39 citations · 77 across the 7 of their papers we have counts for
10 papers
Investigating Prompt Engineering in Diffusion Models
Sam Witteveen, Martin Andrews
With the spread of the use of Text2Img diffusion models such as DALL-E 2, Imagen, Mid Journey and Stable Diffusion, one challenge that artists face is selecting the right prompts t…
Handshakes AI Research at CASE 2021 Task 1: Exploring different approaches for multilingual tasks
Vivek Kalyan, Paul Tan, Shaun Tan +1
The aim of the CASE 2021 Shared Task 1 (Hürriyetoğlu et al., 2021) was to detect and classify socio-political and crisis event information at document, sentence, cross-sentence, an…
Red Dragon AI at TextGraphs 2021 Shared Task: Multi-Hop Inference Explanation Regeneration by Matching Expert Ratings
Vivek Kalyan, Sam Witteveen, Martin Andrews
Creating explanations for answers to science questions is a challenging task that requires multi-hop inference over a large set of fact sentences. This year, to refocus the Textgra…
Red Dragon AI at TextGraphs 2020 Shared Task: LIT : LSTM-Interleaved Transformer for Multi-Hop Explanation Ranking
Yew Ken Chia, Sam Witteveen, Martin Andrews
Explainable question answering for science questions is a challenging task that requires multi-hop inference over a large set of fact sentences. To counter the limitations of metho…
Paraphrasing with Large Language Models
Sam Witteveen, Martin Andrews
Recently, large language models such as GPT-2 have shown themselves to be extremely adept at text generation and have also been able to achieve high-quality results in many downstr…
Red Dragon AI at TextGraphs 2019 Shared Task: Language Model Assisted Explanation Generation
Yew Ken Chia, Sam Witteveen, Martin Andrews
The TextGraphs-13 Shared Task on Explanation Regeneration asked participants to develop methods to reconstruct gold explanations for elementary science questions. Red Dragon AI's e…