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Mnemon uses raw, dated records and divides memory into fast System 1 and slow System 2 work. It scores 91.7% on LoCoMo and 83.8% on LongMemEval-S using gpt-4.1-mini.
Source: arXiv cs.CL
https://arxiv.org/abs/2609.36059
#MachineLearning
CruxBench evaluates information discovery in large language models by grading generated questions using Value of Information. Frontier models only narrowly outperform a random-timing baseline.
Source: arXiv cs.CL
https://arxiv.org/abs/2609.35879
#MachineLearning
Researchers introduced SCOUT, a two-stage agentic safety verifier for computer-use agents that synergizes reasoning-intensive rubric generation with tool-intensive evidence gathering.
Source: arXiv cs.CL
https://arxiv.org/abs/2609.36201
#MachineLearning
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