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cs.LG2026
From Demonstrations to Rewards: Test-Time Prompt Optimization for VLM Reward Models
Christian Gumbsch, Leonardo Barcellona, Lennard Schünemann +7
Reinforcement learning relies on accurate reward functions, which are often hand-crafted or even unavailable in real-world applications, such as robotics. Recent work has explored…
cs.CV2026
Reconstruction by Generation: 3D Multi-Object Scene Reconstruction from Sparse Observations
Andrii Zadaianchuk, Leonardo Barcellona, Lennard Schuenemann +7
Accurately reconstructing complex full multi-object scenes from sparse observations remains a core challenge in computer vision and a key step toward scalable and reliable simulati…