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DReSD: Dense Retrieval for Speculative Decoding
Milan Gritta, Huiyin Xue, Gerasimos Lampouras
Speculative decoding (SD) accelerates Large Language Model (LLM) generation by using an efficient draft model to propose the next few tokens, which are verified by the LLM in a sin…
Mixture of Attentions For Speculative Decoding
Matthieu Zimmer, Milan Gritta, Gerasimos Lampouras +2
The growth in the number of parameters of Large Language Models (LLMs) has led to a significant surge in computational requirements, making them challenging and costly to deploy. S…
CrossAligner & Co: Zero-Shot Transfer Methods for Task-Oriented Cross-lingual Natural Language Understanding
Milan Gritta, Ruoyu Hu, Ignacio Iacobacci
Task-oriented personal assistants enable people to interact with a host of devices and services using natural language. One of the challenges of making neural dialogue systems avai…
XeroAlign: Zero-Shot Cross-lingual Transformer Alignment
Milan Gritta, Ignacio Iacobacci
The introduction of pretrained cross-lingual language models brought decisive improvements to multilingual NLP tasks. However, the lack of labelled task data necessitates a variety…
Conversation Graph: Data Augmentation, Training and Evaluation for Non-Deterministic Dialogue Management
Milan Gritta, Gerasimos Lampouras, Ignacio Iacobacci
Task-oriented dialogue systems typically rely on large amounts of high-quality training data or require complex handcrafted rules. However, existing datasets are often limited in s…
A Comparison of Techniques for Sentiment Classification of Film Reviews
Milan Gritta
We undertake the task of comparing lexicon-based sentiment classification of film reviews with machine learning approaches. We look at existing methodologies and attempt to emulate…