientific'),
+        BenchmarkAmazonReview2023Config(name='5core_last_out_w_his_Gift_Cards'),
+        BenchmarkAmazonReview2023Config(name='5core_last_out_w_his_Musical_Instruments'),
+        BenchmarkAmazonReview2023Config(name='5core_last_out_w_his_Electronics'),
+        BenchmarkAmazonReview2023Config(name='5core_last_out_w_his_Arts_Crafts_and_Sewing'),
+        BenchmarkAmazonReview2023Config(name='5core_last_out_w_his_Baby_Products'),
+        BenchmarkAmazonReview2023Config(name='5core_last_out_w_his_Health_and_Household'),
+        BenchmarkAmazonReview2023Config(name='5core_last_out_w_his_Office_Products'),
+        BenchmarkAmazonReview2023Config(name='5core_last_out_w_his_Grocery_and_Gourmet_Food'),
+        BenchmarkAmazonReview2023Config(name='5core_last_out_w_his_Sports_and_Outdoors'),
+        BenchmarkAmazonReview2023Config(name='5core_last_out_w_his_Home_and_Kitchen'),
+        BenchmarkAmazonReview2023Config(name='5core_last_out_w_his_Tools_and_Home_Improvement'),
+        BenchmarkAmazonReview2023Config(name='5core_last_out_w_his_Pet_Supplies'),
+        BenchmarkAmazonReview2023Config(name='5core_last_out_w_his_Video_Games'),
+        BenchmarkAmazonReview2023Config(name='5core_last_out_w_his_Kindle_Store'),
+        BenchmarkAmazonReview2023Config(name='5core_last_out_w_his_Clothing_Shoes_and_Jewelry'),
+        BenchmarkAmazonReview2023Config(name='5core_last_out_w_his_Patio_Lawn_and_Garden'),
+        BenchmarkAmazonReview2023Config(name='5core_last_out_w_his_Unknown'),
+        BenchmarkAmazonReview2023Config(name='5core_last_out_w_his_Books'),
+        BenchmarkAmazonReview2023Config(name='5core_last_out_w_his_Automotive'),
+        BenchmarkAmazonReview2023Config(name='5core_last_out_w_his_CDs_and_Vinyl'),
+        BenchmarkAmazonReview2023Config(name='5core_last_out_w_his_Beauty_and_Personal_Care'),
+        BenchmarkAmazonReview2023Config(name='5core_last_out_w_his_Magazine_Subscriptions'),
+        BenchmarkAmazonReview2023Config(name='5core_last_out_w_his_Software'),
+        BenchmarkAmazonReview2023Config(name='5core_last_out_w_his_Movies_and_TV'),
+        # Benchmark - timestamp - 0core
+        BenchmarkAmazonReview2023Config(name='0core_timestamp_All_Beauty'),
+        BenchmarkAmazonReview2023Config(name='0core_timestamp_Toys_and_Games'),
+        BenchmarkAmazonReview2023Config(name='0core_timestamp_Cell_Phones_and_Accessories'),
+        BenchmarkAmazonReview2023Config(name='0core_timestamp_Industrial_and_Scientific'),
+        BenchmarkAmazonReview2023Config(name='0core_timestamp_Gift_Cards'),
+        BenchmarkAmazonReview2023Config(name='0core_timestamp_Musical_Instruments'),
+        BenchmarkAmazonReview2023Config(name='0core_timestamp_Electronics'),
+        BenchmarkAmazonReview2023Config(name='0core_timestamp_Handmade_Products'),
+        BenchmarkAmazonReview2023Config(name='0core_timestamp_Arts_Crafts_and_Sewing'),
+        BenchmarkAmazonReview2023Config(name='0core_timestamp_Baby_Products'),
+        BenchmarkAmazonReview2023Config(name='0core_timestamp_Health_and_Household'),
+        BenchmarkAmazonReview2023Config(name='0core_timestamp_Office_Products'),
+        BenchmarkAmazonReview2023Config(name='0core_timestamp_Digital_Music'),
+        BenchmarkAmazonReview2023Config(name='0core_timestamp_Grocery_and_Gourmet_Food'),
+        BenchmarkAmazonReview2023Config(name='0core_timestamp_Sports_and_Outdoors'),
+        BenchmarkAmazonReview2023Config(name='0core_timestamp_Home_and_Kitchen'),
+        BenchmarkAmazonReview2023Config(name='0core_timestamp_Subscription_Boxes'),
+        BenchmarkAmazonReview2023Config(name='0core_timestamp_Tools_and_Home_Improvement'),
+        BenchmarkAmazonReview2023Config(name='0core_timestamp_Pet_Supplies'),
+        BenchmarkAmazonReview2023Config(name='0core_timestamp_Video_Games'),
+        BenchmarkAmazonReview2023Config(name='0core_timestamp_Kindle_Store'),
+        BenchmarkAmazonReview2023Config(name='0core_timestamp_Clothing_Shoes_and_Jewelry'),
+        BenchmarkAmazonReview2023Config(name='0core_timestamp_Patio_Lawn_and_Garden'),
+        BenchmarkAmazonReview2023Config(name='0core_timestamp_Unknown'),
+        BenchmarkAmazonReview2023Config(name='0core_timestamp_Books'),
+        BenchmarkAmazonReview2023Config(name='0core_timestamp_Automotive'),
+        BenchmarkAmazonReview2023Config(name='0core_timestamp_CDs_and_Vinyl'),
+        BenchmarkAmazonReview2023Config(name='0core_timestamp_Beauty_and_Personal_Care'),
+        BenchmarkAmazonReview2023Config(name='0core_timestamp_Amazon_Fashion'),
+        BenchmarkAmazonReview2023Config(name='0core_timestamp_Magazine_Subscriptions'),
+        BenchmarkAmazonReview2023Config(name='0core_timestamp_Software'),
+        BenchmarkAmazonReview2023Config(name='0core_timestamp_Health_and_Personal_Care'),
+        BenchmarkAmazonReview2023Config(name='0core_timestamp_Appliances'),
+        BenchmarkAmazonReview2023Config(name='0core_timestamp_Movies_and_TV'),
+        # Benchmark - timestamp - 5core
+        BenchmarkAmazonReview2023Config(name='5core_timestamp_All_Beauty'),
+        BenchmarkAmazonReview2023Config(name='5core_timestamp_Toys_and_Games'),
+        BenchmarkAmazonReview2023Config(name='5core_timestamp_Cell_Phones_and_Accessories'),
+        BenchmarkAmazonReview2023Config(name='5core_timestamp_Industrial_and_Scientific'),
+        BenchmarkAmazonReview2023Config(name='5core_timestamp_Gift_Cards'),
+        BenchmarkAmazonReview2023Config(name='5core_timestamp_Musical_Instruments'),
+        BenchmarkAmazonReview2023Config(name='5core_timestamp_Electronics'),
+        BenchmarkAmazonReview2023Config(name='5core_timestamp_Arts_Crafts_and_Sewing'),
+        BenchmarkAmazonReview2023Config(name='5core_timestamp_Baby_Products'),
+        BenchmarkAmazonReview2023Config(name='5core_timestamp_Health_and_Household'),
+        BenchmarkAmazonReview2023Config(name='5core_timestamp_Office_Products'),
+        BenchmarkAmazonReview2023Config(name='5core_timestamp_Grocery_and_Gourmet_Food'),
+        BenchmarkAmazonReview2023Config(name='5core_timestamp_Sports_and_Outdoors'),
+        BenchmarkAmazonReview2023Config(name='5core_timestamp_Home_and_Kitchen'),
+        BenchmarkAmazonReview2023Config(name='5core_timestamp_Tools_and_Home_Improvement'),
+        BenchmarkAmazonReview2023Config(name='5core_timestamp_Pet_Supplies'),
+        BenchmarkAmazonReview2023Config(name='5core_timestamp_Video_Games'),
+        BenchmarkAmazonReview2023Config(name='5core_timestamp_Kindle_Store'),
+        BenchmarkAmazonReview2023Config(name='5core_timestamp_Clothing_Shoes_and_Jewelry'),
+        BenchmarkAmazonReview2023Config(name='5core_timestamp_Patio_Lawn_and_Garden'),
+        BenchmarkAmazonReview2023Config(name='5core_timestamp_Unknown'),
+        BenchmarkAmazonReview2023Config(name='5core_timestamp_Books'),
+        BenchmarkAmazonReview2023Config(name='5core_timestamp_Automotive'),
+        BenchmarkAmazonReview2023Config(name='5core_timestamp_CDs_and_Vinyl'),
+        BenchmarkAmazonReview2023Config(name='5core_timestamp_Beauty_and_Personal_Care'),
+        BenchmarkAmazonReview2023Config(name='5core_timestamp_Magazine_Subscriptions'),
+        BenchmarkAmazonReview2023Config(name='5core_timestamp_Software'),
+        BenchmarkAmazonReview2023Config(name='5core_timestamp_Movies_and_TV'),
+        # Benchmark - timestamp_w_his - 0core
+        BenchmarkAmazonReview2023Config(name='0core_timestamp_w_his_All_Beauty'),
+        BenchmarkAmazonReview2023Config(name='0core_timestamp_w_his_Toys_and_Games'),
+        BenchmarkAmazonReview2023Config(name='0core_timestamp_w_his_Cell_Phones_and_Accessories'),
+        BenchmarkAmazonReview2023Config(name='0core_timestamp_w_his_Industrial_and_Scientific'),
+        BenchmarkAmazonReview2023Config(name='0core_timestamp_w_his_Gift_Cards'),
+        BenchmarkAmazonReview2023Config(name='0core_timestamp_w_his_Musical_Instruments'),
+        BenchmarkAmazonReview2023Config(name='0core_timestamp_w_his_Electronics'),
+        BenchmarkAmazonReview2023Config(name='0core_timestamp_w_his_Handmade_Products'),
+        BenchmarkAmazonReview2023Config(name='0core_timestamp_w_his_Arts_Crafts_and_Sewing'),
+        BenchmarkAmazonReview2023Config(name='0core_timestamp_w_his_Baby_Products'),
+        BenchmarkAmazonReview2023Config(name='0core_timestamp_w_his_Health_and_Household'),
+        BenchmarkAmazonReview2023Config(name='0core_timestamp_w_his_Office_Products'),
+        BenchmarkAmazonReview2023Config(name='0core_timestamp_w_his_Digital_Music'),
+        BenchmarkAmazonReview2023Config(name='0core_timestamp_w_his_Grocery_and_Gourmet_Food'),
+        BenchmarkAmazonReview2023Config(name='0core_timestamp_w_his_Sports_and_Outdoors'),
+        BenchmarkAmazonReview2023Config(name='0core_timestamp_w_his_Home_and_Kitchen'),
+        BenchmarkAmazonReview2023Config(name='0core_timestamp_w_his_Subscription_Boxes'),
+        BenchmarkAmazonReview2023Config(name='0core_timestamp_w_his_Tools_and_Home_Improvement'),
+        BenchmarkAmazonReview2023Config(name='0core_timestamp_w_his_Pet_Supplies'),
+        BenchmarkAmazonReview2023Config(name='0core_timestamp_w_his_Video_Games'),
+        BenchmarkAmazonReview2023Config(name='0core_timestamp_w_his_Kindle_Store'),
+        BenchmarkAmazonReview2023Config(name='0core_timestamp_w_his_Clothing_Shoes_and_Jewelry'),
+        BenchmarkAmazonReview2023Config(name='0core_timestamp_w_his_Patio_Lawn_and_Garden'),
+        BenchmarkAmazonReview2023Config(name='0core_timestamp_w_his_Unknown'),
+        BenchmarkAmazonReview2023Config(name='0core_timestamp_w_his_Books'),
+        BenchmarkAmazonReview2023Config(name='0core_timestamp_w_his_Automotive'),
+        BenchmarkAmazonReview2023Config(name='0core_timestamp_w_his_CDs_and_Vinyl'),
+        BenchmarkAmazonReview2023Config(name='0core_timestamp_w_his_Beauty_and_Personal_Care'),
+        BenchmarkAmazonReview2023Config(name='0core_timestamp_w_his_Amazon_Fashion'),
+        BenchmarkAmazonReview2023Config(name='0core_timestamp_w_his_Magazine_Subscriptions'),
+        BenchmarkAmazonReview2023Config(name='0core_timestamp_w_his_Software'),
+        BenchmarkAmazonReview2023Config(name='0core_timestamp_w_his_Health_and_Personal_Care'),
+        BenchmarkAmazonReview2023Config(name='0core_timestamp_w_his_Appliances'),
+        BenchmarkAmazonReview2023Config(name='0core_timestamp_w_his_Movies_and_TV'),
+        # Benchmark - timestamp_w_his - 5core
+        BenchmarkAmazonReview2023Config(name='5core_timestamp_w_his_All_Beauty'),
+        BenchmarkAmazonReview2023Config(name='5core_timestamp_w_his_Toys_and_Games'),
+        BenchmarkAmazonReview2023Config(name='5core_timestamp_w_his_Cell_Phones_and_Accessories'),
+        BenchmarkAmazonReview2023Config(name='5core_timestamp_w_his_Industrial_and_Scientific'),
+        BenchmarkAmazonReview2023Config(name='5core_timestamp_w_his_Gift_Cards'),
+        BenchmarkAmazonReview2023Config(name='5core_timestamp_w_his_Musical_Instruments'),
+        BenchmarkAmazonReview2023Config(name='5core_timestamp_w_his_Electronics'),
+        BenchmarkAmazonReview2023Config(name='5core_timestamp_w_his_Arts_Crafts_and_Sewing'),
+        BenchmarkAmazonReview2023Config(name='5core_timestamp_w_his_Baby_Products'),
+        BenchmarkAmazonReview2023Config(name='5core_timestamp_w_his_Health_and_Household'),
+        BenchmarkAmazonReview2023Config(name='5core_timestamp_w_his_Office_Products'),
+        BenchmarkAmazonReview2023Config(name='5core_timestamp_w_his_Grocery_and_Gourmet_Food'),
+        BenchmarkAmazonReview2023Config(name='5core_timestamp_w_his_Sports_and_Outdoors'),
+        BenchmarkAmazonReview2023Config(name='5core_timestamp_w_his_Home_and_Kitchen'),
+        BenchmarkAmazonReview2023Config(name='5core_timestamp_w_his_Tools_and_Home_Improvement'),
+        BenchmarkAmazonReview2023Config(name='5core_timestamp_w_his_Pet_Supplies'),
+        BenchmarkAmazonReview2023Config(name='5core_timestamp_w_his_Video_Games'),
+        BenchmarkAmazonReview2023Config(name='5core_timestamp_w_his_Kindle_Store'),
+        BenchmarkAmazonReview2023Config(name='5core_timestamp_w_his_Clothing_Shoes_and_Jewelry'),
+        BenchmarkAmazonReview2023Config(name='5core_timestamp_w_his_Patio_Lawn_and_Garden'),
+        BenchmarkAmazonReview2023Config(name='5core_timestamp_w_his_Unknown'),
+        BenchmarkAmazonReview2023Config(name='5core_timestamp_w_his_Books'),
+        BenchmarkAmazonReview2023Config(name='5core_timestamp_w_his_Automotive'),
+        BenchmarkAmazonReview2023Config(name='5core_timestamp_w_his_CDs_and_Vinyl'),
+        BenchmarkAmazonReview2023Config(name='5core_timestamp_w_his_Beauty_and_Personal_Care'),
+        BenchmarkAmazonReview2023Config(name='5core_timestamp_w_his_Magazine_Subscriptions'),
+        BenchmarkAmazonReview2023Config(name='5core_timestamp_w_his_Software'),
+        BenchmarkAmazonReview2023Config(name='5core_timestamp_w_his_Movies_and_TV'),
+    ]
+
+    def _info(self):
+        features = None
+        if isinstance(self.config, RawMetaAmazonReview2023Config):
+            features = datasets.Features({
+                'main_category': datasets.Value('string'),
+                'title': datasets.Value('string'),
+                'average_rating': datasets.Value(dtype='float64'),
+                'rating_number': datasets.Value(dtype='int64'),
+                'features': datasets.Sequence(datasets.Value('string')),
+                'description': datasets.Sequence(datasets.Value('string')),
+                'price': datasets.Value('string'),
+                'images': datasets.Sequence({
+                    'hi_res': datasets.Value('string'),
+                    'large': datasets.Value('string'),
+                    'thumb': datasets.Value('string'),
+                    'variant': datasets.Value('string')
+                }),
+                'videos': datasets.Sequence({
+                    'title': datasets.Value('string'),
+                    'url': datasets.Value('string'),
+                    'user_id': datasets.Value('string')
+                }),
+                'store': datasets.Value('string'),
+                'categories': datasets.Sequence(datasets.Value('string')),
+                'details': datasets.Value('string'),
+                'parent_asin': datasets.Value('string'),
+                'bought_together': datasets.Value('string'),    # TODO: Check this type
+                'subtitle': datasets.Value('string'),
+                'author': datasets.Value('string')
+            })
+        elif isinstance(self.config, RawReviewAmazonReview2023Config):
+            # TODO: Check review features
+            pass
+
+        return datasets.DatasetInfo(
+            description=_AMAZON_REVIEW_2023_DESCRIPTION + self.config.description,
+            features=features
+        )
+
+    def _split_generators(self, dl_manager):
+        dl_dir = dl_manager.download_and_extract(self.config.data_dir)
+        if isinstance(self.config, BenchmarkAmazonReview2023Config):
+            return [
+                datasets.SplitGenerator(name='train', gen_kwargs={"filepath": dl_dir['train']}),
+                datasets.SplitGenerator(name='valid', gen_kwargs={"filepath": dl_dir['valid']}),
+                datasets.SplitGenerator(name='test', gen_kwargs={"filepath": dl_dir['test']}),
+            ]
+        else:
+            return [
+                datasets.SplitGenerator(name='full', gen_kwargs={"filepath": dl_dir})
+            ]
+
+    def _generate_examples(self, filepath):
+        with open(filepath, 'r', encoding='utf-8') as file:
+            if self.config.suffix == 'csv':
+                colnames = file.readline().strip().split(',')
+            for idx, line in enumerate(file):
+                if self.config.suffix == 'jsonl':
+                    try:
+                        dp = json.loads(line)
+                        """
+                        For item metadata, 'details' is free-form structured data
+                        Here we dump it to string to make huggingface datasets easy
+                        to store.
+                        """
+                        if isinstance(self.config, RawMetaAmazonReview2023Config):
+                            if 'details' in dp:
+                                dp['details'] = json.dumps(dp['details'])
+                            if 'price' in dp:
+                                dp['price'] = str(dp['price'])
+                            for optional_key in ['subtitle', 'author']:
+                                if optional_key not in dp:
+                                    dp[optional_key] = None
+                            for i in range(len(dp['images'])):
+                                for k in ['hi_res', 'large', 'thumb', 'variant']:
+                                    if k not in dp['images'][i]:
+                                        dp['images'][i][k] = None
+                            for i in range(len(dp['videos'])):
+                                for k in ['title', 'url', 'user_id']:
+                                    if k not in dp['videos'][i]:
+                                        dp['videos'][i][k] = None
+                    except:
+                        continue
+                elif self.config.suffix == 'csv':
+                    line = line.strip().split(',')
+                    dp = {k: v for k, v in zip(colnames, line)}
+                else:
+                    raise ValueError(f'Unknown suffix {self.config.suffix}.')
+                yield idx, dp
diff --git a/README.md b/README.md
new file mode 100755
index 0000000000000000000000000000000000000000..96d6ce6ae8c9fe233b48903d8a35acc80befcaf0
--- /dev/null
+++ b/README.md
@@ -0,0 +1,733 @@
+---
+language:
+- en
+tags:
+- recommendation
+- reviews
+size_categories:
+- 10B<n<100B
+dataset_info:
+- config_name: raw_meta_All_Beauty
+  features:
+  - name: main_category
+    dtype: string
+  - name: title
+    dtype: string
+  - name: average_rating
+    dtype: float64
+  - name: rating_number
+    dtype: int64
+  - name: features
+    sequence: string
+  - name: description
+    sequence: string
+  - name: price
+    dtype: string
+  - name: images
+    sequence:
+    - name: hi_res
+      dtype: string
+    - name: large
+      dtype: string
+    - name: thumb
+      dtype: string
+    - name: variant
+      dtype: string
+  - name: videos
+    sequence:
+    - name: title
+      dtype: string
+    - name: url
+      dtype: string
+    - name: user_id
+      dtype: string
+  - name: store
+    dtype: string
+  - name: categories
+    sequence: string
+  - name: details
+    dtype: string
+  - name: parent_asin
+    dtype: string
+  - name: bought_together
+    dtype: string
+  - name: subtitle
+    dtype: string
+  - name: author
+    dtype: string
+  splits:
+  - name: full
+    num_bytes: 172622243
+    num_examples: 112590
+  download_size: 59635138
+  dataset_size: 172622243
+- config_name: raw_meta_Arts_Crafts_and_Sewing
+  features:
+  - name: main_category
+    dtype: string
+  - name: title
+    dtype: string
+  - name: average_rating
+    dtype: float64
+  - name: rating_number
+    dtype: int64
+  - name: features
+    sequence: string
+  - name: description
+    sequence: string
+  - name: price
+    dtype: string
+  - name: images
+    sequence:
+    - name: hi_res
+      dtype: string
+    - name: large
+      dtype: string
+    - name: thumb
+      dtype: string
+    - name: variant
+      dtype: string
+  - name: videos
+    sequence:
+    - name: title
+      dtype: string
+    - name: url
+      dtype: string
+    - name: user_id
+      dtype: string
+  - name: store
+    dtype: string
+  - name: categories
+    sequence: string
+  - name: details
+    dtype: string
+  - name: parent_asin
+    dtype: string
+  - name: bought_together
+    dtype: string
+  - name: subtitle
+    dtype: string
+  - name: author
+    dtype: string
+  splits:
+  - name: full
+    num_bytes: 1893257069
+    num_examples: 801446
+  download_size: 806711170
+  dataset_size: 1893257069
+- config_name: raw_meta_Cell_Phones_and_Accessories
+  features:
+  - name: main_category
+    dtype: string
+  - name: title
+    dtype: string
+  - name: average_rating
+    dtype: float64
+  - name: rating_number
+    dtype: int64
+  - name: features
+    sequence: string
+  - name: description
+    sequence: string
+  - name: price
+    dtype: string
+  - name: images
+    sequence:
+    - name: hi_res
+      dtype: string
+    - name: large
+      dtype: string
+    - name: thumb
+      dtype: string
+    - name: variant
+      dtype: string
+  - name: videos
+    sequence:
+    - name: title
+      dtype: string
+    - name: url
+      dtype: string
+    - name: user_id
+      dtype: string
+  - name: store
+    dtype: string
+  - name: categories
+    sequence: string
+  - name: details
+    dtype: string
+  - name: parent_asin
+    dtype: string
+  - name: bought_together
+    dtype: string
+  - name: subtitle
+    dtype: string
+  - name: author
+    dtype: string
+  splits:
+  - name: full
+    num_bytes: 3497596478
+    num_examples: 1288490
+  download_size: 1262072469
+  dataset_size: 3497596478
+- config_name: raw_meta_Electronics
+  features:
+  - name: main_category
+    dtype: string
+  - name: title
+    dtype: string
+  - name: average_rating
+    dtype: float64
+  - name: rating_number
+    dtype: int64
+  - name: features
+    sequence: string
+  - name: description
+    sequence: string
+  - name: price
+    dtype: string
+  - name: images
+    sequence:
+    - name: hi_res
+      dtype: string
+    - name: large
+      dtype: string
+    - name: thumb
+      dtype: string
+    - name: variant
+      dtype: string
+  - name: videos
+    sequence:
+    - name: title
+      dtype: string
+    - name: url
+      dtype: string
+    - name: user_id
+      dtype: string
+  - name: store
+    dtype: string
+  - name: categories
+    sequence: string
+  - name: details
+    dtype: string
+  - name: parent_asin
+    dtype: string
+  - name: bought_together
+    dtype: string
+  - name: subtitle
+    dtype: string
+  - name: author
+    dtype: string
+  splits:
+  - name: full
+    num_bytes: 4603602269
+    num_examples: 1610012
+  download_size: 1955009715
+  dataset_size: 4603602269
+- config_name: raw_meta_Gift_Cards
+  features:
+  - name: main_category
+    dtype: string
+  - name: title
+    dtype: string
+  - name: average_rating
+    dtype: float64
+  - name: rating_number
+    dtype: int64
+  - name: features
+    sequence: string
+  - name: description
+    sequence: string
+  - name: price
+    dtype: string
+  - name: images
+    sequence:
+    - name: hi_res
+      dtype: string
+    - name: large
+      dtype: string
+    - name: thumb
+      dtype: string
+    - name: variant
+      dtype: string
+  - name: videos
+    sequence:
+    - name: title
+      dtype: string
+    - name: url
+      dtype: string
+    - name: user_id
+      dtype: string
+  - name: store
+    dtype: string
+  - name: categories
+    sequence: string
+  - name: details
+    dtype: string
+  - name: parent_asin
+    dtype: string
+  - name: bought_together
+    dtype: string
+  - name: subtitle
+    dtype: string
+  - name: author
+    dtype: string
+  splits:
+  - name: full
+    num_bytes: 1740761
+    num_examples: 1137
+  download_size: 401887
+  dataset_size: 1740761
+- config_name: raw_meta_Handmade_Products
+  features:
+  - name: main_category
+    dtype: string
+  - name: title
+    dtype: string
+  - name: average_rating
+    dtype: float64
+  - name: rating_number
+    dtype: int64
+  - name: features
+    sequence: string
+  - name: description
+    sequence: string
+  - name: price
+    dtype: string
+  - name: images
+    sequence:
+    - name: hi_res
+      dtype: string
+    - name: large
+      dtype: string
+    - name: thumb
+      dtype: string
+    - name: variant
+      dtype: string
+  - name: videos
+    sequence:
+    - name: title
+      dtype: string
+    - name: url
+      dtype: string
+    - name: user_id
+      dtype: string
+  - name: store
+    dtype: string
+  - name: categories
+    sequence: string
+  - name: details
+    dtype: string
+  - name: parent_asin
+    dtype: string
+  - name: bought_together
+    dtype: string
+  - name: subtitle
+    dtype: string
+  - name: author
+    dtype: string
+  splits:
+  - name: full
+    num_bytes: 340772183
+    num_examples: 164817
+  download_size: 132049123
+  dataset_size: 340772183
+- config_name: raw_meta_Industrial_and_Scientific
+  features:
+  - name: main_category
+    dtype: string
+  - name: title
+    dtype: string
+  - name: average_rating
+    dtype: float64
+  - name: rating_number
+    dtype: int64
+  - name: features
+    sequence: string
+  - name: description
+    sequence: string
+  - name: price
+    dtype: string
+  - name: images
+    sequence:
+    - name: hi_res
+      dtype: string
+    - name: large
+      dtype: string
+    - name: thumb
+      dtype: string
+    - name: variant
+      dtype: string
+  - name: videos
+    sequence:
+    - name: title
+      dtype: string
+    - name: url
+      dtype: string
+    - name: user_id
+      dtype: string
+  - name: store
+    dtype: string
+  - name: categories
+    sequence: string
+  - name: details
+    dtype: string
+  - name: parent_asin
+    dtype: string
+  - name: bought_together
+    dtype: string
+  - name: subtitle
+    dtype: string
+  - name: author
+    dtype: string
+  splits:
+  - name: full
+    num_bytes: 986632649
+    num_examples: 427564
+  download_size: 425007659
+  dataset_size: 986632649
+- config_name: raw_meta_Musical_Instruments
+  features:
+  - name: main_category
+    dtype: string
+  - name: title
+    dtype: string
+  - name: average_rating
+    dtype: float64
+  - name: rating_number
+    dtype: int64
+  - name: features
+    sequence: string
+  - name: description
+    sequence: string
+  - name: price
+    dtype: string
+  - name: images
+    sequence:
+    - name: hi_res
+      dtype: string
+    - name: large
+      dtype: string
+    - name: thumb
+      dtype: string
+    - name: variant
+      dtype: string
+  - name: videos
+    sequence:
+    - name: title
+      dtype: string
+    - name: url
+      dtype: string
+    - name: user_id
+      dtype: string
+  - name: store
+    dtype: string
+  - name: categories
+    sequence: string
+  - name: details
+    dtype: string
+  - name: parent_asin
+    dtype: string
+  - name: bought_together
+    dtype: string
+  - name: subtitle
+    dtype: string
+  - name: author
+    dtype: string
+  splits:
+  - name: full
+    num_bytes: 553296301
+    num_examples: 213593
+  download_size: 229633633
+  dataset_size: 553296301
+- config_name: raw_meta_Toys_and_Games
+  features:
+  - name: main_category
+    dtype: string
+  - name: title
+    dtype: string
+  - name: average_rating
+    dtype: float64
+  - name: rating_number
+    dtype: int64
+  - name: features
+    sequence: string
+  - name: description
+    sequence: string
+  - name: price
+    dtype: string
+  - name: images
+    sequence:
+    - name: hi_res
+      dtype: string
+    - name: large
+      dtype: string
+    - name: thumb
+      dtype: string
+    - name: variant
+      dtype: string
+  - name: videos
+    sequence:
+    - name: title
+      dtype: string
+    - name: url
+      dtype: string
+    - name: user_id
+      dtype: string
+  - name: store
+    dtype: string
+  - name: categories
+    sequence: string
+  - name: details
+    dtype: string
+  - name: parent_asin
+    dtype: string
+  - name: bought_together
+    dtype: string
+  - name: subtitle
+    dtype: string
+  - name: author
+    dtype: string
+  splits:
+  - name: full
+    num_bytes: 2291736294
+    num_examples: 890874
+  download_size: 972667016
+  dataset_size: 2291736294
+configs:
+- config_name: raw_meta_All_Beauty
+  data_files:
+  - split: full
+    path: raw_meta_All_Beauty/full-*
+- config_name: raw_meta_Arts_Crafts_and_Sewing
+  data_files:
+  - split: full
+    path: raw_meta_Arts_Crafts_and_Sewing/full-*
+- config_name: raw_meta_Cell_Phones_and_Accessories
+  data_files:
+  - split: full
+    path: raw_meta_Cell_Phones_and_Accessories/full-*
+- config_name: raw_meta_Electronics
+  data_files:
+  - split: full
+    path: raw_meta_Electronics/full-*
+- config_name: raw_meta_Gift_Cards
+  data_files:
+  - split: full
+    path: raw_meta_Gift_Cards/full-*
+- config_name: raw_meta_Handmade_Products
+  data_files:
+  - split: full
+    path: raw_meta_Handmade_Products/full-*
+- config_name: raw_meta_Industrial_and_Scientific
+  data_files:
+  - split: full
+    path: raw_meta_Industrial_and_Scientific/full-*
+- config_name: raw_meta_Musical_Instruments
+  data_files:
+  - split: full
+    path: raw_meta_Musical_Instruments/full-*
+- config_name: raw_meta_Toys_and_Games
+  data_files:
+  - split: full
+    path: raw_meta_Toys_and_Games/full-*
+---
+
+# Amazon Reviews 2023
+
+**Please also visit [amazon-reviews-2023.github.io/](https://amazon-reviews-2023.github.io/) for more details, loading scripts, and preprocessed benchmark files.**
+
+**[April 7, 2024]** We add two useful files:
+
+1. `all_categories.txt`: 34 lines (33 categories + "Unknown"), each line contains a category name.
+2. `asin2category.json`: A mapping between `parent_asin` (item ID) to its corresponding category name.
+
+---
+
+<!-- Provide a quick summary of the dataset. -->
+
+This is a large-scale **Amazon Reviews** dataset, collected in **2023** by [McAuley Lab](https://cseweb.ucsd.edu/~jmcauley/), and it includes rich features such as:
+1. **User Reviews** (*ratings*, *text*, *helpfulness votes*, etc.);
+2. **Item Metadata** (*descriptions*, *price*, *raw image*, etc.);
+3. **Links** (*user-item* / *bought together* graphs). 
+
+## What's New?
+
+In the Amazon Reviews'23, we provide:
+
+1. **Larger Dataset:** We collected 571.54M reviews, 245.2% larger than the last version;
+2. **Newer Interactions:** Current interactions range from May. 1996 to Sep. 2023;
+3. **Richer Metadata:** More descriptive features in item metadata;
+4. **Fine-grained Timestamp:** Interaction timestamp at the second or finer level;
+5. **Cleaner Processing:** Cleaner item metadata than previous versions;
+6. **Standard Splitting:** Standard data splits to encourage RecSys benchmarking.
+
+## Basic Statistics
+
+> We define the <b>#R_Tokens</b> as the number of [tokens](https://pypi.org/project/tiktoken/) in user reviews and <b>#M_Tokens</b> as the number of [tokens](https://pypi.org/project/tiktoken/) if treating the dictionaries of item attributes as strings. We emphasize them as important statistics in the era of LLMs.
+
+> We count the number of items based on user reviews rather than item metadata files. Note that some items lack metadata.
+
+### Compared to Previous Versions
+
+|  Year       | #Review | #User | #Item | #R_Token | #M_Token | #Domain | Timespan          |
+| ----------- | ---------: | -------: | -------: | ---------: | ------------: | ------------: |   ------------: |  
+| [2013](https://snap.stanford.edu/data/web-Amazon-links.html) | 34.69M      | 6.64M     | 2.44M     | 5.91B             | -- |  28          |  Jun'96 - Mar'13       | 
+| [2014](https://cseweb.ucsd.edu/~jmcauley/datasets/amazon/links.html)     | 82.83M      | 21.13M    | 9.86M     | 9.16B             | 4.14B | 24          | May'96 - Jul'14       |
+| [2018](https://cseweb.ucsd.edu/~jmcauley/datasets/amazon_v2/)                   | 233.10M      | 43.53M   | 15.17M    | 15.73B             | 7.99B | 29          |  May'96 - Oct'18       |
+| <b>[2023](https://)</b>                                                     | **571.54M**  | **54.51M** | **48.19M** | **30.14B**  | **30.78B** | **33**  | **May'96 - Sep'23**    |
+
+
+### Grouped by Category
+
+| Category                 | #User   | #Item   | #Rating   | #R_Token | #M_Token | Download                     |
+| ------------------------ | ------: | ------: | --------: | -------: | -------: | ------------------------------: |
+| All_Beauty | 632.0K | 112.6K | 701.5K | 31.6M | 74.1M | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/All_Beauty.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_All_Beauty.jsonl.gz' download> meta </a> |
+| Amazon_Fashion | 2.0M | 825.9K | 2.5M | 94.9M | 510.5M | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Amazon_Fashion.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Amazon_Fashion.jsonl.gz' download> meta </a> |
+| Appliances | 1.8M | 94.3K | 2.1M | 92.8M | 95.3M | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Appliances.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Appliances.jsonl.gz' download> meta </a> |
+| Arts_Crafts_and_Sewing | 4.6M | 801.3K | 9.0M | 350.0M | 695.4M | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Arts_Crafts_and_Sewing.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Arts_Crafts_and_Sewing.jsonl.gz' download> meta </a> |
+| Automotive | 8.0M | 2.0M | 20.0M | 824.9M | 1.7B | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Automotive.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Automotive.jsonl.gz' download> meta </a> |
+| Baby_Products | 3.4M | 217.7K | 6.0M | 323.3M | 218.6M | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Baby_Products.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Baby_Products.jsonl.gz' download> meta </a> |
+| Beauty_and_Personal_Care | 11.3M | 1.0M | 23.9M | 1.1B | 913.7M | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Beauty_and_Personal_Care.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Beauty_and_Personal_Care.jsonl.gz' download> meta </a> |
+| Books | 10.3M | 4.4M | 29.5M | 2.9B | 3.7B | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Books.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Books.jsonl.gz' download> meta </a> |
+| CDs_and_Vinyl | 1.8M | 701.7K | 4.8M | 514.8M | 287.5M | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/CDs_and_Vinyl.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_CDs_and_Vinyl.jsonl.gz' download> meta </a> |
+| Cell_Phones_and_Accessories | 11.6M | 1.3M | 20.8M | 935.4M | 1.3B | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Cell_Phones_and_Accessories.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Cell_Phones_and_Accessories.jsonl.gz' download> meta </a> |
+| Clothing_Shoes_and_Jewelry | 22.6M | 7.2M | 66.0M | 2.6B | 5.9B | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Clothing_Shoes_and_Jewelry.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Clothing_Shoes_and_Jewelry.jsonl.gz' download> meta </a> |
+| Digital_Music | 101.0K | 70.5K | 130.4K | 11.4M | 22.3M | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Digital_Music.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Digital_Music.jsonl.gz' download> meta </a> |
+| Electronics | 18.3M | 1.6M | 43.9M | 2.7B | 1.7B | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Electronics.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Electronics.jsonl.gz' download> meta </a> |
+| Gift_Cards | 132.7K | 1.1K | 152.4K | 3.6M | 630.0K | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Gift_Cards.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Gift_Cards.jsonl.gz' download> meta </a> |
+| Grocery_and_Gourmet_Food | 7.0M | 603.2K | 14.3M | 579.5M | 462.8M | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Grocery_and_Gourmet_Food.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Grocery_and_Gourmet_Food.jsonl.gz' download> meta </a> |
+| Handmade_Products | 586.6K | 164.7K | 664.2K | 23.3M | 125.8M | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Handmade_Products.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Handmade_Products.jsonl.gz' download> meta </a> |
+| Health_and_Household | 12.5M | 797.4K | 25.6M | 1.2B | 787.2M | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Health_and_Household.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Health_and_Household.jsonl.gz' download> meta </a> |
+| Health_and_Personal_Care | 461.7K | 60.3K | 494.1K | 23.9M | 40.3M | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Health_and_Personal_Care.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Health_and_Personal_Care.jsonl.gz' download> meta </a> |
+| Home_and_Kitchen | 23.2M | 3.7M | 67.4M | 3.1B | 3.8B | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Home_and_Kitchen.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Home_and_Kitchen.jsonl.gz' download> meta </a> |
+| Industrial_and_Scientific | 3.4M | 427.5K | 5.2M | 235.2M | 363.1M | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Industrial_and_Scientific.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Industrial_and_Scientific.jsonl.gz' download> meta </a> |
+| Kindle_Store | 5.6M | 1.6M | 25.6M | 2.2B | 1.7B | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Kindle_Store.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Kindle_Store.jsonl.gz' download> meta </a> |
+| Magazine_Subscriptions | 60.1K | 3.4K | 71.5K | 3.8M | 1.3M | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Magazine_Subscriptions.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Magazine_Subscriptions.jsonl.gz' download> meta </a> |
+| Movies_and_TV | 6.5M | 747.8K | 17.3M | 1.0B | 415.5M | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Movies_and_TV.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Movies_and_TV.jsonl.gz' download> meta </a> |
+| Musical_Instruments | 1.8M | 213.6K | 3.0M | 182.2M | 200.1M | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Musical_Instruments.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Musical_Instruments.jsonl.gz' download> meta </a> |
+| Office_Products | 7.6M | 710.4K | 12.8M | 574.7M | 682.8M | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Office_Products.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Office_Products.jsonl.gz' download> meta </a> |
+| Patio_Lawn_and_Garden | 8.6M | 851.7K | 16.5M | 781.3M | 875.1M | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Patio_Lawn_and_Garden.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Patio_Lawn_and_Garden.jsonl.gz' download> meta </a> |
+| Pet_Supplies | 7.8M | 492.7K | 16.8M | 905.9M | 511.0M | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Pet_Supplies.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Pet_Supplies.jsonl.gz' download> meta </a> |
+| Software | 2.6M | 89.2K | 4.9M | 179.4M | 67.1M | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Software.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Software.jsonl.gz' download> meta </a> |
+| Sports_and_Outdoors | 10.3M | 1.6M | 19.6M | 986.2M | 1.3B | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Sports_and_Outdoors.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Sports_and_Outdoors.jsonl.gz' download> meta </a> |
+| Subscription_Boxes | 15.2K | 641 | 16.2K | 1.0M | 447.0K | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Subscription_Boxes.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Subscription_Boxes.jsonl.gz' download> meta </a> |
+| Tools_and_Home_Improvement | 12.2M | 1.5M | 27.0M | 1.3B | 1.5B | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Tools_and_Home_Improvement.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Tools_and_Home_Improvement.jsonl.gz' download> meta </a> |
+| Toys_and_Games | 8.1M | 890.7K | 16.3M | 707.9M | 848.3M | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Toys_and_Games.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Toys_and_Games.jsonl.gz' download> meta </a> |
+| Video_Games | 2.8M | 137.2K | 4.6M | 347.9M | 137.3M | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Video_Games.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Video_Games.jsonl.gz' download> meta </a> |
+| Unknown | 23.1M | 13.2M | 63.8M | 3.3B | 232.8M | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Unknown.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Unknown.jsonl.gz' download> meta </a> |
+
+
+> Check Pure ID files and corresponding data splitting strategies in <b>[Common Data Processing](https://amazon-reviews-2023.github.io/data_processing/index.html)</b> section.
+
+## Quick Start
+
+### Load User Reviews
+
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("McAuley-Lab/Amazon-Reviews-2023", "raw_review_All_Beauty", trust_remote_code=True)
+print(dataset["full"][0])
+```
+
+```json
+{'rating': 5.0,
+ 'title': 'Such a lovely scent but not overpowering.',
+ 'text': "This spray is really nice. It smells really good, goes on really fine, and does the trick. I will say it feels like you need a lot of it though to get the texture I want. I have a lot of hair, medium thickness. I am comparing to other brands with yucky chemicals so I'm gonna stick with this. Try it!",
+ 'images': [],
+ 'asin': 'B00YQ6X8EO',
+ 'parent_asin': 'B00YQ6X8EO',
+ 'user_id': 'AGKHLEW2SOWHNMFQIJGBECAF7INQ',
+ 'timestamp': 1588687728923,
+ 'helpful_vote': 0,
+ 'verified_purchase': True}
+```
+
+### Load Item Metadata
+
+```python
+dataset = load_dataset("McAuley-Lab/Amazon-Reviews-2023", "raw_meta_All_Beauty", split="full", trust_remote_code=True)
+print(dataset[0])
+```
+
+```json
+{'main_category': 'All Beauty',
+ 'title': 'Howard LC0008 Leather Conditioner, 8-Ounce (4-Pack)',
+ 'average_rating': 4.8,
+ 'rating_number': 10,
+ 'features': [],
+ 'description': [],
+ 'price': 'None',
+ 'images': {'hi_res': [None,
+   'https://m.media-amazon.com/images/I/71i77AuI9xL._SL1500_.jpg'],
+  'large': ['https://m.media-amazon.com/images/I/41qfjSfqNyL.jpg',
+   'https://m.media-amazon.com/images/I/41w2yznfuZL.jpg'],
+  'thumb': ['https://m.media-amazon.com/images/I/41qfjSfqNyL._SS40_.jpg',
+   'https://m.media-amazon.com/images/I/41w2yznfuZL._SS40_.jpg'],
+  'variant': ['MAIN', 'PT01']},
+ 'videos': {'title': [], 'url': [], 'user_id': []},
+ 'store': 'Howard Products',
+ 'categories': [],
+ 'details': '{"Package Dimensions": "7.1 x 5.5 x 3 inches; 2.38 Pounds", "UPC": "617390882781"}',
+ 'parent_asin': 'B01CUPMQZE',
+ 'bought_together': None,
+ 'subtitle': None,
+ 'author': None}
+```
+
+> Check data loading examples and Huggingface datasets APIs in <b>[Common Data Loading](https://amazon-reviews-2023.github.io/data_loading/index.html)</b> section.
+
+
+## Data Fields
+
+### For User Reviews
+
+| Field | Type |  Explanation |
+| ----- | ---- | ----------- |
+| rating | float | Rating of the product (from 1.0 to 5.0). |
+| title  | str | Title of the user review. |
+| text   | str | Text body of the user review. |
+| images | list | Images that users post after they have received the product. Each image has different sizes (small, medium, large), represented by the small_image_url, medium_image_url, and large_image_url respectively. |
+| asin  | str | ID of the product. |
+| parent_asin | str | Parent ID of the product. Note: Products with different colors, styles, sizes usually belong to the same parent ID. The “asin” in previous Amazon datasets is actually parent ID. <b>Please use parent ID to find product meta.</b> |
+| user_id | str | ID of the reviewer |
+| timestamp | int | Time of the review (unix time) |
+| verified_purchase | bool | User purchase verification |
+| helpful_vote | int | Helpful votes of the review |
+
+### For Item Metadata
+
+| Field | Type |  Explanation |
+| ----- | ---- | ----------- |
+| main_category | str | Main category (i.e., domain) of the product. |
+| title | str | Name of the product. |
+| average_rating | float | Rating of the product shown on the product page. |
+| rating_number | int | Number of ratings in the product. |
+| features | list | Bullet-point format features of the product. |
+| description | list | Description of the product. |
+| price  | float | Price in US dollars (at time of crawling). |
+| images | list |  Images of the product. Each image has different sizes (thumb, large, hi_res). The “variant” field shows the position of image. |
+| videos | list | Videos of the product including title and url. |
+| store | str | Store name of the product. |
+| categories | list | Hierarchical categories of the product. |
+| details | dict | Product details, including materials, brand, sizes, etc. |
+| parent_asin | str | Parent ID of the product. |
+| bought_together | list | Recommended bundles from the websites. |
+
+## Citation
+
+```bibtex
+@article{hou2024bridging,
+  title={Bridging Language and Items for Retrieval and Recommendation},
+  author={Hou, Yupeng and Li, Jiacheng and He, Zhankui and Yan, An and Chen, Xiusi and McAuley, Julian},
+  journal={arXiv preprint arXiv:2403.03952},
+  year={2024}
+}
+```
+
+## Contact Us
+
+- **Report Bugs**: To report bugs in the dataset, please file an issue on our [GitHub](https://github.com/hyp1231/AmazonReviews2023/issues/new).
+
+- **Others**: For research collaborations or other questions, please email **yphou AT ucsd.edu**.
\ No newline at end of file
diff --git a/all_categories.txt b/all_categories.txt
new file mode 100644
index 0000000000000000000000000000000000000000..360a48180afefde76695e0248398fc87fb421b39
--- /dev/null
+++ b/all_categories.txt
@@ -0,0 +1,34 @@
+All_Beauty
+Toys_and_Games
+Cell_Phones_and_Accessories
+Industrial_and_Scientific
+Gift_Cards
+Musical_Instruments
+Electronics
+Handmade_Products
+Arts_Crafts_and_Sewing
+Baby_Products
+Health_and_Household
+Office_Products
+Digital_Music
+Grocery_and_Gourmet_Food
+Sports_and_Outdoors
+Home_and_Kitchen
+Subscription_Boxes
+Tools_and_Home_Improvement
+Pet_Supplies
+Video_Games
+Kindle_Store
+Clothing_Shoes_and_Jewelry
+Patio_Lawn_and_Garden
+Unknown
+Books
+Automotive
+CDs_and_Vinyl
+Beauty_and_Personal_Care
+Amazon_Fashion
+Magazine_Subscriptions
+Software
+Health_and_Personal_Care
+Appliances
+Movies_and_TV
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