Publications

127 publications

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20268 publications
  1. Anticipating the Consequences of Curriculum Decisions with Large Language Models

    Octavio Pappalardo; Nathan Herr; Tim Rocktäschel

    arXiv preprint arXiv:2610.04604

  2. Benchmarking Open-Ended Multi-Agent Coordination in Language Agents

    Kale-ab Tessera; Andras Szecsenyi; Cameron Barker; Alexander Rutherford; Davide Paglieri; Aidan Scannell; Henry Gouk; Elliot J Crowley; Tim Rocktäschel; Amos Storkey

    NeurIPS 2026 (Evaluations and Datasets)

  3. Check Your Work: Structured Checklist Feedback for Improving Large Language Models

    Jonathan Cook; Tim Rocktäschel; Jakob Foerster; Dennis Aumiller; Alex Wang

    ACL 2026

  4. DèjàQ: Open-ended Evolution of Diverse, Learnable and Verifiable Problems

    Willem Röpke; Samuel Coward; Andrei Lupu; Thomas Foster; Tim Rocktäschel; Jakob Foerster

    LLA 2026

  5. First Steps Toward Automated AI Research

    Recursive

    https://www.recursive.com/articles/first-steps-toward-automated-ai-research

  6. Learning When to Plan: Efficiently Allocating Test-Time Compute for LLM Agents

    Davide Paglieri; Bartłomiej Cupiał; Jonathan Cook; Ulyana Piterbarg; Jens Tuyls; Edward Grefenstette; Jakob Nicolaus Foerster; Jack Parker-Holder; Tim Rocktäschel

    Meta-Agents 2026

  7. Programming by Backprop: An Instruction is Worth 100 Examples When Finetuning LLMs

    Jonathan Cook; Silvia Sapora; Arash Ahmadian; Akbir Khan; Tim Rocktaschel; Jakob Foerster; Laura Ruis

    ICLR 2026

  8. Stress-Testing the Truth Advantage in Language Model Debates

    Ethar Hamid; Nathan Herr; Tim Rocktäschel

    Verify-Agents 2026

20258 publications
  1. BALROG: Benchmarking Agentic LLM and VLM Reasoning on Games

    Davide Paglieri; Bartłomiej Cupiał; Samuel Coward; Ulyana Piterbarg; Maciej Wolczyk; Akbir Khan; Eduardo Pignatelli; Łukasz Kuciński; Lerrel Pinto; Rob Fergus; and others

    ICLR 2025

  2. D3PO: Preference-Based Alignment of Discrete Diffusion Models

    Umberto Borso; Davide Paglieri; Jude Wells; Tim Rocktäschel

    Bi-Align 2025

  3. Generative Interactive Environments

    Jacob Bruce; Michael David Dennis; Ashley Deloris Edwards; Jack William Thadeus Parker-Holder; Yuge Shi; Edward Fauchon Hughes; Matthew Lai; Aditi Ashutosh Mavalankar; Richard Anton Steigerwald; Konrad Zolna; and others

    US Patent App. 19/041,971 , 2025

  4. Genie 3: A New Frontier for World Models

    P Ball; J Bauer; F Belletti; B Brownfield; A Ephrat; S Fruchter; A Gupta; K Holsheimer; A Holynski; J Hron; and others

    https://deepmind.google/discover/blog/genie-3-a-new-frontier-for-world-models/

  5. Imagined Autocurricula

    Ahmet H. Güzel; Matthew Thomas Jackson; Jarek Luca Liesen; Tim Rocktäschel; Jakob Nicolaus Foerster; Ilija Bogunovic; Jack Parker-Holder

    NeurIPS 2025

  6. Investigating Non-Transitivity in LLM-as-a-Judge

    Yi Xu; Laura Ruis; Tim Rocktäschel; Robert Kirk

    ICML 2025 (𝗦𝗽𝗼𝘁𝗹𝗶𝗴𝗵𝘁)

  7. LLM-First Search: Self-Guided Exploration of the Solution Space

    Nathan Herr; Tim Rocktäschel; Roberta Raileanu

    arXiv preprint arXiv:2506.05213

  8. 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

    ICLR 2025

202415 publications
  1. Artificial Intelligence: 10 Things You Should Know

    Tim Rocktäschel

  2. Assessing the Zero-Shot Capabilities of LLMs for Action Evaluation in RL

    Eduardo Pignatelli; Johan Ferret; Davide Paglieri; Samuel Coward; Tim Rocktäschel; Edward Grefenstette; Laura Toni

    AutoRL 2024

  3. 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 (𝗕𝗲𝘀𝘁 𝗣𝗮𝗽𝗲𝗿 𝗔𝘄𝗮𝗿𝗱)

  4. Genie 2: A Large-Scale Foundation World Model

    Jack Parker-Holder; Philip Ball; Jake Bruce; Vibhavari Dasagi; Kristian Holsheimer; Christos Kaplanis; Alexandre Moufarek; Guy Scully; Jeremy Shar; Jimmy Shi; and others

    https://deepmind.google/discover/blog/genie-2-a-large-scale-foundation-world-model/

  5. Genie: Generative Interactive Environments

    Jake Bruce; Michael Dennis; Ashley Edwards; Jack Parker-Holder; Yuge Shi; Edward Hughes; Matthew Lai; Aditi Mavalankar; Richie Steigerwald; Chris Apps; and others

    ICML 2024 (𝗕𝗲𝘀𝘁 𝗣𝗮𝗽𝗲𝗿 𝗔𝘄𝗮𝗿𝗱)

  6. H-GAP: Humanoid Control with a Generalist Planner

    Zhengyao Jiang; Yingchen Xu; Nolan Wagener; Yicheng Luo; Michael Janner; Edward Grefenstette; Tim Rocktäschel; Yuandong Tian

    ICLR 2024 (𝗦𝗽𝗼𝘁𝗹𝗶𝗴𝗵𝘁)

  7. JaxMARL: Multi-Agent RL Environments and Algorithms in JAX

    Alexander Rutherford; Benjamin Ellis; Matteo Gallici; Jonathan Cook; Andrei Lupu; Garðar Ingvarsson; Timon Willi; Akbir Khan; Christian Schroeder de Witt; Alexandra Souly; and others

    NeurIPS 2024 (Datasets and Benchmarks)

  8. Mechanistically Analyzing the Effects of Fine-tuning on Procedurally Defined Tasks

    Samyak Jain; Robert Kirk; Ekdeep Singh Lubana; Robert P Dick; Hidenori Tanaka; Tim Rocktäschel; Edward Grefenstette; David Scott Krueger

    ICLR 2024

  9. Multi-Agent Diagnostics for Robustness via Illuminated Diversity

    Mikayel Samvelyan; Davide Paglieri; Minqi Jiang; Jack Parker-Holder; Tim Rocktäschel

    AAMAS 2024 (𝗢𝗿𝗮𝗹)

  10. On Reward Functions For Self-Improving General-Purpose Reasoning

    Thomas Foster; Eltayeb Ahmed; Jonathan Cook; Shalev Lifshitz; Tim Rocktäschel; Jakob Foerster

    LanGame 2024

  11. Open-Endedness is Essential for Artificial Superhuman Intelligence

    Edward Hughes; Michael Dennis; Jack Parker-Holder; Feryal Behbahani; Aditi Mavalankar; Yuge Shi; Tom Schaul; Tim Rocktäschel

    ICML 2024 (𝗢𝗿𝗮𝗹)

  12. Outliers and Calibration Sets have Diminishing Effect on Quantization of Modern LLMs

    Davide Paglieri; Saurabh Dash; Tim Rocktäschel; Jack Parker-Holder

    ES-FoMo-II 2024

  13. Promptbreeder: Self-Referential Self-Improvement via Prompt Evolution

    Chrisantha Fernando; Dylan Banarse; Henryk Michalewski; Simon Osindero; Tim Rocktäschel

    ICML 2024

  14. Rainbow Teaming: Open-Ended Generation of Diverse Adversarial Prompts

    Mikayel Samvelyan; Sharath Chandra Raparthy; Andrei Lupu; Eric Hambro; Aram H Markosyan; Manish Bhatt; Yuning Mao; Minqi Jiang; Jack Parker-Holder; Jakob Foerster; and others

    NeurIPS 2024

  15. Scaling Opponent Shaping to High Dimensional Games

    Akbir Khan; Timon Willi; Newton Kwan; Andrea Tachetti; Chris Lu; Edward Grefenstette; Tim Rocktäschel; Jakob Foerster

    AAMAS 2024 (𝗢𝗿𝗮𝗹)

202313 publications
  1. A Survey of Zero-Shot Generalisation in Deep Reinforcement Learning

    Robert Kirk; Amy Zhang; Edward Grefenstette; Tim Rocktäschel

    JAIR

  2. ChatArena: Multi-agent Language Game Environments for Large Language Models

    Yuxiang Wu; Zhengyao Jiang; Akbir Khan; Yao Fu; Laura Ruis; Edward Grefenstette; Tim Rocktäschel

    https://github.com/Farama-Foundation/chatarena

  3. Do LLMs Selectively Encode the Goal of an Agent's Reach?

    Laura Ruis; Arduin Findeis; Herbie Bradley; Hossein A. Rahmani; Kyoung Whan Choe; Edward Grefenstette; Tim Rocktäschel

    ToM 2023

  4. Efficient Planning in a Compact Latent Action Space

    Zhengyao Jiang; Tianjun Zhang; Michael Janner; Yueying Li; Tim Rocktäschel; Edward Grefenstette; Yuandong Tian

    ICLR 2023

  5. General Intelligence Requires Rethinking Exploration

    Minqi Jiang; Tim Rocktäschel; Edward Grefenstette

    Royal Society Open Science

  6. Human-Timescale Adaptation in an Open-Ended Task Space

    Adaptive Agent Team; Jakob Bauer; Kate Baumli; Satinder Baveja; Feryal Behbahani; Avishkar Bhoopchand; Nathalie Bradley-Schmieg; Michael Chang; Natalie Clay; Adrian Collister; and others

    ICML 2023 (𝗢𝗿𝗮𝗹)

  7. Leading the Pack: N-player Opponent Shaping

    Alexandra Souly; Timon Willi; Akbir Khan; Robert Kirk; Chris Lu; Edward Grefenstette; Tim Rocktäschel

    MASEC 2023

  8. MAESTRO: Open-Ended Environment Design for Multi-Agent Reinforcement Learning

    Mikayel Samvelyan; Akbir Khan; Michael D Dennis; Minqi Jiang; Jack Parker-Holder; Jakob Nicolaus Foerster; Roberta Raileanu; Tim Rocktäschel

    ICLR 2023

  9. minimax: Efficient Baselines for Autocurricula in JAX

    Minqi Jiang; Michael D Dennis; Edward Grefenstette; Tim Rocktäschel

    ALOE 2023

  10. Mix-ME: Quality-Diversity for Multi-Agent Learning

    Gardar Ingvarsson; Mikayel Samvelyan; Manon Flageat; Bryan Lim; Antoine Cully; Tim Rocktäschel

    ALOE 2023

  11. Stabilizing Unsupervised Environment Design with a Learned Adversary

    Ishita Mediratta; Minqi Jiang; Jack Parker-Holder; Michael D Dennis; Eugene Vinitsky; Tim Rocktäschel

    CoLLAs 2023

  12. 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 (𝗦𝗽𝗼𝘁𝗹𝗶𝗴𝗵𝘁)

  13. Vision-Language Models as a Source of Rewards

    Kate Baumli; Satinder Baveja; Feryal Behbahani; Harris Chan; Gheorghe Comanici; Sebastian Flennerhag; Maxime Gazeau; Kristian Holsheimer; Dan Horgan; Michael Laskin; and others

    ALOE 2023

202212 publications
  1. A Study of Off-Policy Learning in Environments with Procedural Content Generation

    Andy Ehrenberg; Robert Kirk; Minqi Jiang; Edward Grefenstette; Tim Rocktäschel

    ALOE 2022

  2. Dungeons and Data: A Large-Scale NetHack Dataset

    Eric Hambro; Roberta Raileanu; Danielle Rothermel; Vegard Mella; Tim Rocktäschel; Heinrich Kuttler; Naila Murray

    NeurIPS 2022 (Datasets and Benchmarks)

  3. Evolving Curricula with Regret-Based Environment Design

    Jack Parker-Holder; Minqi Jiang; Michael Dennis; Mikayel Samvelyan; Jakob Foerster; Edward Grefenstette; Tim Rocktäschel

    ICML 2022

  4. Exploration via Elliptical Episodic Bonuses

    Mikael Henaff; Roberta Raileanu; Minqi Jiang; Tim Rocktäschel

    NeurIPS 2022

  5. Generalization in Cooperative Multi-agent Systems

    Anuj Mahajan; Mikayel Samvelyan; Tarun Gupta; Benjamin Ellis; Mingfei Sun; Tim Rocktäschel; Shimon Whiteson

    arXiv preprint arXiv:2202.00104

  6. GriddlyJS: A Web IDE for Reinforcement Learning

    Christopher Bamford; Minqi Jiang; Mikayel Samvelyan; Tim Rocktäschel

    NeurIPS 2022 (Datasets and Benchmarks)

  7. Grounding Aleatoric Uncertainty in Unsupervised Environment Design

    Minqi Jiang; Michael D Dennis; Jack Parker-Holder; Andrei Lupu; Heinrich Küttler; Edward Grefenstette; Tim Rocktäschel; Jakob Nicolaus Foerster

    NeurIPS 2022

  8. Hierarchical Kickstarting for Skill Transfer in Reinforcement Learning

    Michael Matthews; Mikayel Samvelyan; Jack Parker-Holder; Edward Grefenstette; Tim Rocktäschel

    CoLLAs 2022

  9. Improving Intrinsic Exploration with Language Abstractions

    Jesse Mu; Victor Zhong; Roberta Raileanu; Minqi Jiang; Noah Goodman; Tim Rocktäschel; Edward Grefenstette

    NeurIPS 2022

  10. Improving Policy Learning via Language Dynamics Distillation

    Victor Zhong; Jesse Mu; Luke Zettlemoyer; Edward Grefenstette; Tim Rocktäschel

    NeurIPS 2022

  11. Learning General World Models in a Handful of Reward-Free Deployments

    Yingchen Xu; Jack Parker-Holder; Philip J. Ball; Aldo Pacchiano; Oleh Rybkin; Stephen J. Roberts; Tim Rocktäschel; Edward Grefenstette

    NeurIPS 2022

  12. SkillHack: A Benchmark for Skill Transfer in Open-Ended Reinforcement Learning

    Michael Matthews; Mikayel Samvelyan; Jack Parker-Holder; Edward Grefenstette; Tim Rocktäschel

    ALOE 2022

202113 publications
  1. Don't Sweep your Learning Rate under the Rug: A Closer Look at Cross-modal Transfer of Pretrained Transformers

    Danielle Rothermel; Margaret Li; Tim Rocktäschel; Jakob Foerster

    SSL 2021

  2. Graph Backup: Data Efficient Backup Exploiting Markovian Transitions

    Zhengyao Jiang; Tianjun Zhang; Robert Kirk; Tim Rocktäschel; Edward Grefenstette

    DeepRL 2021

  3. Grid-to-Graph: Flexible Spatial Relational Inductive Biases for Reinforcement Learning

    Zhengyao Jiang; Pasquale Minervini; Minqi Jiang; Tim Rocktäschel

    AAMAS 2021

  4. How to Motivate Your Dragon: Teaching Goal-Driven Agents to Speak and Act in Fantasy Worlds

    Prithviraj Ammanabrolu; Jack Urbanek; Margaret Li; Arthur Szlam; Tim Rocktäschel; Jason Weston

    NAACL-HLT 2021

  5. Insights from the NeurIPS 2021 NetHack Challenge

    Eric Hambro; Sharada Mohanty; Dmitrii Babaev; Minwoo Byeon; Dipam Chakraborty; Edward Grefenstette; Minqi Jiang; Daejin Jo; Anssi Kanervisto; Jongmin Kim; and others

    PMLR

  6. KILT: a Benchmark for Knowledge Intensive Language Tasks

    Fabio Petroni; Aleksandra Piktus; Angela Fan; Patrick Lewis; Majid Yazdani; Nicola De Cao; James Thorne; Yacine Jernite; Vassilis Plachouras; Tim Rocktäschel; and others

    NAACL-HLT 2021

  7. Learning with AMIGo: Adversarially Motivated Intrinsic Goals

    Andres Campero; Roberta Raileanu; Heinrich Küttler; Joshua B Tenenbaum; Tim Rocktäschel; Edward Grefenstette

    ICLR 2021

  8. MiniHack the Planet: A Sandbox for Open-Ended Reinforcement Learning Research

    Mikayel Samvelyan; Robert Kirk; Vitaly Kurin; Jack Parker-Holder; Minqi Jiang; Eric Hambro; Fabio Petroni; Heinrich Kuttler; Edward Grefenstette; Tim Rocktäschel

    NeurIPS 2021 (Datasets and Benchmarks)

  9. My Body is a Cage: the Role of Morphology in Graph-Based Incompatible Control

    Vitaly Kurin; Maximilian Igl; Tim Rocktäschel; Wendelin Boehmer; Shimon Whiteson

    ICLR 2021

  10. Prioritized Level Replay

    Minqi Jiang; Ed Grefenstette; Tim Rocktäschel

    ICML 2021

  11. Replay-Guided Adversarial Environment Design

    Minqi Jiang; Michael D Dennis; Jack Parker-Holder; Jakob Nicolaus Foerster; Edward Grefenstette; Tim Rocktäschel

    NeurIPS 2021

  12. Return Dispersion as an Estimator of Learning Potential for Prioritized Level Replay

    Iryna Korshunova; Minqi Jiang; Jack Parker-Holder; Tim Rocktäschel; Edward Grefenstette

    DeepRL 2021

  13. That Escalated Quickly: Compounding Complexity by Editing Levels at the Frontier of Agent Capabilities

    Jack Parker-Holder; Minqi Jiang; Michael D Dennis; Mikayel Samvelyan; Jakob Nicolaus Foerster; Edward Grefenstette; Tim Rocktäschel

    DeepRL 2021

202011 publications
  1. Avoiding the Hypothesis-Only Bias in Natural Language Inference via Ensemble Adversarial Training

    Joe Stacey; Pasquale Minervini; Haim Dubossarsky; Sebastian Riedel; Tim Rocktäschel

    EMNLP 2020

  2. Differentiable Reasoning on Large Knowledge Bases and Natural Language

    Pasquale Minervini; Matko Bosnjak; Tim Rocktäschel; Sebastian Riedel; Edward Grefenstette

    AAAI 2020 (𝗢𝗿𝗮𝗹)

  3. Generating Interactive Worlds with Text

    Angela Fan; Jack Urbanek; Pratik Ringshia; Emily Dinan; Emma Qian; Siddharth Karamcheti; Shrimai Prabhumoye; Douwe Kiela; Tim Rocktäschel; Arthur Szlam; and others

    AAAI 2020

  4. How Context Affects Language Models' Factual Predictions

    Fabio Petroni; Patrick Lewis; Aleksandra Piktus; Tim Rocktäschel; Yuxiang Wu; Alexander H. Miller; Sebastian Riedel

    AKBC 2020 (𝗕𝗲𝘀𝘁 𝗣𝗮𝗽𝗲𝗿 𝗔𝘄𝗮𝗿𝗱)

  5. How Decoding Strategies Affect the Verifiability of Generated Text

    Luca Massarelli; Fabio Petroni; Aleksandra Piktus; Myle Ott; Tim Rocktäschel; Vassilis Plachouras; Fabrizio Silvestri; Sebastian Riedel

    Findings of ACL: EMNLP 2020

  6. Learning Reasoning Strategies in End-to-End Differentiable Proving

    Pasquale Minervini; Sebastian Riedel; Pontus Stenetorp; Edward Grefenstette; Tim Rocktäschel

    ICML 2020

  7. Retrieval-augmented Generation for Knowledge-intensive NLP Tasks

    Patrick Lewis; Ethan Perez; Aleksandara Piktus; Fabio Petroni; Vladimir Karpukhin; Naman Goyal; Heinrich Küttler; Mike Lewis; Wen-tau Yih; Tim Rocktäschel; and others

    NeurIPS 2020

  8. RIDE: Rewarding Impact-Driven Exploration for Procedurally-Generated Environments

    Roberta Raileanu; Tim Rocktäschel

    ICLR 2020

  9. RTFM: Generalising to Novel Environment Dynamics via Reading

    Victor Zhong; Tim Rocktäschel; Edward Grefenstette

    ICLR 2020

  10. The NetHack Learning Environment

    Heinrich Küttler; Nantas Nardelli; Alexander Miller; Roberta Raileanu; Marco Selvatici; Edward Grefenstette; Tim Rocktäschel

    NeurIPS 2020

  11. WordCraft: An Environment for Benchmarking Commonsense Agents

    Minqi Jiang; Jelena Luketina; Nantas Nardelli; Pasquale Minervini; Philip Torr; Shimon Whiteson; Tim Rocktäschel

    LaReL 2020

201910 publications
  1. A Baseline for Any Order Gradient Estimation in Stochastic Computation Graphs

    Jingkai Mao; Jakob Foerster; Tim Rocktäschel; Maruan Al-Shedivat; Gregory Farquhar; Shimon Whiteson

    ICML 2019

  2. A Survey of Reinforcement Learning Informed by Natural Language

    J Luketina; N Nardelli; G Farquhar; J Foerster; J Andreas; E Grefenstette; S Whiteson; T Rocktäschel

    IJCAI 2019

  3. HUNER: Improving Biomedical NER with Pretraining

    Leon Weber; Jannes Münchmeyer; Tim Rocktäschel; Maryam Habibi; Ulf Leser

    Bioinformatics

  4. Language Models as Knowledge Bases?

    Fabio Petroni; Tim Rocktäschel; Patrick Lewis; Anton Bakhtin; Yuxiang Wu; Alexander H Miller; Sebastian Riedel

    EMNLP 2019

  5. Learning to Speak and Act in a Fantasy Text Adventure Game

    Jack Urbanek; Angela Fan; Siddharth Karamcheti; Saachi Jain; Samuel Humeau; Emily Dinan; Tim Rocktäschel; Douwe Kiela; Arthur Szlam; Jason Weston

    EMNLP 2019

  6. MVFST-RL: An Asynchronous RL Framework for Congestion Control with Delayed Actions

    Viswanath Sivakumar; Olivier Delalleau; Tim Rocktäschel; Alexander H. Miller; Heinrich Küttler; Nantas Nardelli; Mike Rabbat; Joelle Pineau; Sebastian Riedel

    ML for Systems 2019

  7. Neural Variational Inference For Estimating Uncertainty in Knowledge Graph Embeddings

    Alexander I Cowen-Rivers; Pasquale Minervini; Tim Rocktaschel; Matko Bosnjak; Sebastian Riedel; Jun Wang

    NeSy 2019

  8. NLProlog: Reasoning with Weak Unification for Question Answering in Natural Language

    Leon Weber; Pasquale Minervini; Jannes Münchmeyer; Ulf Leser; Tim Rocktäschel

    ACL 2019

  9. Stable Opponent Shaping in Differentiable Games

    Alistair Letcher; Jakob Foerster; David Balduzzi; Tim Rocktäschel; Shimon Whiteson

    ICLR 2019

  10. TorchBeast: A PyTorch Platform for Distributed RL

    Heinrich Küttler; Nantas Nardelli; Thibaut Lavril; Marco Selvatici; Viswanath Sivakumar; Tim Rocktäschel; Edward Grefenstette

    Technical Report arXiv:1910.03552

20187 publications
  1. DiCE: The Infinitely Differentiable Monte-Carlo Estimator

    Jakob Foerster; Gregory Farquhar; Maruan Al-Shedivat; Tim Rocktäschel; Eric P Xing; Shimon Whiteson

    ICML 2018

  2. e-SNLI: Natural Language Inference with Natural Language Explanations

    Oana-Maria Camburu; Tim Rocktäschel; Thomas Lukasiewicz; Phil Blunsom

    NeurIPS 2018

  3. Einsum is All you Need - Einstein Summation in Deep Learning

    Tim Rocktäschel

    https://rockt.github.io/2018/04/30/einsum

  4. Interpretation of Natural Language Rules in Conversational Machine Reading

    Marzieh Saeidi; Max Bartolo; Patrick Lewis; Sameer Singh; Tim Rocktäschel; Mike Sheldon; Guillaume Bouchard; Sebastian Riedel

    EMNLP 2018

  5. Jack the Reader-A Machine Reading Framework

    Dirk Weissenborn; Pasquale Minervini; Tim Dettmers; Isabelle Augenstein; Johannes Welbl; Tim Rocktäschel; Matko Bošnjak; Jeff Mitchell; Thomas Demeester; Pontus Stenetorp; and others

    ACL 2018 Demo

  6. Towards Neural Theorem Proving at Scale

    Pasquale Minervini; Matko Bosnjak; Tim Rocktäschel; Sebastian Riedel

    NAMPI 2018

  7. TreeQN and ATreeC: Differentiable Tree-Structured Models for Deep Reinforcement Learning

    Gregory Farquhar; Tim Rocktäschel; Maximilian Igl; Shimon Whiteson

    ICLR 2018

20175 publications
  1. Adversarial Sets for Regularising Neural Link Predictors

    Pasquale Minervini; Thomas Demeester; Tim Rocktäschel; Sebastian Riedel

    UAI 2017

  2. Combining Representation Learning with Logic for Language Processing

    Tim Rocktäschel

    Ph.D. Thesis. University College London

  3. End-to-End Differentiable Proving

    Tim Rocktäschel; Sebastian Riedel

    NeurIPS 2017 (𝗢𝗿𝗮𝗹)

  4. Frustratingly Short Attention Spans in Neural Language Modeling

    Michał Daniluk; Tim Rocktäschel; Johannes Welbl; Sebastian Riedel

    ICLR 2017

  5. Programming with a Differentiable Forth Interpreter

    Matko Bošnjak; Tim Rocktäschel; Jason Naradowsky; Sebastian Riedel

    ICML 2017

201610 publications
  1. emoji2vec: Learning Emoji Representations from their Description

    Ben Eisner; Tim Rocktäschel; Isabelle Augenstein; Matko Bošnjak; Sebastian Riedel

    SocialNLP 2016 (𝗕𝗲𝘀𝘁 𝗣𝗮𝗽𝗲𝗿 𝗔𝘄𝗮𝗿𝗱)

  2. Generating Natural Language Inference Chains

    Vladyslav Kolesnyk; Tim Rocktäschel; Sebastian Riedel

    Technical Report arXiv:1606.01404

  3. Learning Knowledge Base Inference with Neural Theorem Provers

    Tim Rocktäschel; Sebastian Riedel

    AKBC 2016

  4. Learning Python Code Suggestion with a Sparse Pointer Network

    Avishkar Bhoopchand; Tim Rocktäschel; Earl Barr; Sebastian Riedel

    Technical Report arXiv:1611.08307

  5. Lifted Rule Injection for Relation Embeddings

    Thomas Demeester; Tim Rocktäschel; Sebastian Riedel

    EMNLP 2016

  6. MuFuRU: The Multi-Function Recurrent Unit

    Dirk Weissenborn; Tim Rocktäschel

    RepL4NLP 2016

  7. Reasoning about Entailment with Neural Attention

    Tim Rocktäschel; Edward Grefenstette; Karl Moritz Hermann; Tomáš Kočiskỳ; Phil Blunsom

    ICLR 2016

  8. Regularizing Relation Representations by First-order Implications

    Thomas Demeester; Tim Rocktäschel; Sebastian Riedel

    AKBC 2016

  9. SETH Detects and Normalizes Genetic Variants in Text

    Philippe Thomas; Tim Rocktäschel; Jörg Hakenberg; Yvonne Lichtblau; Ulf Leser

    Bioinformatics

  10. Stance Detection with Bidirectional Conditional Encoding

    Isabelle Augenstein; Tim Rocktäschel; Andreas Vlachos; Kalina Bontcheva

    EMNLP 2016

20157 publications
  1. Injecting Logical Background Knowledge into Embeddings for Relation Extraction

    Tim Rocktäschel; Sameer Singh; Sebastian Riedel

    NAACL 2015

  2. Matrix and Tensor Factorization Methods for Natural Language Processing

    Guillaume Bouchard; Jason Naradowsky; Sebastian Riedel; Tim Rocktäschel; Andreas Vlachos

    ACL 2015 Tutorial

  3. The CHEMDNER Corpus of Chemicals and Drugs and its Annotation Principles

    Martin Krallinger; Obdulia Rabal; Florian Leitner; Miguel Vazquez; David Salgado; Zhiyong Lu; Robert Leaman; Yanan Lu; Donghong Ji; Daniel M Lowe; and others

    Journal of Cheminformatics

  4. Towards Combined Matrix and Tensor Factorization for Universal Schema Relation Extraction

    Sameer Singh; Tim Rocktäschel; Sebastian Riedel

    VSM 2015

  5. Towards Extracting Faithful and Descriptive Representations of Latent Variable Models

    Iván Sánchez; Tim Rocktäschel; Sebastian Riedel; Sameer Singh

    KRR 2015

  6. Towards Two-way Interaction with Reading Machines

    Sebastian Riedel; Sameer Singh; Guillaume Bouchard; Tim Rocktäschel; Ivan Sanchez

    SLSP 2015

  7. WOLFE: An NLP-friendly Declarative Machine Learning Stack

    Sameer Singh; Tim Rocktäschel; Luke Hewitt; Jason Naradowsky; Sebastian Riedel

    NAACL 2015 Demo

20143 publications
  1. Designing an IDE for Probabilistic Programming: Challenges and a Prototype

    Sameer Singh; Sebastian Riedel; Luke Hewitt; Tim Rocktäschel

    ProbProg 2014

  2. Low-Dimensional Embeddings of Logic

    Tim Rocktäschel; Matko Bosnjak; Sameer Singh; Sebastian Riedel

    SP 2014 (𝗘𝘅𝗰𝗲𝗽𝘁𝗶𝗼𝗻𝗮𝗹 𝗦𝘂𝗯𝗺𝗶𝘀𝘀𝗶𝗼𝗻 𝗔𝘄𝗮𝗿𝗱)

  3. WOLFE: Strength Reduction and Approximate Programming for Probabilistic Programming.

    Sebastian Robert Riedel; Sameer Singh; Vivek Srikumar; Tim Rocktäschel; Larysa Visengeriyeva; Jan Noessner

    StarAI 2014

20133 publications
  1. Extended Feature Set for Chemical Named Entity Recognition and Indexing

    Torsten Huber; Tim Rocktäschel; Michael Weidlich; Philippe Thomas; Ulf Leser

    BioCreative 2013

  2. WBI-DDI: Drug-drug Interaction Extraction using Majority Voting

    Philippe Thomas; Mariana Neves; Tim Rocktäschel; Ulf Leser

    SemEval 2013

  3. WBI-NER: The Impact of Domain-specific Features on the Performance of Identifying and Classifying Mentions of Drugs

    Tim Rocktäschel; Torsten Huber; Michael Weidlich; Ulf Leser

    SemEval 2013

20121 publication
  1. ChemSpot: a Hybrid System for Chemical Named Entity Recognition

    Tim Rocktäschel; Michael Weidlich; Ulf Leser

    Bioinformatics

20111 publication
  1. Single-Step Extraction of Protein-Protein Interactions with Support Vector Machines

    Tim Rocktäschel