Himanshu Dutta

HOBIT: Hardness Optimized Batch Sampling for InfoNCE Training

Contrastive training with InfoNCE loss and in-batch negatives is the standard approach for learning dual-encoder models. Its effectiveness, however, critically depends on the availability of hard negatives; in their absence, learning quickly saturates. Existing methods address this via explicit hard…