The Silicon Mirror: Dynamic Behavioral Gating for Anti-Sycophancy in LLM Agents

arXiv:2605.05403v1 Announce Type: new Abstract: This position paper argues that sycophancy in LLMs is a boundary failure between social alignment and epistemic integrity. Existing

arXiv:2610.02568v1 Announce Type: new Abstract: Personal advice, including relationship advice, now ranks among the most common uses of generative AI. But language models (LMs)

arXiv:2603.23406v1 Announce Type: new Abstract: While large language models simulate social behaviors, their capacity for stable stance formation and identity negotiation during

arXiv:2610.04083v1 Announce Type: new Abstract: Memory poisoning attacks on LLM agents typically assume an external adversary who plants content in the agent's persistent memory

arXiv:2604.05279v1 Announce Type: new Abstract: Large language models exhibit sycophancy, the tendency to shift their stated positions toward perceived user preferences or

arXiv:2603.18743v1 Announce Type: new Abstract: We introduce \emph{Memento-Skills}, a generalist, continually-learnable LLM agent system that functions as an \emph{agent-designing

arXiv:2603.25747v1 Announce Type: new Abstract: The rapid evolution of Large Multimodal Models (LMMs) has enabled agents to perform complex digital and physical tasks, yet their

<!-- SC_OFF --><div class="md"><p>I published a model you can use now to help detect sycophantic AI responses. It rejects 100% of the sycophantic delusion affirming responses from