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arXiv AI By Kapil Wanaskar, Gaytri Jena, Vinija Jain, Aman Chadha, Amitava Das

ECLIPTICA -- A Framework for Switchable LLM Alignment via CITA - Contrastive Instruction-Tuned Alignment

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ECLIPTICA is a framework that makes large language model alignment instruction‑driven and runtime‑controllable, allowing natural‑language alignment instructions to modulate behavior on the fly. It introduces Contrastive Instruction‑Tuned Alignment (CITA), which combines supervised fine‑tuning with contrastive preference optimization anchored to a reference model, ensuring stable policy updates within a shared neighborhood. The authors release an ECLIPTICA benchmark of 3,000 controlled cases and demonstrate that CITA achieves 86.7% instruction‑alignment efficiency on Llama‑3.1‑8B, outperforming DPO, GRPO, and PPO.

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