activity
20202026
most citedBeyond the Imitation Game: Quantifying and extrapolating the capabilities of language models

565 citations · 1.2k across the 17 of their papers we have counts for

collaborators
Showing 2023Show all

5 papers · 1 filter

cs.CL2023★ 3 cited

Camoscio: an Italian Instruction-tuned LLaMA

Andrea Santilli, Emanuele Rodolà

In recent years Large Language Models (LLMs) have increased the state of the art on several natural language processing tasks. However, their accessibility is often limited to paid…

cs.CL2023

Fauno: The Italian Large Language Model that will leave you senza parole!

Andrea Bacciu, Giovanni Trappolini, Andrea Santilli +2

This paper presents Fauno, the first and largest open-source Italian conversational Large Language Model (LLM). Our goal with Fauno is to democratize the study of LLMs in Italian,…

cs.CL2023★ 28 cited

Accelerating Transformer Inference for Translation via Parallel Decoding

Andrea Santilli, Silvio Severino, Emilian Postolache +4

Autoregressive decoding limits the efficiency of transformers for Machine Translation (MT). The community proposed specific network architectures and learning-based methods to solv…

cs.MM2023★ 11 cited

Multimodal Neural Databases

Giovanni Trappolini, Andrea Santilli, Emanuele Rodolà +2

The rise in loosely-structured data available through text, images, and other modalities has called for new ways of querying them. Multimedia Information Retrieval has filled this…

cs.LG2023

Latent Autoregressive Source Separation

Emilian Postolache, Giorgio Mariani, Michele Mancusi +3

Autoregressive models have achieved impressive results over a wide range of domains in terms of generation quality and downstream task performance. In the continuous domain, a key…