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Recurrent Transformers let you trade model depth for width, slashing KV cache memory footprint and inference latency without sacrificing performance.
Ditch the task-specific verifier: energy-based fine-tuning (EBFT) lets you directly optimize sequence-level behavior in LMs, beating SFT and matching RLVR in downstream tasks.
