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Three new papers tackle agent reliability through formal contracts, active knowledge acquisition for memory systems, and provably stable mechanistic interpretability.
New papers tackle training collapse in agentic RL with a unified stabilization recipe, reveal when querying multiple models actually helps, and expose a paradox where LLMs claim to trust humans but bet on algorithms.
YC-backed startup Guide Labs releases Steerling-8B under Apache 2.0 - an 8.4B parameter model with a built-in concept module that traces every output token back to its training data.
