Feb 19, 2024 · This study introduces triple-encoders, which efficiently compute distributed utterance mixtures from these independently encoded utterances.

Aug 11, 2024 · Our analysis shows that the co-occurrence training pushes representations that oc- cur (fire) together closer together, leading to stronger.

At inference, triple encoders can be used for retrieval-based sequence modeling via sequential modular late-interaction: Representations are encoded separately ...

This study introduces triple-encoders, which efficiently compute distributed utterance mixtures from these independently encoded utterances.

Aug 11, 2024 · Dive into the research topics of 'Triple-Encoders: Representations That Fire Together, Wire Together'. Together they form a unique fingerprint.

Triple-Encoders: Representations That Fire Together, Wire Together. Authors: Justus-Jonas Erker, Florian Mai, Nils Reimers 0001, Gerasimos Spanakis, Iryna ...

Sep 23, 2024 · Request PDF | On Jan 1, 2024, Justus-Jonas Erker and others published Triple-Encoders: Representations That Fire Together, Wire Together | Find,

Jul 15, 2024 · Traditional dialog models re-encode the full dialog history at each turn, which is computationally expensive.

Fingerprint. Dive into the research topics of 'Triple-Encoders: Representations That Fire Together, Wire Together'. Together they form a unique fingerprint.

Feb 19, 2024 · Search-based dialog models typically re-encode the dialog history at every turn, incurring high cost. Curved Contrastive Learning ...