Parameters vs. Context: TRACE Fine-Tuning for Robust Retrieval-Augmented Generation

arXiv:2609.30337 · cs.LG · Submitted 2026-09-24 · Read on arXiv

cs.LG

Submitted: 2026-09-24

Updated: 2026-09-24

Terminology

• Trace — 118× in this paper · explained in 2 episodes
• RAG — 50× in this paper · explained in 3 episodes
• Fine-Tuning — 29× in this paper · explained in 5 episodes
• Regularization — 27× in this paper · explained in 3 episodes
• Retrieval-Augmented Generation — 9× in this paper
• Robustness — 9× in this paper · explained in 5 episodes
• GRPO — 8× in this paper · explained in 6 episodes
• Ablation — 6× in this paper · explained in 1 episode
• Benchmark — 5× in this paper · explained in 2 episodes
• Hallucination — 3× in this paper · explained in 3 episodes
• Knowledge Graph — 3× in this paper · explained in 7 episodes
• Ablation study — 2× in this paper · explained in 1 episode
• Reinforcement Learning — 2× in this paper · explained in 4 episodes
• Retrieval-Augmented Generation (RAG) — 2× in this paper · explained in 16 episodes
• Ablation Studies — 1× in this paper · explained in 1 episode
• Accuracy — 1× in this paper · explained in 1 episode
• Adaptation — 1× in this paper · explained in 1 episode
• Consistency — 1× in this paper · explained in 3 episodes
• Core — 1× in this paper · explained in 2 episodes
• Exponential Moving Average (EMA) — 1× in this paper · explained in 2 episodes
• Knowledge graphs — 1× in this paper · explained in 2 episodes
• Large Language Models (LLMs) — 1× in this paper · explained in 6 episodes
• LoRA Fine-Tuning — 1× in this paper · explained in 3 episodes
• Multi-hop Reasoning — 1× in this paper · explained in 3 episodes
• Reasoning Traces — 1× in this paper · explained in 3 episodes

Sources

• OpenAI GPT-5 System Card
• LLaMA: Open and Efficient Foundation Language Models
• Retrieval-Augmented Generation for Large Language Models: A Survey
• Corrective Retrieval Augmented Generation
• Certifiably Robust RAG against Retrieval Corruption

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