Alignment & Reasoning

Alignment & Reasoning #

  1. Alignment: Ensuring AI systems behave in ways that reflect human intent — safely, reliably, and ethically.
  2. Reasoning: Providing structural tools and methods that guide model thinking, improve transparency, and support meaningful generalization.

These aren’t separate concerns — in modern AI workflows, alignment depends on structured reasoning, and reasoning is guided by the goal of human alignment.

  • RLHF (Reinforcement Learning from Human Feedback)
    • Reward modeling
    • Preference data collection
    • Proximal Policy Optimization (PPO) fine-tuning
  • DPO (Direct Preference Optimization)
    • Simplified alternative to RLHF using pairwise ranking
  • Causality
    • Structural causal models
    • Counterfactuals and interventions
    • Causal inference in ML and AI safety
  • Graph-Based Reasoning
    • GraphRAG (Graph-enhanced Retrieval-Augmented Generation)
      • Knowledge graph-guided retrieval pipelines
      • Interpretable memory structures
    • Knowledge Graphs
      • Ontologies and structured semantic reasoning
      • Context-aware generation in LLMs