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Ferdinando Fioretto

30 papers hereh-index 14937 citations78 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author1
  • middle author5
  • last author22

Across the 28 of 30 papers where every author was matched, so the position is known.

fields
  • cs.LG15
  • cs.CL4
  • cs.CR4
  • cs.RO3
  • math.OC2
  • eess.SY1
same name
  • Ferdinando Fioretto — 3 papers, h 1
  • Ferdinando Fioretto — 1 paper, h 1
  • Ferdinando Fioretto — 1 paper, h 22

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20242026
most citedSoK: Data Minimization in Machine Learning

1 citations · 1 across the 8 of their papers we have counts for

collaborators
Showing cs.CLShow all

4 papers · 1 filter

cs.CL2025

Constrained Discrete Diffusion

Michael Cardei, Jacob K Christopher, Thomas Hartvigsen +2

Discrete diffusion models are a class of generative models that construct sequences by progressively denoising samples from a categorical noise distribution. Beyond their rapidly g…

cs.CL2025

SpecDiff-2: Scaling Diffusion Drafter Alignment For Faster Speculative Decoding

Jameson Sandler, Jacob K. Christopher, Thomas Hartvigsen +1

Speculative decoding has become the standard approach for accelerating Large Language Model (LLM) inference. It exploits a lossless draft-then-verify procedure to circumvent the la…

cs.CL2025

The Disparate Impacts of Speculative Decoding

Jameson Sandler, Ahmet Üstün, Marco Romanelli +2

The practice of speculative decoding, whereby inference is probabilistically supported by a smaller, cheaper, ``drafter'' model, has become a standard technique for systematically…

cs.CL2025

Speculative Diffusion Decoding: Accelerating Language Generation through Diffusion

Jacob K Christopher, Brian R Bartoldson, Tal Ben-Nun +3

Speculative decoding has emerged as a widely adopted method to accelerate large language model inference without sacrificing the quality of the model outputs. While this technique…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.