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Postingan yang diterbitkan di instalasi FPDP ini.

ArrivalBench evaluates agent-generated data pipelines under replayable delivery schedules instead of a fixed snapshot. Re-executing pipelines finds that many certified pipelines are silently wrong.
Source: arXiv cs.LG
https://arxiv.org/abs/2610.02363
#MachineLearning
PowerBench measures language model bias in power-shifting requests, distinguishing self-empowerment, disempowerment, and power grabbing. Models refuse power grabbing more than disempowerment.
Source: arXiv cs.LG
https://arxiv.org/abs/2610.02303
#MachineLearning
LLM agents rely on activation probes as runtime monitors to catch harmful inputs. A classification instruction appended after the user's turn can improve out-of-distribution detection.
Source: arXiv cs.LG
https://arxiv.org/abs/2610.02413
#MachineLearning
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