A Benchmark for Systematic Generalization in Grounded Language Understanding. - Laura Ruis; Jacob Andreas; Marco Baroni; Diane Bouchacourt; Brenden M. Lake (NeurIPS, 2020)

Insertion-Deletion Transformer. - Laura Ruis; Mitchell Stern; Julia Proskurnia; William Chan (CoRR, 2020)

Improving Systematic Generalization Through Modularity and Augmentation. - Laura Ruis; Brenden M. Lake (CogSci, 2022)

Large language models are not zero-shot communicators. - Laura Ruis; Akbir Khan; Stella Biderman; Sara Hooker; Tim Rocktäschel; Edward Grefenstette (CoRR, 2022)

The Goldilocks of Pragmatic Understanding: Fine-Tuning Strategy Matters for Implicature Resolution by LLMs. - Laura Ruis; Akbir Khan; Stella Biderman; Sara Hooker; Tim Rocktäschel; Edward Grefenstette (NeurIPS, 2023)

Debating with More Persuasive LLMs Leads to More Truthful Answers. - Akbir Khan; John Hughes; Dan Valentine; Laura Ruis; Kshitij Sachan; Ansh Radhakrishnan; Edward Grefenstette; Samuel R. Bowman; Tim Rocktäschel; Ethan Perez (ICML, 2024)

Towards Reliable Evaluation of Behavior Steering Interventions in LLMs. - Itamar Pres; Laura Ruis; Ekdeep Singh Lubana; David Krueger 001 (CoRR, 2024)

Procedural Knowledge in Pretraining Drives Reasoning in Large Language Models. - Laura Ruis; Maximilian Mozes; Juhan Bae; Siddhartha Rao Kamalakara; Dwarak Talupuru; Acyr Locatelli; Robert Kirk; Tim Rocktäschel; Edward Grefenstette; Max Bartolo (CoRR, 2024)

Procedural Knowledge in Pretraining Drives Reasoning in Large Language Models. - Laura Ruis; Maximilian Mozes; Juhan Bae; Siddhartha Rao Kamalakara; Dwaraknath Gnaneshwar; Acyr Locatelli; Robert Kirk; Tim Rocktäschel; Edward Grefenstette; Max Bartolo (ICLR, 2025)

Investigating Non-Transitivity in LLM-as-a-Judge. - Yi Xu; Laura Ruis; Tim Rocktäschel; Robert Kirk (CoRR, 2025)

Programming by Backprop: LLMs Acquire Reusable Algorithmic Abstractions During Code Training. - Jonathan Cook 004; Silvia Sapora; Arash Ahmadian; Akbir Khan; Tim Rocktäschel; Jakob N. Foerster; Laura Ruis (CoRR, 2025)