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Mobile Manipulation (MoMa) is a cornerstone of autonomous robotic systems, yet real-world fine-tuning remains a formi...
Recent advances in robot learning have driven rapid progress in humanoid control, enabling increasingly agile behavio...
Context can improve large language model performance, but these gains may be lost after context removal. Inspired by ...
Long contexts enlarge key--value (KV) caches, increasing memory use and attention costs during generation. Compressin...
A central challenge in scaling flow models is maintaining stability in training and integration. In flow matching, th...
Recent years have witnessed rapid progress in joint audio--visual generation. However, audio--visual synchronization ...
Large language models (LLMs) are increasingly expected to orchestrate diverse tools over long-horizon tasks. Existing...
Language models are becoming infrastructure, and infrastructure built in the open, by public institutions, on documen...
Multi-agent systems allow language models to solve tasks collaboratively by sharing complementary information. These ...
A recommendation request on Reddit draws several replies, each naming different titles. When an LLM recommender is tr...
We present a Generative World Simulation framework that couples persistent shared world state with continuous first-p...
Visual grounding combines image--language understanding with geometric prediction, yet autoregressive multimodal mode...