2.1 KiB
Submitted Proposals
Crimson Leaf -- Task 8f43dee3-ed7e-448c-89b6-75116f2fcd6f
Date: 2026-04-29 Status: AWAITING DAVID'S APPROVAL Summary: This proposal outlines the development of a specialized suite of model probe tasks designed to stress-test LLM reasoning and internal world models. It fills the current gap in granular performance metrics for agentic behavior. Unlike previous submissions, this plan introduces a dynamic scoring system that adapts to the complexity of the specific Foreman-generated task.
Crimson Leaf -- Task 074623e4-fa2a-43bd-a33f-3f6bba03a26b
Date: 2026-04-29 Status: AWAITING DAVID'S APPROVAL Summary: This proposal introduces a modular framework for evaluating LLMs across multiple dimensions of reasoning, including logical deduction, causal inference, and ethical alignment. It addresses the lack of a comprehensive, multi-faceted evaluation system and builds upon previous submissions by incorporating real-time feedback loops to refine task difficulty and measurement accuracy.
Crimson Leaf -- Task 2ec93d32-4159-44bf-b989-d1da04df3a2b
Date: 2026-04-29 Status: AWAITING DAVID'S APPROVAL Summary: This proposal details a comprehensive company plan for Crimson Leaf, focusing on the Foreman Probe project to create advanced model probe tasks for benchmarking LLM capabilities. It fills the gap in structured organizational strategies for AI evaluation initiatives. Unlike prior task-specific proposals, this one provides a high-level company framework integrating all ongoing projects under a unified vision.
Crimson Leaf -- Task 1eb17144-5663-4ddb-bab9-5f3364f8bc17
Date: 2026-04-29 Status: AWAITING DAVID'S APPROVAL Summary: This proposal aims to benchmark and evaluate LLM capabilities through a series of Foreman probe tasks. The objective is to create detailed and dynamic benchmarks that go beyond static assessments, focusing on the real-time adaptability and effectiveness of the LLM in varied complex scenarios. It serves to bridge the gap in dynamic and iterative evaluation tactics for advanced language models and builds on previous static proposals by offering enhanced, iterative evaluation mechanisms.