5 citations · 8 across the 8 of their papers we have counts for
8 papers
A Comparative Study of Controlled Text Generation Systems Using Level-Playing-Field Evaluation Principles
Michela Lorandi, Anya Belz
Background: Many different approaches to controlled text generation (CTG) have been proposed over recent years, but it is difficult to get a clear picture of which approach perform…
Output Composability of QLoRA PEFT Modules for Plug-and-Play Attribute-Controlled Text Generation
Michela Lorandi, Anya Belz
Parameter-efficient fine-tuning (PEFT) techniques offer task-specific fine-tuning at a fraction of the cost of full fine-tuning, but require separate fine-tuning for every new task…
Enhancing Study-Level Inference from Clinical Trial Papers via Reinforcement Learning-Based Numeric Reasoning
Massimiliano Pronesti, Michela Lorandi, Paul Flanagan +3
Systematic reviews in medicine play a critical role in evidence-based decision-making by aggregating findings from multiple studies. A central bottleneck in automating this process…
News is More than a Collection of Facts: Moral Frame Preserving News Summarization
Enrico Liscio, Michela Lorandi, Pradeep K. Murukannaiah
News articles are more than collections of facts; they reflect journalists' framing, shaping how events are presented to the audience. One key aspect of framing is the choice to wr…
Reproducing the Metric-Based Evaluation of a Set of Controllable Text Generation Techniques
Michela Lorandi, Anya Belz
Rerunning a metric-based evaluation should be more straightforward, and results should be closer, than in a human-based evaluation, especially where code and model checkpoints are…
High-quality Data-to-Text Generation for Severely Under-Resourced Languages with Out-of-the-box Large Language Models
Michela Lorandi, Anya Belz
The performance of NLP methods for severely under-resourced languages cannot currently hope to match the state of the art in NLP methods for well resourced languages. We explore th…
Data-to-text Generation for Severely Under-Resourced Languages with GPT-3.5: A Bit of Help Needed from Google Translate
Michela Lorandi, Anya Belz
LLMs like GPT are great at tasks involving English which dominates in their training data. In this paper, we look at how they cope with tasks involving languages that are severely…
Genetic Improvement of Routing Protocols for Delay Tolerant Networks
Michela Lorandi, Leonardo Lucio Custode, Giovanni Iacca
Routing plays a fundamental role in network applications, but it is especially challenging in Delay Tolerant Networks (DTNs). These are a kind of mobile ad hoc networks made of e.g…