A proposed pipeline shows LLMs introduce detectable race and gender biases when summarizing life narratives, creating potential for representational harm in research.
Biometrics Bulletin , volume=
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
years
2026 3verdicts
UNVERDICTED 3representative citing papers
AI agents on Moltbook reflect the specific behavioral traits of their linked human owners across multiple dimensions, with stronger transfer linked to greater privacy risks.
MTG-Causal-RL is a new benchmark for causal RL using Magic: The Gathering with an explicit SCM, five archetypes, and CGFA-PPO agent showing competitive win rates plus diagnostic metrics.
citing papers explorer
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Whose Story Gets Told? Positionality and Bias in LLM Summaries of Life Narratives
A proposed pipeline shows LLMs introduce detectable race and gender biases when summarizing life narratives, creating potential for representational harm in research.
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Behavioral Transfer in AI Agents: Evidence and Privacy Implications
AI agents on Moltbook reflect the specific behavioral traits of their linked human owners across multiple dimensions, with stronger transfer linked to greater privacy risks.
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Causal Reinforcement Learning for Complex Card Games: A Magic The Gathering Benchmark
MTG-Causal-RL is a new benchmark for causal RL using Magic: The Gathering with an explicit SCM, five archetypes, and CGFA-PPO agent showing competitive win rates plus diagnostic metrics.