AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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DiDi-Merging is proposed, which jointly allocates low-rank capacity to these components through differentiable rank selection, followed by data-free parameter-space refinement, followed by data-free parameter-space refinement.
Vision-language-action (VLA) models can learn a wide range of robotic skills, but combining separately trained skills remains challenging. The original training data may be unavailable for joint retraining, while directly merging model weights can cause interference. We propose NestedVLA, which consolidates independent...
Speculative decoding accelerates autoregressive generation by using a lightweight draft model to propose multiple tokens that are verified by a target model in parallel. However, the standard acceptance rule focuses on exact distribution correction and rejects tokens that remain highly plausible under the target model...
A three-stage calibration framework that evaluates confidence before, during, and after chain-of-thought generation, corresponding to difficulty estimation, early termination, and answer aggregation finds that OPD provides the most useful pre-reasoning confidence, SFT gives the strongest online signal for early stoppin...
A three-stage calibration framework that evaluates confidence before, during, and after chain-of-thought generation, corresponding to difficulty estimation, early termination, and answer aggregation finds that OPD provides the most useful pre-reasoning confidence, SFT gives the strongest online signal for early stoppin...
This work introduces AgentSnare, a trajectory-adaptive deception system that dynamically unfolds a decoy environment to continually steer the penetration agent away from the real target.
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