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Reinforced Fast Weights with Next-Sequence Prediction

Intermediate

Hee Seung Hwang, Xindi Wu et al.Feb 18arXiv

Fast weight models remember context with a tiny, fixed memory, but standard next-token training teaches them to think only one word ahead.

#fast weight models#next-sequence prediction#reinforcement learning for LMs

LycheeDecode: Accelerating Long-Context LLM Inference via Hybrid-Head Sparse Decoding

Intermediate

Gang Lin, Dongfang Li et al.Feb 4arXiv

Long texts make language models slow because they must keep and re-check a huge memory called the KV cache for every new word they write.

#long-context LLM#sparse attention#head specialization

Recursive Language Models

Beginner

Alex L. Zhang, Tim Kraska et al.Dec 31arXiv

Recursive Language Models (RLMs) let an AI read and work with prompts that are much longer than its normal memory by treating the prompt like a big external document it can open, search, and study with code.

#Recursive Language Models#RLM#Long-context reasoning

Papers3

Reinforced Fast Weights with Next-Sequence Prediction

LycheeDecode: Accelerating Long-Context LLM Inference via Hybrid-Head Sparse Decoding

Recursive Language Models