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From Knowledge Access to Source Learning: Developing Source-Specific Competence

Large language model (LLM) agents increasingly rely on persistent external sources to solve sequences of knowledge-intensive tasks. Existing methods improve how source content is accessed and organized, while agent-memory systems preserve reusable knowledge from prior interactions, but repeated use of the same source is still largely treated as repeated access rather than an opportunity to…

We haven't written up this one. arXiv cs.AI has the full story — the link below goes straight to it.

Read the original at arxiv.org →

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Local Support Learning

We explore catastrophic forgetting in the context of large pre-trained models. By considering forgetting as a geometric problem in the input space of each weight matrix, we uncover a natural retention…

Opus 5.5 loves to tell you ‘this matters’ (and other AI writing tells)

Opus 5.5’s biggest tell is the word “dependable,” which pops up 23 times more often than in human samples.

  • "Dependable" appears 23 times more often in Claude Opus 5.5's writing than in humans
  • "This matters" occurs 116 times more frequently in Opus 5.5 than in human writing
  • Astra model emphasizes "another dimension" and uses "may provide" or "can provide" hedging

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