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Across two backbones and five benchmarks, EDIC improves both safety and utility over the strongest prior defense, lifting harmful-rejection by up to 7.7\% and Arena-Hard-Auto utility by 12.5\% on Qwen3-4B.
HEIMAT, a HEurIstic-style autoMATic debiasing framework for LMs, effectively mitigates bias in different cultures while maintaining the model's natural language understanding (NLU) performance.
PivoARL is proposed, a self-feedback retry framework for experience exploitation in LLM agents that identifies the pivotal erroneous turn through structured reflection and performs local retry only from the corresponding pivotal state, thereby reusing the correct prefix and reducing redundant interactions.
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