AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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KV-streams is proposed, a plug-and-play strategy compatible with any compaction strategy that substantially increases throughput while showing no evidence of hindering performance, and is shown to be an efficient and lightweight plug-and-play addition to any post-training pipeline.
R-Qwen is a recursive reasoning framework built upon a pretrained Qwen backbone, which consistently outperforms prior recursive reasoning models and substantially larger LLMs while using a comparable number of trainable parameters, suggesting that recursive reasoning mechanisms and pretrained language model priors are...
This work interprets chain-of-thought reasoning as a latent variable modeling problem and demonstrates that this distribution-matching paradigm of LLM fine-tuning can serve as an effective alternative to maximum-likelihood training and reward-maximizing policy optimization.
A new algorithm for amortized inference in sparse probabilistic graphical models (PGMs) is presented that enables off-policy training but avoids the need to instantiate all the random variables for each parameter update, thus speeding up training considerably.
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