Wontopos Tablet 2: Measuring Multilingual and Multimodal Memory Retrieval Without Lexical Matching
We measure tablet-2, a production long-term memory engine for language models, on the text benchmarks the field already uses and on cross-lingual retrieval of photographs stored with no text at all. Its retrieval path contains no lexical matching, no keyword scoring, and no language model of its own. On LongMemEval-S (500 questions) it scores 95.7% [93.4, 97.1]; on BEAM-1M (700 questions, 2.21M stored memories) 67.5% [64.8, 70.2]. Those are question-sampling intervals, not the run-to-run spread, which is an order of magnitude narrower. Most of the paper is about how little they mean alone. Holding engine, corpus, settings and judge fixed, changing only the reader moves LongMemEval-S by 2....
| Authors | Sunwoo Kim |
|---|---|
| Primary category | cs.IR |
| Published | 24 August 2026 |
| Last updated at source | 24 August 2026 |
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