WordCraft: An Environment for Benchmarking Commonsense Agents. - Minqi Jiang; Jelena Luketina; Nantas Nardelli; Pasquale Minervini; Philip H. S. Torr; Shimon Whiteson; Tim Rocktäschel (CoRR, 2020)

Grid-to-Graph: Flexible Spatial Relational Inductive Biases for Reinforcement Learning. - Zhengyao Jiang; Pasquale Minervini; Minqi Jiang; Tim Rocktäschel (AAMAS, 2021)

Prioritized Level Replay. - Minqi Jiang; Edward Grefenstette; Tim Rocktäschel (ICML, 2021)

Insights From the NeurIPS 2021 NetHack Challenge. - Eric Hambro; Sharada P. Mohanty; Dmitrii Babaev; Minwoo Byeon; Dipam Chakraborty; Edward Grefenstette; Minqi Jiang; DaeJin Jo; Anssi Kanervisto; Jongmin Kim 006; Sungwoong Kim; Robert Kirk; et al. (NeurIPS (Competition and Demos), 2021)

Replay-Guided Adversarial Environment Design. - Minqi Jiang; Michael Dennis 001; Jack Parker-Holder; Jakob N. Foerster; Edward Grefenstette; Tim Rocktäschel (NeurIPS, 2021)

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 Küttler; Edward Grefenstette; Tim Rocktäschel (NeurIPS Datasets and Benchmarks, 2021)

Evolving Curricula with Regret-Based Environment Design. - Jack Parker-Holder; Minqi Jiang; Michael Dennis 001; Mikayel Samvelyan; Jakob N. Foerster; Edward Grefenstette; Tim Rocktäschel (ICML, 2022)

GriddlyJS: A Web IDE for Reinforcement Learning. - Christopher Bamford 001; Minqi Jiang; Mikayel Samvelyan; Tim Rocktäschel (NeurIPS, 2022)

ADBench: Anomaly Detection Benchmark. - Songqiao Han; Xiyang Hu; Hailiang Huang; Minqi Jiang; Yue Zhao 016 (NeurIPS, 2022)

Exploration via Elliptical Episodic Bonuses. - Mikael Henaff; Roberta Raileanu; Minqi Jiang; Tim Rocktäschel (NeurIPS, 2022)

Grounding Aleatoric Uncertainty for Unsupervised Environment Design. - Minqi Jiang; Michael Dennis 001; Jack Parker-Holder; Andrei Lupu; Heinrich Küttler; Edward Grefenstette; Tim Rocktäschel; Jakob N. Foerster (NeurIPS, 2022)

Improving Intrinsic Exploration with Language Abstractions. - Jesse Mu; Victor Zhong; Roberta Raileanu; Minqi Jiang; Noah D. Goodman; Tim Rocktäschel; Edward Grefenstette (NeurIPS, 2022)

General Intelligence Requires Rethinking Exploration. - Minqi Jiang; Tim Rocktäschel; Edward Grefenstette (CoRR, 2022)

Stabilizing Unsupervised Environment Design with a Learned Adversary. - Ishita Mediratta; Minqi Jiang; Jack Parker-Holder; Michael Dennis 001; Eugene Vinitsky; Tim Rocktäschel (CoLLAs, 2023)

MAESTRO: Open-Ended Environment Design for Multi-Agent Reinforcement Learning. - Mikayel Samvelyan; Akbir Khan; Michael Dennis 001; Minqi Jiang; Jack Parker-Holder; Jakob Nicolaus Foerster; Roberta Raileanu; Tim Rocktäschel (ICLR, 2023)

A Study of Global and Episodic Bonuses for Exploration in Contextual MDPs. - Mikael Henaff; Minqi Jiang; Roberta Raileanu (ICML, 2023)

Anomaly Detection with Score Distribution Discrimination. - Minqi Jiang; Songqiao Han; Hailiang Huang (KDD, 2023)

Discovering General Reinforcement Learning Algorithms with Adversarial Environment Design. - Matthew Thomas Jackson; Minqi Jiang; Jack Parker-Holder; Risto Vuorio; Chris Lu 001; Gregory Farquhar; Shimon Whiteson; Jakob N. Foerster (NeurIPS, 2023)

ADGym: Design Choices for Deep Anomaly Detection. - Minqi Jiang; Chaochuan Hou; Ao Zheng; Songqiao Han; Hailiang Huang; Qingsong Wen; Xiyang Hu; Yue Zhao 016 (NeurIPS, 2023)

How Close is ChatGPT to Human Experts? Comparison Corpus, Evaluation, and Detection. - Biyang Guo; Xin Zhang; Ziyuan Wang; Minqi Jiang; Jinran Nie; Yuxuan Ding; Jianwei Yue; Yupeng Wu (CoRR, 2023)

Weakly Supervised Anomaly Detection: A Survey. - Minqi Jiang; Chaochuan Hou; Ao Zheng; Xiyang Hu; Songqiao Han; Hailiang Huang; Xiangnan He 001; Philip S. Yu; Yue Zhao 016 (CoRR, 2023)

JaxMARL: Multi-Agent RL Environments in JAX. - Alexander Rutherford; Benjamin Ellis; Matteo Gallici; Jonathan Cook 004; Andrei Lupu; Garðar Ingvarsson; Timon Willi; Akbir Khan; Christian Schröder de Witt; Alexandra Souly; Saptarashmi Bandyopadhyay; Mikayel Samvelyan; et al. (CoRR, 2023)

minimax: Efficient Baselines for Autocurricula in JAX. - Minqi Jiang; Michael Dennis 001; Edward Grefenstette; Tim Rocktäschel (CoRR, 2023)

Learning Curricula in Open-Ended Worlds. - Minqi Jiang (CoRR, 2023)

JaxMARL: Multi-Agent RL Environments and Algorithms in JAX. - Alexander Rutherford; Benjamin Ellis; Matteo Gallici; Jonathan Cook 004; Andrei Lupu; Garðar Ingvarsson; Timon Willi; Akbir Khan; Christian Schröder de Witt; Alexandra Souly; Saptarashmi Bandyopadhyay; Mikayel Samvelyan; et al. (AAMAS, 2024)

Multi-Agent Diagnostics for Robustness via Illuminated Diversity. - Mikayel Samvelyan; Davide Paglieri; Minqi Jiang; Jack Parker-Holder; Tim Rocktäschel (AAMAS, 2024)

Advancing Multivariate Time Series Anomaly Detection: A Comprehensive Benchmark with Real-World Data from Alibaba Cloud. - Chaoli Zhang 001; Yingying Zhang; Lanshu Peng; Qingsong Wen; Yiyuan Yang; Chong-Jiong Fan; Minqi Jiang; Lunting Fan; Liang Sun 001 (CIKM, 2024)

The Generalization Gap in Offline Reinforcement Learning. - Ishita Mediratta; Qingfei You; Minqi Jiang; Roberta Raileanu (ICLR, 2024)

Reward-Free Curricula for Training Robust World Models. - Marc Rigter; Minqi Jiang; Ingmar Posner (ICLR, 2024)

Learning to Act without Actions. - Dominik Schmidt; Minqi Jiang (ICLR, 2024)

Refining Minimax Regret for Unsupervised Environment Design. - Michael Beukman; Samuel Coward; Michael T. Matthews; Mattie Fellows; Minqi Jiang; Michael D. Dennis; Jakob Nicolaus Foerster (ICML, 2024)

JaxMARL: Multi-Agent RL Environments and Algorithms in JAX. - Alexander Rutherford; Benjamin Ellis; Matteo Gallici; Jonathan Cook 004; Andrei Lupu; Garðar Ingvarsson; Timon Willi; Ravi Hammond; Akbir Khan; Christian Schröder de Witt; Alexandra Souly; Saptarashmi Bandyopadhyay; et al. (NeurIPS, 2024)

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 N. Foerster; Tim Rocktäschel; Roberta Raileanu (NeurIPS, 2024)

The 2025 PNPL Competition: Speech Detection and Phoneme Classification in the LibriBrain Dataset. - Gilad Landau; Miran Özdogan; Gereon Elvers; Francesco Mantegna; Pratik Somaiya; Dulhan Jayalath; Luisa Kurth; Teyun Kwon; Brendan Shillingford; Gregory Farquhar; Minqi Jiang; Karim Jerbi; et al. (CoRR, 2025)

The Automated LLM Speedrunning Benchmark: Reproducing NanoGPT Improvements. - Bingchen Zhao; Despoina Magka; Minqi Jiang; Xian Li; Roberta Raileanu; Tatiana Shavrina; Jean-Christophe Gagnon-Audet; Kelvin Niu; Shagun Sodhani; Michael Shvartsman; Andrei Lupu; Alisia Maria Lupidi; et al. (CoRR, 2025)

AI Research Agents for Machine Learning: Search, Exploration, and Generalization in MLE-bench. - Edan Toledo; Karen Hambardzumyan; Martin Josifoski; Rishi Hazra; Nicolas Mario Baldwin; Alexis Audran-Reiss; Michael Kuchnik; Despoina Magka; Minqi Jiang; Alisia Maria Lupidi; Andrei Lupu; Roberta Raileanu; et al. (CoRR, 2025)