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Announcing SimReady Central: An Open Library of Simulation-Ready 3D Assets for Robotics and AI Factories58m◆An AI Security Agent for University ACMIS: Multi-Vector Threat Detection and Automated Response7h◆Learning Transferable Latent User Preferences for Human-Aligned Decision Making7h◆Repair the Core, Not the Symptom: Planning-Graph Repair for Long-Horizon Agents7h◆IndustryForge-27B: A Domain-Enhanced Multimodal Foundation Model for Industrial CAD7h◆Ethical LLM-Assisted Research: A Framework for Responsible Delegation, Verification, and Epistemic Value7h◆PALATE: Peculiar Application of the Law of Total Expectation to Enhance the Evaluation of Deep Generative Models7h◆WoW-Bench: Evaluating Fine-Grained Acoustic Perception in Audio-Language Models via Marine Mammal Vocalizations7h◆When Synthetic Speech Is All You Have: Better Call GRPO7h◆Reducing belief in conspiracy theories as they unfold using large language models7h◆Harnessing Magnitude-Only and Complex Measurements for Improved Dynamic MRI Reconstruction with Learned Priors7h◆EDISCO: Equivariant DIScrete Diffusion for Euclidean Combinatorial Optimization7h◆Composing What Each Teacher Learned: Delta Distillation for Multi-Teacher On-Policy Learning7h◆CRISP: Fixing Flying Pixels in Latent LiDAR Generation via Diffusion Decoding7h◆WeGR: Towards Unified Generative Retrieval via Behavior-aware Tokenization and Preference Alignment7h◆StartLux-Decision: AutoThink Decision Models with Reinforcement Learning for Calibrated Deliberative Decisions7h◆Many Steps into One: Reasoning Contraction and the Limits of Safe Memory Reuse for LLM Agents7h◆Secure Agentic Coding through Counterexample-Grounded Feedback7h◆Policy Search in Code Space for Multi-Agent Pathfinding7h◆TamedFlow: Trajectory-Aware Distillation for Teacher-Assisted Diffusion Sampling7h◆Announcing SimReady Central: An Open Library of Simulation-Ready 3D Assets for Robotics and AI Factories58m◆An AI Security Agent for University ACMIS: Multi-Vector Threat Detection and Automated Response7h◆Learning Transferable Latent User Preferences for Human-Aligned Decision Making7h◆Repair the Core, Not the Symptom: Planning-Graph Repair for Long-Horizon Agents7h◆IndustryForge-27B: A Domain-Enhanced Multimodal Foundation Model for Industrial CAD7h◆Ethical LLM-Assisted Research: A Framework for Responsible Delegation, Verification, and Epistemic Value7h◆PALATE: Peculiar Application of the Law of Total Expectation to Enhance the Evaluation of Deep Generative Models7h◆WoW-Bench: Evaluating Fine-Grained Acoustic Perception in Audio-Language Models via Marine Mammal Vocalizations7h◆When Synthetic Speech Is All You Have: Better Call GRPO7h◆Reducing belief in conspiracy theories as they unfold using large language models7h◆Harnessing Magnitude-Only and Complex Measurements for Improved Dynamic MRI Reconstruction with Learned Priors7h◆EDISCO: Equivariant DIScrete Diffusion for Euclidean Combinatorial Optimization7h◆Composing What Each Teacher Learned: Delta Distillation for Multi-Teacher On-Policy Learning7h◆CRISP: Fixing Flying Pixels in Latent LiDAR Generation via Diffusion Decoding7h◆WeGR: Towards Unified Generative Retrieval via Behavior-aware Tokenization and Preference Alignment7h◆StartLux-Decision: AutoThink Decision Models with Reinforcement Learning for Calibrated Deliberative Decisions7h◆Many Steps into One: Reasoning Contraction and the Limits of Safe Memory Reuse for LLM Agents7h◆Secure Agentic Coding through Counterexample-Grounded Feedback7h◆Policy Search in Code Space for Multi-Agent Pathfinding7h◆TamedFlow: Trajectory-Aware Distillation for Teacher-Assisted Diffusion Sampling7h◆

News/model/Laguna-S-2.1-Uncensored-APEX-GGUF

Laguna-S-2.1-Uncensored-APEX-GGUF news

1 articles mentioning Laguna-S-2.1-Uncensored-APEX-GGUF

arxivMay 28

Laguna M.1/XS.2 Technical Report

arXiv:2605.27605v1 Announce Type: new 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 traine

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