Context-Fidelity Boosting reduces faithfulness hallucinations by applying context-based logit boosts to source-supported tokens during LLM decoding.
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Memory Inception is a training-free method that injects latent KV banks at chosen layers to steer LLMs, achieving superior control-drift balance and up to 118x storage reduction on personality and structured-reasoning tasks.
citing papers explorer
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Context-Fidelity Boosting: Enhancing Faithful Generation through Watermark-Inspired Decoding
Context-Fidelity Boosting reduces faithfulness hallucinations by applying context-based logit boosts to source-supported tokens during LLM decoding.
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Memory Inception: Latent-Space KV Cache Manipulation for Steering LLMs
Memory Inception is a training-free method that injects latent KV banks at chosen layers to steer LLMs, achieving superior control-drift balance and up to 118x storage reduction on personality and structured-reasoning tasks.