Papers with self-monitor

2 papers
Think Twice, Generate Once: Safeguarding by Progressive Self-Reflection (2025.findings-emnlp)

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Challenge: Large language models generate coherent and contextually relevant text, but their deployment raises significant concerns about the potential for harmful or inappropriate content.
Approach: They propose a novel inference-time technique that empowers LLMs to self-monitor and correct their outputs dynamically.
Outcome: The proposed method reduces the attack success rate from 77.47% to 5.86%, to Llama-3.1-8B base from 89.70% to 5.56%, and to Qwen2.5-7B-Instruct from 44.44% to 3.84%, without additional training.
Adaptive Platt Scaling with Causal Interpretations for Self-Reflective Language Model Uncertainty Estimates (2025.findings-emnlp)

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Challenge: a new study examines the ability of large language models to self-monitor and ask for human intervention.
Approach: They propose a formal analysis of LLM self-reflection for uncertainty estimation using domain adaptation theory.
Outcome: The proposed method improves accuracy and human interpretation on reasoning tasks.

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