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Sparse autoencoders (SAEs) are increasingly used not only to interpret language models but also to intervene on their internal representations. We show that this creates a supply-chain attack surface: a maliciously modified SAE can induce attacker-chosen behavior when inserted into the forward pass of an otherwise unch...
Personas are widely used to represent users' motivations, goals, and needs, yet the perspectives of underrepresented groups are rarely addressed in human-centered design. Large Language Models (LLMs) promise to generate personas from vast datasets, but achieving genuine diversity and accurate representation requires de...
It is suggested that repair budgets should be treated as an explicit experimental variable, as they directly affect evaluation outcomes, computational cost, runtime, and reproducibility in LLM-based software engineering research.
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