Running Reproduction: Reward-free Alignment for Conflicting Objectives π― Explore project logs, traces, and workspace with agent collaboration
Running Reproduction: On Structured State-Space Duality π― Explore project logs, traces, and workspace in a single view
Running Reproduction: Attention's forward pass and Frank-Wolfe π― Explore logs, view code/traces, and collaborate with an AI agent
Running Reproduction: A Tight Theory of Error Feedback Algorithms in Distributed Optimization π― Explore project logbook with code, traces, and AI collaboration
Running Reproduction: Measuring Agents in Production π― Explore project logs, traces, and workspace in an interactive web UI
Running Reproduction: Ski Rental with Distributional Predictions of Unknown Quality π― Explore research logbooks and collaborate with a coding agent
Running Reproduction: Who Said Neural Networks Aren't Linear? π― Explore and share experiment logs with an interactive UI
Running Reproduction: A Coin Flip for Safety: LLM Judges Fail to Reliably Measure Adversarial Robustness π― Explore experiment logs, traces, and workspace in a unified view
Runtime error Agents LlamaPIE Dual Inference CPU π’ LlamaPIE pipeline (1B Classifier + 8B Generator in GGUF form
Sleeping Agents LlamaPIE Dual Inference CPU π’ LlamaPIE pipeline (1B Classifier + 8B Generator in GGUF form
Sleeping Agents LlamaPIE Dual Inference CPU π’ LlamaPIE pipeline (1B Classifier + 8B Generator in GGUF form
Runtime error Agents LlamaPIE-Dual-Inference 1 π¨ LlamaPIE is explicitly a two-model pipeline (small βwhen to