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Wontopos Tablet 2 advances LLM memory retrieval without lexical matching · 2 sources tracked

A new research paper introduces Wontopos Tablet 2, a long-term memory engine for language models designed for multilingual and multimodal retrieval without relying on lexical matching. The system demonstrated strong performance on text benchmarks like LongMemEval-S, achieving 95.7% accuracy, and on the BEAM-1M dataset with 67.5% accuracy. In multimodal tests, Wontopos Tablet 2 significantly outperformed BM25 in cross-lingual retrieval of photographs, achieving 95.2% recall compared to BM25's 19.0%, and showed better language independence on captionless images. AI

IMPACT Advances memory retrieval capabilities for LLMs, potentially improving performance in multilingual and multimodal applications.

RANK_REASON The cluster contains a research paper detailing a new system and its performance on benchmarks.

Read on arXiv cs.IR (Information Retrieval) →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

Wontopos Tablet 2 advances LLM memory retrieval without lexical matching · 2 sources tracked

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COVERAGE [2]

  1. arXiv cs.IR (Information Retrieval) TIER_1 English(EN) · Sunwoo Kim ·

    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 langu…

  2. arXiv cs.CV TIER_1 English(EN) · Sunwoo Kim ·

    Wontopos Tablet 2: Measuring Multilingual and Multimodal Memory Retrieval Without Lexical Matching

    arXiv:2608.23920v1 Announce Type: cross Abstract: 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 …