activity
20192025
most citedParaphrasing with Large Language Models

39 citations · 106 across the 12 of their papers we have counts for

collaborators

12 papers

cs.CL2025

A Reasoning-Based Approach to Cryptic Crossword Clue Solving

Martin Andrews, Sam Witteveen

Cryptic crossword clues are challenging language tasks for which new test sets are released daily by major newspapers on a global basis. Each cryptic clue contains both the definit…

cs.LG2025★ 1 cited

GPU Kernel Scientist: An LLM-Driven Framework for Iterative Kernel Optimization

Martin Andrews, Sam Witteveen

Optimizing GPU kernels for high performance is a complex task, often demanding deep architectural knowledge, extensive profiling, and iterative experimentation. This challenge is a…

cs.CL2024

Proving that Cryptic Crossword Clue Answers are Correct

Martin Andrews, Sam Witteveen

Cryptic crossword clues are challenging cognitive tasks, for which new test sets are released on a daily basis by multiple international newspapers. Each cryptic clue contains both…

cs.CV2022★ 16 cited

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…

cs.CL2021

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…

cs.CL2020

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…