14 citations · 24 across the 5 of their papers we have counts for
9 papers
Small Language Models Improve Giants by Rewriting Their Outputs
Giorgos Vernikos, Arthur Bražinskas, Jakub Adamek +3
Despite the impressive performance of large language models (LLMs), they often lag behind specialized models in various tasks. LLMs only use a fraction of the existing training dat…
Teaching Small Language Models to Reason
Lucie Charlotte Magister, Jonathan Mallinson, Jakub Adamek +2
Chain of thought prompting successfully improves the reasoning capabilities of large language models, achieving state of the art results on a range of datasets. However, these reas…
Text Generation with Text-Editing Models
Eric Malmi, Yue Dong, Jonathan Mallinson +7
Text-editing models have recently become a prominent alternative to seq2seq models for monolingual text-generation tasks such as grammatical error correction, simplification, and s…
EdiT5: Semi-Autoregressive Text-Editing with T5 Warm-Start
Jonathan Mallinson, Jakub Adamek, Eric Malmi +1
We present EdiT5 - a novel semi-autoregressive text-editing model designed to combine the strengths of non-autoregressive text-editing and autoregressive decoding. EdiT5 is faster…
RED-ACE: Robust Error Detection for ASR using Confidence Embeddings
Zorik Gekhman, Dina Zverinski, Jonathan Mallinson +1
ASR Error Detection (AED) models aim to post-process the output of Automatic Speech Recognition (ASR) systems, in order to detect transcription errors. Modern approaches usually us…
A Simple Recipe for Multilingual Grammatical Error Correction
Sascha Rothe, Jonathan Mallinson, Eric Malmi +2
This paper presents a simple recipe to train state-of-the-art multilingual Grammatical Error Correction (GEC) models. We achieve this by first proposing a language-agnostic method…
Felix: Flexible Text Editing Through Tagging and Insertion
Jonathan Mallinson, Aliaksei Severyn, Eric Malmi +1
We present Felix --- a flexible text-editing approach for generation, designed to derive the maximum benefit from the ideas of decoding with bi-directional contexts and self-superv…
Controllable Sentence Simplification: Employing Syntactic and Lexical Constraints
Jonathan Mallinson, Mirella Lapata
Sentence simplification aims to make sentences easier to read and understand. Recent approaches have shown promising results with sequence-to-sequence models which have been develo…
Learning Paraphrastic Sentence Embeddings from Back-Translated Bitext
John Wieting, Jonathan Mallinson, Kevin Gimpel
We consider the problem of learning general-purpose, paraphrastic sentence embeddings in the setting of Wieting et al. (2016b). We use neural machine translation to generate senten…