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20162026
most citedEfficient Methods for Natural Language Processing: A Survey

11 citations · 20 across the 9 of their papers we have counts for

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cs.CL2025

FS-DFM: Fast and Accurate Long Text Generation with Few-Step Diffusion Language Models

Amin Karimi Monsefi, Nikhil Bhendawade, Manuel Rafael Ciosici +3

Autoregressive language models (ARMs) deliver strong likelihoods, but are inherently serial: they generate one token per forward pass, which limits throughput and inflates latency…

cs.CL2023

Remember what you did so you know what to do next

Manuel R. Ciosici, Alex Hedges, Yash Kankanampati +3

We explore using a moderately sized large language model (GPT-J 6B parameters) to create a plan for a simulated robot to achieve 30 classes of goals in ScienceWorld, a text game si…

cs.CL2022★ 11 cited

Efficient Methods for Natural Language Processing: A Survey

Marcos Treviso, Ji-Ung Lee, Tianchu Ji +19

Recent work in natural language processing (NLP) has yielded appealing results from scaling model parameters and training data; however, using only scale to improve performance mea…

cs.CL2022★ 1 cited

Training a T5 Using Lab-sized Resources

Manuel R. Ciosici, Leon Derczynski

Training large neural language models on large datasets is resource- and time-intensive. These requirements create a barrier to entry, where those with fewer resources cannot build…

cs.CL2021

Perhaps PTLMs Should Go to School -- A Task to Assess Open Book and Closed Book QA

Manuel R. Ciosici, Joe Cecil, Alex Hedges +3

Our goal is to deliver a new task and leaderboard to stimulate research on question answering and pre-trained language models (PTLMs) to understand a significant instructional docu…

cs.CL2021

A reproduction of Apple's bi-directional LSTM models for language identification in short strings

Mads Toftrup, Søren Asger Sørensen, Manuel R. Ciosici +1

Language Identification is the task of identifying a document's language. For applications like automatic spell checker selection, language identification must use very short strin…