AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
We have 7 of 20 papers
We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.
Not the right person? Other researchers publish under this name.
Looped transformers have demonstrated promising parameter efficiency by reusing layers for latent computation. Prior studies compare looped and non-looped models at matched parameters or per-token FLOPs. However, to the best of our knowledge, whether looping improves test-time scaling as outputs grow longer remains und...
Draft-OPD, which uses target-assisted rollout for stable continuations and replays drafting from the verification-exposed error positions, allowing the drafter to learn from target feedback on both accepted and rejected proposals, focusing on the draft-induced errors that limit speculative acceptance.
Value Flattening is identified as an important yet overlooked failure mode of critic learning in standard PPO and a simple sparse supervision strategy can mitigate it; SParse Proximal Policy Optimization is introduced, which applies the value loss to only a few well-separated states in each response to mitigate both ef...
OpenMLE is introduced, an open full-stack system for RSI research in MLE, spanning verifiable task environments with execution feedback, operator learning, and long-horizon search (OpenMLE-Evo) and enabling reproducible research on executable AI4AI toward RSI.
The routed-state interface unifies contextual memory and persistent capability adaptation within the model's native computation, reframing memory from a passive record of prior context into an active substrate for maintaining and evolving model behavior.
Memory-Anchor Routing across Context History (MARCH), a network architecture that effectively scales state-space models beyond a fixed-size dimension, while maintaining computational efficiency over long-sequences, is introduced.
This work introduces a student reference KL loss and mask the advantages of special termination tokens to mitigate the problem of excessive generation length and frequent truncation, and improves on science benchmarks such as HLE and HiPhO, suggesting that OPD transfers reasoning capabilities that generalize beyond the...
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.