@inproceedings{estevanell-valladares-etal-2026-smartmatch,
    title = "{S}mart{M}atch: Real-Time Semantic Retrieval for Translation Memory Systems",
    author = "Estevanell Valladares, Ernesto Luis  and
      Lamsiyah, Salima  and
      Picazo-Izquierdo, Alicia  and
      Ranasinghe, Tharindu  and
      Mitkov, Ruslan  and
      Munoz, Rafael",
    editor = "Croce, Danilo  and
      Leidner, Jochen  and
      Moosavi, Nafise Sadat",
    booktitle = "Proceedings of the 19th Conference of the {E}uropean Chapter of the {A}ssociation for {C}omputational {L}inguistics (Volume 3: System Demonstrations)",
    month = mar,
    year = "2026",
    address = "Rabat, Marocco",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/manual-author-scripts/2026.eacl-demo.36/",
    pages = "527--536",
    ISBN = "979-8-89176-382-1",
    abstract = "Translation Memory (TM) systems are core components of commercial computer-aided translation (CAT) tools. However, traditional fuzzy matching methods often fail to retrieve semantically relevant content when surface similarity is low. We introduce SmartMatch, an open-source interactive demo and evaluation toolkit for TM retrieval that connects modern sentence encoders (including LLM-derived representations) and strong lexical/fuzzy baselines with a vector database, and exposes the end-to-end retrieval pipeline through a web-based UI for qualitative inspection and preference logging. The demo allows users to (i) enter a query segment, (ii) switch retrieval backends and embedding models, (iii) inspect top-$k$ retrieved matches with similarity scores and qualitative cues, and (iv) observe end-to-end latency in real time. We provide a reproducible benchmark on multilingual TM data, reporting retrieval quality using reference-based MT metrics (COMET, BERTScore, METEOR, chrF) together with coverage and latency/throughput trade-offs relevant to real-time CAT workflows. On DGT-TM, encoder-based retrieval achieves full coverage (100{\%}) with millisecond-level latency (p50/p90 $\leq$ 6{--}20 ms) and attains the strongest semantic-quality scores on the shared query set (e.g., BERTScore up to 0.91 at $k{=}10$), while BM25 remains a strong lightweight lexical baseline with very low latency. SmartMatch targets CAT researchers and tool builders and bridges recent advances in sentence encoders with the real-time constraints of translation memory retrieval."
}