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Self-Improving World Modelling with Latent Actions

SWIRL learns world models from state-only sequences via latent actions and alternating forward/inverse dynamics, improving LLM/VLM reasoning benchmarks by up to 28%.

Yifu QIU, Zheng Zhao, Waylon Li, Yftah Ziser and 3 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026 · ▲ 32 on Hugging Face · Code ★ 20

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AI panel: 13 of 20 reviewers recommend it
lenient 5/5
medium 6/10
strict 2/5