Before we call CludeMem "first" at anything, we tried to prove ourselves wrong. We ran a prior-art check, a search for every model, paper and product that already does what our claim says.
The claim we tested was that CludeMem is the first small open model trained to settle contradictions between memories. When a new fact clashes with an old one, it decides whether the new fact replaces the old one, both stay true, or the conflict gets flagged for review.
My agents searched papers, Hugging Face, GitHub, product launches, patents and Chinese-language sources over three rounds. After each round, a critic agent listed angles the search had missed. That turned up 526 candidates, and 120 of them could plausibly beat our claim. Every one of the 120 got a full read: open weights or not, parameter count, training method, release date. Then two more agents took on each possible counterexample. One argued it already beats our claim. The other checked its facts.
No released model does all of it at once, but most of the pieces already exist. PSM, a 0.5B open model, can flag a memory conflict for review. LAM8B decides whether a new memory supersedes an old one. Memory-R2 and Mem-T-4B delete memories that new facts contradict. NAVER researchers trained a model to keep conversation memories up to date back in 2022, though we found no public weights for it. In June, a developer published "reconcile" adapters for a meeting assistant on the same Gemma base we use.
We've increased CludeMem from 4B to 8B parameters in total. One claim survived, and it needs our weights to be public first. As far as we can find, CludeMem would be the first open model under 10B parameters trained to make that three-way call, with its contradiction calls tested on DNLI and DECODE, two human-labelled dialogue datasets.
If you know a released model that already makes all three calls, send it. I'd love to hear about it.