most citedSelf-Supervised Contrastive BERT Fine-tuning for Fusion-based Reviewed-Item Retrieval

5 citations · 5 across the 5 of their papers we have counts for

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cs.LG2025

SCOUT: Toward Sub-Quadratic Attention via Segment Compression for Optimized Utility in Transformers

Aref Jafari, Yuhe Fan, Benyamin Jamialahmadi +3

Transformers have demonstrated strong performance across a wide range of sequence modeling tasks, but their quadratic attention complexity limits scalability to long sequences. Lin…

cs.LG2025

DTRNet: Dynamic Token Routing Network to Reduce Quadratic Costs in Transformers

Aman Sharma, Saeed Najafi, Parsa Farinneya +6

Transformers achieve state-of-the-art results across many tasks, but their uniform application of quadratic self-attention to every token at every layer makes them computationally…