2 papers
cs.LG2026
Match the Distribution, Not the Compute: Post-Training Multi-Token Prediction Heads
Prachi Badarayani, Aidan Jay, Chenghui Zhou +8
Multi-token prediction (MTP) improves the throughput of autoregressive generation by enabling the language model to draft multiple next tokens per forward pass, while a verificatio…
cs.IR2025
Beyond Contrastive Learning: Synthetic Data Enables List-wise Training with Multiple Levels of Relevance
Reza Esfandiarpoor, George Zerveas, Ruochen Zhang +3
Although synthetic data has changed various aspects of information retrieval (IR) pipelines, the main training paradigm remains: contrastive learning with binary relevance labels,…