Verifiable Visual Rewards Transfer from Synthetic Scenes to Natural Prompts
What the paper is about Precise instruction following in image generation, such as satisfying object counts and spatial relations, remains an open challenge...
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What the paper is about Precise instruction following in image generation, such as satisfying object counts and spatial relations, remains an open challenge...
What the paper is about Continuous diffusion generates complete reasoning solutions through iterative refinement in latent space.
What the paper is about Mobile GUI agents operate through a perception--action loop: at each step they screenshot the device, invoke a vision--language model...
What the paper is about Users of Workday's deployed LLM-based agents often request features which can be addressed by defining named procedures, also kno...
What the paper is about People learn not only by repeating successful actions, but also by recounting and explaining their experiences, revising their unders...
What the paper is about Evaluating finance research agents requires rubrics that reflect expert standards and fix the values correct as of an information cut...
What the paper is about In reinforcement learning with verifiable rewards (RLVR), imperfect verifiers can reward incorrect responses, creating opportunities...
What the paper is about Large language models (LLMs) excel at structured, verifiable tasks, but their low-entropy bias can produce homogeneous and predictabl...
What the paper is about Tool-using agents can fail twice: a required tool can fail, and the agent can then report success without the evidence needed to just...
What the paper is about Large Language Models can perform multi-step reasoning and improve task performance through different forms of intermediate computati...
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