Tim Rocktäschel

Open-EndednessRecursive Self-Improvement
Tim Rocktäschel

I am a Co-Founder and Chief Scientist of Recursive and a Professor of AI at University College London (UCL). I am also faculty at the British Open-Ended Learning & Discovery (BOLD) national UK AI research lab, and a Fellow at the European Laboratory for Learning and Intelligent Systems (ELLIS). Before, I was a Director, Principal Scientist, and the Open-Endedness Team Lead at Google DeepMind, and before that the Reinforcement Learning Team Lead at Meta AI (FAIR) London. My academic background includes postdoctoral research at the University of Oxford’s Whiteson Research Lab, along with a Junior Research Fellowship at Jesus College and a stipendiary lectureship at Hertford College. I earned my Ph.D. from UCL under the supervision of Sebastian Riedel, supported by a 2013 Microsoft Research Ph.D. Scholarship and a 2017 Google Ph.D. Fellowship. My research focuses on Artificial General Intelligence, Open-Endedness, and Recursive Self-Improvement. My work was recognized with two Best Paper Awards at ICML 2024 and a Keynote at ICLR 2025.

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