5 papers · 1 filter
On the (In)effectiveness of AMR Augmentation for Large Language Models
Hoa Quynh Nhung Nguyen, Jacopo Staiano, Michael Sullivan
While Abstract Meaning Representation (AMR) has historically improved performance on a range of NLP tasks, the benefit---or lack thereof---of AMR augmentation for modern LLMs is th…
AuthorMix: Modular Authorship Style Transfer via Layer-wise Adapter Mixing
Sarubi Thillainathan, Ji-Ung Lee, Michael Sullivan +1
The task of authorship style transfer involves rewriting text in the style of a target author while preserving the meaning of the original text. Existing style transfer methods tra…
Evaluating Spatiotemporal Consistency in Automatically Generated Sewing Instructions
Luisa Geiger, Mareike Hartmann, Michael Sullivan +1
In this paper, we propose a novel, automatic tree-based evaluation metric for LLM-generated step-by-step assembly instructions, that more accurately reflects spatiotemporal aspects…
Exploring Graph Representations of Logical Forms for Language Modeling
Michael Sullivan
We make the case for language models over logical forms (LFLMs), arguing that such models are more data-efficient than their textual counterparts. To that end, we introduce the Gra…
Playpen: An Environment for Exploring Learning Through Conversational Interaction
Nicola Horst, Davide Mazzaccara, Antonia Schmidt +13
Interaction between learner and feedback-giver has come into focus recently for post-training of Large Language Models (LLMs), through the use of reward models that judge the appro…