Adversarial Retriever-Ranker for dense text retrieval

Understand

Current dense text retrieval models face two typical challenges.

• First, they adopt a siamese dual-encoder architecture to encode queries and documents independently for fast indexing and searching, while neglecting the finer-grained term-wise interactions.
• This results in a sub-optimal recall performance.
• Second, their model training highly relies on a negative sampling technique to build up the negative documents in their contrastive losses.