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This work introduces a policy-aligned predictive verifier (PAV) that anticipates the consequences of candidate action prefixes and evaluates their compatibility with successful continuation before execution, and combines trajectory-level survival supervision with a localization prior that preserves useful behavior with...
Commercial design platforms increasingly edit documents through large language model (LLM) agents, but two practical problems block reliable deployment: legacy document formats expose only \emph{flat}, absolutely positioned elements, so agents must recompute coordinates and routinely break layouts; and design has no un...
Robot agents must connect their intended actions to observed outcomes while retaining the context needed to revise their choices over repeated attempts. Existing interfaces often leave these choices inside predefined tools or require agents to manage detailed execution code and its growing history. We introduce RobotUs...
This paper introduces Completion Aware Guidance (CAG), a training-free sampling method that guides generation toward task completion, and shows that this failure is not inherent to the world model backbone, but emerges when adapted for short-chunk control.
Value-model-free RLVR methods such as GRPO assign uniform advantages to all tokens in a rollout, ignoring that tokens contribute unequally. Recent methods use token entropy as an importance proxy but compute it globally across the batch, conflating importance with prompt difficulty and positional trends. We argue that...
The results demonstrate the feasibility of harness distillation for robotics: intervention experience can be accumulated, refined through execution, and reused across agents to improve manipulation.
Evaluation of a video authoring pipeline featuring two layers of structured refusal shows that both layers independently improve the same instructional dimensions, suggesting that thoughtful resistance and generative AI are not opposites but partners.
This work proposes LandingAgent, a three-phase agentic framework that profiles the target, constructs a reference-guided wireframe, and refines the page through critique-guided polishing, and evaluates it against direct prompting on faithfulness, conciseness, readability, aesthetics, and structural diversity.
String is presented, an open-source runtime that gives this new class of software user an interface of its own and treats the job as an operating-systems problem and what three months of production use taught us.
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