7 papers
Early-Exit Graph Neural Networks
Andrea Giuseppe Di Francesco, Maria Sofia Bucarelli, Franco Maria Nardini +3
Early-exit mechanisms allow deep neural networks to stop inference once prediction confidence is high, reducing latency and energy on easy inputs while retaining full-depth accurac…
Exact Nearest-Neighbor Search on Energy-Efficient FPGA Devices
Patrizio Dazzi, William Guglielmo, Franco Maria Nardini +2
This paper investigates the usage of FPGA devices for energy-efficient exact kNN search in high-dimension latent spaces. This work intercepts a relevant trend that tries to support…
Blending Learning to Rank and Dense Representations for Efficient and Effective Cascades
Franco Maria Nardini, Raffaele Perego, Nicola Tonellotto +1
We investigate the exploitation of both lexical and neural relevance signals for ad-hoc passage retrieval. Our exploration involves a large-scale training dataset in which dense ne…
Efficient Conversational Search via Topical Locality in Dense Retrieval
Cristina Ioana Muntean, Franco Maria Nardini, Raffaele Perego +2
Pre-trained language models have been widely exploited to learn dense representations of documents and queries for information retrieval. While previous efforts have primarily focu…
Power- and Fragmentation-aware Online Scheduling for GPU Datacenters
Francesco Lettich, Emanuele Carlini, Franco Maria Nardini +2
The rise of Artificial Intelligence and Large Language Models is driving increased GPU usage in data centers for complex training and inference tasks, impacting operational costs,…
Rewriting Conversational Utterances with Instructed Large Language Models
Elnara Galimzhanova, Cristina Ioana Muntean, Franco Maria Nardini +2
Many recent studies have shown the ability of large language models (LLMs) to achieve state-of-the-art performance on many NLP tasks, such as question answering, text summarization…