Prompt-Robust Language Models: Which Training Strategies Work?

arXiv:2609.01217 · cs.AI · Submitted 2026-09-01 · Read on arXiv

cs.AI

Submitted: 2026-09-01

Updated: 2026-09-01

Code: https://github.com/FSadrieh/prompt-agnostic-llms

Terminology

• Robustness — 32× in this paper · explained in 5 episodes
• Consistency — 12× in this paper · explained in 3 episodes
• Accuracy — 10× in this paper · explained in 1 episode
• Regularization — 8× in this paper · explained in 3 episodes
• Alignment — 7× in this paper · explained in 1 episode
• Benchmark — 5× in this paper · explained in 2 episodes
• Cosine Similarity — 5× in this paper · explained in 3 episodes
• Generalization — 4× in this paper · explained in 13 episodes
• In-Context Learning — 4× in this paper · explained in 4 episodes
• Fine-Tuning — 3× in this paper · explained in 5 episodes
• Loss Function — 3× in this paper · explained in 2 episodes
• In-Context Learning (ICL) — 2× in this paper · explained in 5 episodes
• Instruction Tuning — 2× in this paper · explained in 2 episodes
• Prompt Engineering — 2× in this paper · explained in 4 episodes
• Adam — 1× in this paper · explained in 2 episodes
• Adaptation — 1× in this paper · explained in 1 episode
• Calibration — 1× in this paper · explained in 7 episodes
• Combinatorial Optimization — 1× in this paper · explained in 2 episodes
• Generalizability — 1× in this paper · explained in 6 episodes
• Large Language Models (LLMs) — 1× in this paper · explained in 6 episodes
• LoRA Adapters — 1× in this paper · explained in 3 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Trace — 1× in this paper · explained in 2 episodes
• alpha — 1× in this paper · explained in 1 episode

Sources

• The Llama 3 Herd of Models
• Does Prompt Formatting Have Any Impact on LLM Performance?
• The Prompt Report: A Systematic Survey of Prompt Engineering Techniques
• Auto-Prompt Generation is Not Robust: Prompt Optimization Driven by Pseudo Gradient
• CREME: Robustness Enhancement of Code LLMs via Layer-Aware Model Editing
• Qwen3 Technical Report

Related papers

• MAVEN-T: Reinforced Heterogeneous Distillation for Real-Time Multi-Agent Trajectory Prediction
• Model Discovery Agent: LLM-assisted Bayesian experiment design for data-efficient discovery of mechanistic world models
• The Clinician's Veto: Navigating Trust, Liability, and Uncertainty in Autonomous AI Prescribing
• MindHelper: Closed-Loop Embodied Mental-State Reasoning for Precision Intervention
• Incumbent Advantage: Brand Bias and Cognitive Manipulation Dynamics in LLM Recommendation Systems
• VSAL: A Vision Solver with Adaptive Layouts for Graph Property Detection