{"work":{"id":"4ef9012c-9ddc-4414-98c7-de172a2102f5","openalex_id":null,"doi":null,"arxiv_id":"2602.11075","raw_key":null,"title":"RISE: Self-Improving Robot Policy with Compositional World Model","authors":null,"authors_text":null,"year":2026,"venue":"cs.RO","abstract":"Despite the sustained scaling on model capacity and data acquisition, Vision-Language-Action (VLA) models remain brittle in contact-rich and dynamic manipulation tasks, where minor execution deviations can compound into failures. While reinforcement learning (RL) offers a principled path to robustness, on-policy RL in the physical world is constrained by safety risk, hardware cost, and environment reset. To bridge this gap, we present RISE, a scalable framework of robotic reinforcement learning via imagination. At its core is a Compositional World Model that (i) predicts multi-view future via a controllable dynamics model, and (ii) evaluates imagined outcomes with a progress value model, producing informative advantages for the policy improvement. Such compositional design allows state and value to be tailored by best-suited yet distinct architectures and objectives. These components are integrated into a closed-loop self-improving pipeline that continuously generates imaginary rollouts, estimates advantages, and updates the policy in imaginary space without costly physical interaction. Across three challenging real-world tasks, RISE yields significant improvement over prior art, with more than +35% absolute performance increase in dynamic brick sorting, +45% for backpack packing, and +35% for box closing, respectively.","external_url":"https://arxiv.org/abs/2602.11075","cited_by_count":null,"metadata_source":"pith","metadata_fetched_at":"2026-07-03T11:18:03.335688+00:00","pith_arxiv_id":"2602.11075","created_at":"2026-05-11T06:20:57.978242+00:00","updated_at":"2026-07-03T11:18:03.335688+00:00","title_quality_ok":true,"display_title":"RISE: Self-Improving Robot Policy with Compositional World Model","render_title":"RISE: Self-Improving Robot Policy with Compositional World Model"},"hub":{"state":{"work_id":"4ef9012c-9ddc-4414-98c7-de172a2102f5","tier":"hub","tier_reason":"10+ Pith inbound or 1,000+ external citations","pith_inbound_count":19,"external_cited_by_count":null,"distinct_field_count":3,"first_pith_cited_at":"2026-04-08T17:49:35+00:00","last_pith_cited_at":"2026-07-02T17:00:37+00:00","author_build_status":"not_needed","summary_status":"needed","contexts_status":"needed","graph_status":"needed","ask_index_status":"not_needed","reader_status":"not_needed","recognition_status":"not_needed","updated_at":"2026-07-03T11:54:09.543455+00:00","tier_text":"hub"},"tier":"hub","role_counts":[{"context_role":"background","n":3},{"context_role":"other","n":1}],"polarity_counts":[{"context_polarity":"background","n":3},{"context_polarity":"unclear","n":1}],"runs":{},"summary":{},"graph":{},"authors":[]}}