Linear probes on coding-agent residual streams decode current program properties (AUC up to 0.83) and predict future edit outcomes up to 25 steps in advance.
Laguna M.1/XS.2 Technical Report
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
abstract
We present Laguna M.1 and Laguna XS.2, two Mixture-of-Experts foundation models built for long-horizon, agentic coding: M.1 has $225.8$B total parameters ($23.4$B activated per token) and XS.2 has $33.4$B total ($3$B activated). Both models were trained from scratch end-to-end inside the same internal system that we refer to as our Model Factory: a tightly-integrated stack of versioned data, training, evaluation, and inference components that turn model development into an industrial process. We describe the principles and design choices of the Model Factory and also detail the end-to-end training process of our models, throughout pre-training data and architecture, post-training stages, evaluation, and quantization. On agentic software engineering and terminal benchmarks (SWE-bench Verified, SWE-bench Multilingual, SWE-Bench Pro, and Terminal-Bench 2.0) M.1 and XS.2 are competitive with state-of-the-art open models in their respective weight classes. Laguna XS.2 weights are released under Apache~2.0 at https://huggingface.co/collections/poolside/laguna-xs2.
fields
cs.LG 2years
2026 2representative citing papers
Aurora is a leverage-aware spectral optimizer that enforces uniform row norms in matrix updates while preserving Muon's polar geometry, outperforming Muon and achieving SOTA among spectral methods on modded-nanoGPT.
citing papers explorer
-
Latent Programming Horizons in Coding Agents
Linear probes on coding-agent residual streams decode current program properties (AUC up to 0.83) and predict future edit outcomes up to 25 steps in advance.
-
Aurora: A Leverage-Aware Spectral Optimizer
Aurora is a leverage-aware spectral optimizer that enforces uniform row norms in matrix updates while preserving Muon's polar geometry, outperforming Muon and achieving SOTA among spectral methods on modded-nanoGPT.