Considering Race a Problem of Transfer Learning. - Akbir Khan; Marwa Mahmoud (WACV Workshops, 2019)

Multi-dimensional Affect in Poetry (POCA) Dataset: Acquisition, Annotation and Baseline Results. - Akbir Khan; Jack Hopkins; Hatice Gunes (ACII, 2021)

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

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)

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)

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)

Leading the Pack: N-player Opponent Shaping. - Alexandra Souly; Timon Willi; Akbir Khan; Robert Kirk; Chris Lu 001; Edward Grefenstette; Tim Rocktäschel (CoRR, 2023)

Scaling Opponent Shaping to High Dimensional Games. - Akbir Khan; Timon Willi; Newton Kwan; Andrea Tacchetti; Chris Lu 001; Edward Grefenstette; Tim Rocktäschel; Jakob N. Foerster (AAMAS, 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; Akbir Khan; Christian Schröder de Witt; Alexandra Souly; Saptarashmi Bandyopadhyay; Mikayel Samvelyan; et al. (AAMAS, 2024)

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)

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)

Melting Pot Contest: Charting the Future of Generalized Cooperative Intelligence. - Rakshit Trivedi; Akbir Khan; Jesse Clifton; Lewis Hammond; Edgar A. Duéñez-Guzmán; Dipam Chakraborty; John P. Agapiou; Jayd Matyas; Alexander Sasha Vezhnevets; Barna Pásztor; Yunke Ao; Omar G. Younis; et al. (NeurIPS, 2024)

Alignment faking in large language models. - Ryan Greenblatt; Carson Denison; Benjamin Wright; Fabien Roger; Monte MacDiarmid; Samuel Marks; Johannes Treutlein; Tim Belonax; Jack Chen; David Duvenaud; Akbir Khan; Julian Michael; et al. (CoRR, 2024)

BALROG: Benchmarking Agentic LLM and VLM Reasoning On Games. - Davide Paglieri; Bartlomiej Cupial; Samuel Coward; Ulyana Piterbarg; Maciej Wolczyk; Akbir Khan; Eduardo Pignatelli; Lukasz Kucinski; Lerrel Pinto; Rob Fergus; Jakob Nicolaus Foerster; Jack Parker-Holder; et al. (ICLR, 2025)

Adaptive Deployment of Untrusted LLMs Reduces Distributed Threats. - Jiaxin Wen; Vivek Hebbar; Caleb Larson; Aryan Bhatt; Ansh Radhakrishnan; Mrinank Sharma; Henry Sleight; Shi Feng 005; He He 001; Ethan Perez; Buck Shlegeris; Akbir Khan (ICLR, 2025)

Language Models Learn to Mislead Humans via RLHF. - Jiaxin Wen; Ruiqi Zhong; Akbir Khan; Ethan Perez; Jacob Steinhardt; Minlie Huang; Samuel R. Bowman; He He 001; Shi Feng 005 (ICLR, 2025)

Multi-Agent Risks from Advanced AI. - Lewis Hammond; Alan Chan; Jesse Clifton; Jason Hoelscher-Obermaier; Akbir Khan; Euan McLean; Chandler Smith; Wolfram Barfuss; Jakob N. Foerster; Tomas Gavenciak; The Anh Han; Edward Hughes 001; et al. (CoRR, 2025)

Factorio Learning Environment. - Jack Hopkins; Mart Bakler; Akbir Khan (CoRR, 2025)

Auditing language models for hidden objectives. - Samuel Marks; Johannes Treutlein; Trenton Bricken; Jack Lindsey; Jonathan Marcus; Siddharth Mishra-Sharma; Daniel M. Ziegler; Emmanuel Ameisen; Joshua Batson; Tim Belonax; Samuel R. Bowman; Shan Carter; et al. (CoRR, 2025)

Ctrl-Z: Controlling AI Agents via Resampling. - Aryan Bhatt; Cody Rushing; Adam Kaufman; Tyler Tracy; Vasil Georgiev; David Matolcsi; Akbir Khan; Buck Shlegeris (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)