The paper characterizes deductive stereotyping in LLMs and introduces Fair-GCG to discover injection phrases that improve fairness across benchmarks, reasoning, and real-world tasks.
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4 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
years
2026 4verdicts
UNVERDICTED 4representative citing papers
Generative AI advertising is reframed as a problem of trustworthy commercial intervention on the generative process, with a taxonomy of influence tiers from product mentions to long-term preference shaping.
In untrusted strategic settings with unreliable measurements, the quantum primitive for output-hiding function sharing permits parties to generate private unbiased coins.
Proposes a quantum primitive for output-hiding function sharing with applications to enhanced QKD security and hidden joint function encoding.
citing papers explorer
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Wait, am I Being Fair? Characterizing Deductive Stereotyping and Mitigating It with Fair-GCG
The paper characterizes deductive stereotyping in LLMs and introduces Fair-GCG to discover injection phrases that improve fairness across benchmarks, reasoning, and real-world tasks.
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Generative AI Advertising as a Problem of Trustworthy Commercial Intervention
Generative AI advertising is reframed as a problem of trustworthy commercial intervention on the generative process, with a taxonomy of influence tiers from product mentions to long-term preference shaping.
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Quantum Primitive for Output-Hiding Function Sharing: Strategic Settings
In untrusted strategic settings with unreliable measurements, the quantum primitive for output-hiding function sharing permits parties to generate private unbiased coins.
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Quantum Primitive for Output-Hiding Function Sharing: QKD and Joint Computation Applications
Proposes a quantum primitive for output-hiding function sharing with applications to enhanced QKD security and hidden joint function encoding.