collaborators

18 papers

cs.RO2026

DemoBridge: A Simulation-in-the-Loop Toolkit for Single-View Human Demonstration Retargeting

Zehao Wang, Fabien Despinoy, Sergey Zakharov +2

We present DemoBridge, an toolkit that turns a single-view RGB stereo recording of a human hand demonstration into an executable, physics-validated robot-arm trajectory. Retargetin…

cs.LG2026

Continual Self-Improvement with Lightweight Experiential Latent Memories

Vaggelis Dorovatas, Nancy Kalaj, Rahaf Aljundi

Large language models achieve strong reasoning performance by scaling inference-time compute, yet remain fundamentally stateless, discarding the rich, self-produced reasoning trace…

cs.LG2026

Position: Modular Memory is the Key to Continual Learning Agents

Vaggelis Dorovatas, Malte Schwerin, Andrew D. Bagdanov +21

Foundation models have transformed machine learning through large-scale pretraining and increased test-time compute. Despite surpassing human performance in several domains, these…

cs.AI2026

Thinking Past the Answer: Evaluating Harmful Overthinking in Large Reasoning Models

Simone Caldarella, Davide Talon, Rahaf Aljundi +2

Large Reasoning Models (LRMs) improve performance by generating explicit intermediate reasoning traces through increased test-time compute, yet the assumption that longer reasoning…

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…