8 citations · 17 across the 3 of their papers we have counts for
5 papers · 1 filter
EmbeddingGemma: Powerful and Lightweight Text Representations
Henrique Schechter Vera, Sahil Dua, Biao Zhang +86
We introduce EmbeddingGemma, a new lightweight, open text embedding model based on the Gemma 3 language model family. Our innovative training recipe strategically captures knowledg…
Adapting Decoder-Based Language Models for Diverse Encoder Downstream Tasks
Paul Suganthan, Fedor Moiseev, Le Yan +7
Decoder-based transformers, while revolutionizing language modeling and scaling to immense sizes, have not completely overtaken encoder-heavy architectures in natural language proc…
SKILL: Structured Knowledge Infusion for Large Language Models
Fedor Moiseev, Zhe Dong, Enrique Alfonseca +1
Large language models (LLMs) have demonstrated human-level performance on a vast spectrum of natural language tasks. However, it is largely unexplored whether they can better inter…
Prosody Modifications for Question-Answering in Voice-Only Settings
Aleksandr Chuklin, Aliaksei Severyn, Johanne Trippas +3
Many popular form factors of digital assistants---such as Amazon Echo, Apple Homepod, or Google Home---enable the user to hold a conversation with these systems based only on the s…
Eval all, trust a few, do wrong to none: Comparing sentence generation models
Ondřej Cífka, Aliaksei Severyn, Enrique Alfonseca +1
In this paper, we study recent neural generative models for text generation related to variational autoencoders. Previous works have employed various techniques to control the prio…