Which Objectives Need a Dial? Predicting Objective Conflict and Covering Trade-offs in Steerable Pluralistic Alignment

arXiv:2609.26929 · cs.AI, cs.CL, cs.CY · Submitted 2026-09-22 · Read on arXiv

cs.AI, cs.CL, cs.CY

Submitted: 2026-09-22

Updated: 2026-09-22

Code: https://github.com/esradonmez/modpo-objective-trade-off

Terminology

• Alignment — 28× in this paper · explained in 1 episode
• International Conference on Machine Learning — 5× in this paper
• Decode — 4× in this paper · explained in 2 episodes
• Steering — 4× in this paper · explained in 2 episodes
• Adaptation — 2× in this paper · explained in 1 episode
• Consistency — 2× in this paper · explained in 3 episodes
• Fine-Tuning — 2× in this paper · explained in 5 episodes
• LoRA Adapters — 2× in this paper · explained in 3 episodes
• Reinforcement Learning — 2× in this paper · explained in 4 episodes
• AI Alignment — 1× in this paper · explained in 2 episodes
• Accuracy — 1× in this paper · explained in 1 episode
• Adam — 1× in this paper · explained in 2 episodes
• Benchmark — 1× in this paper · explained in 2 episodes
• Eleventh International Conference on Learning Representations — 1× in this paper
• Fidelity — 1× in this paper · explained in 2 episodes
• Foundation Model — 1× in this paper · explained in 3 episodes
• Foundation Models — 1× in this paper · explained in 7 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• LLM-as-a-Judge — 1× in this paper · explained in 3 episodes
• Scaling Laws — 1× in this paper · explained in 4 episodes
• Supervised Fine-Tuning (SFT) — 1× in this paper · explained in 8 episodes
• Trace — 1× in this paper · explained in 2 episodes
• alpha — 1× in this paper · explained in 1 episode

Sources

• Structuring the Space of Sociotechnical Alignment
• Misaligned by Reward: Socially Undesirable Preferences in LLMs
• Llama 2: Open Foundation and Fine-Tuned Chat Models

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