AI EVALUATION, IN CONTEXT.BY EQUALITY MACHINE

Claire Radar

DynamicMem

DynamicMem evaluates long-horizon memory in LLM agents through a synthetic benchmark with 15 months of multi-app activity per user across 16 applications, including attributes, habits, and preferences that evolve and must be inferred from scattered evidence. Scoring occurs at quarterly checkpoints, tracking performance as history grows.

Evidence available for this benchmark

Numeric results have not been collected for this source record. Use the paper, code or dataset below to check the task and experiments; this does not imply that the original work contains no results.

Start with these resources

Cited documents and dates (1)

Catalog collected on 2026-10-14; resources and fields reflect that saved source.

Recorded attention

Observed on: 2026-10-11

GitHub stars
19

wenyaxie023/dynamicmem · View source snapshot

Dated attention observations, not live counts or benchmark scores.

Evaluation context and evidence

Source
Claire Radar
Publisher
Not recorded
Benchmark release
2026-06-22
Collected
2026-10-14
Modality
Not recorded

These are source-reported observations, not independent reruns by this site. Check the task version, evaluation protocol, unit and reporting date before comparing models. Results from different setups are not a universal ranking.

Reported results 0

This source record has no numeric results in our collection. That does not mean a score of zero or that no public results exist. Consult the original resources above.