Exact And Fuzzy Duplicate Detection And Removal

via “duplicate detection and deduplication across embeddings”

Open-source embedding models with full transparency.

Unique: Implements semantic deduplication using embedding similarity rather than string matching, enabling detection of paraphrased or reformatted duplicates. Integrates with Atlas visualization to show duplicate clusters interactively.

vs others: Detects semantic duplicates that string-based tools (fuzzy matching, exact hashing) would miss, and provides interactive exploration of duplicate groups rather than just lists.

Dataset by allenai. 7,61,810 downloads.

Unique: C4 combines exact and fuzzy deduplication in a two-stage pipeline, using MinHash for efficient approximate matching at scale. The approach is fully reproducible and the thresholds are published, allowing researchers to audit or adjust deduplication aggressiveness. This is more sophisticated than simple exact-match deduplication but simpler than learned semantic deduplication models.

vs others: C4's two-stage deduplication is more scalable and transparent than semantic deduplication models, while catching more duplicates than exact-match-only approaches, making it practical for petabyte-scale datasets.

via “duplicate-product-detection”