Causal Memory Intervention selects memories based on estimated causal impact on LLM answers rather than semantic similarity, with a new benchmark showing improved robustness to irrelevant or harmful memories.
Proceedings of the 36th Annual ACM Symposium on User Interface Software and Technology , year =
2 Pith papers cite this work. Polarity classification is still indexing.
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cs.AI 2years
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UNVERDICTED 2representative citing papers
Twelve LLM agents in a 12 Angry Men jury setup almost always end in hung juries due to anchoring, with Llama-4-Scout showing more vote changes than GPT-4o, suggesting RLHF alignment intensity limits deliberative flexibility.
citing papers explorer
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Causal Intervention-Based Memory Selection for Long-Horizon LLM Agents
Causal Memory Intervention selects memories based on estimated causal impact on LLM answers rather than semantic similarity, with a new benchmark showing improved robustness to irrelevant or harmful memories.
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12 Angry AI Agents: Evaluating Multi-Agent LLM Decision-Making Through Cinematic Jury Deliberation
Twelve LLM agents in a 12 Angry Men jury setup almost always end in hung juries due to anchoring, with Llama-4-Scout showing more vote changes than GPT-4o, suggesting RLHF alignment intensity limits deliberative flexibility.