TDA-RC: Task-Driven Alignment for Knowledge-Based Reasoning Chains in Large Language Models

TDA-RC introduces a task-driven alignment approach for optimizing knowledge-based reasoning chains in LLMs. The paper addresses a core challenge in LLM reasoning: enabling reliable multi-step inference by aligning model behavior to task-specific objectives. This contributes to broader efforts to improve LLM reasoning capabilities and alignment.