SEEA-R1: Tree-Structured Reinforcement Fine-Tuning for Self-Evolving Embodied Agents
arXiv:2506.21669v1 Announce Type: new Abstract: Self-evolution, the ability of agents to autonomously improve their reasoning and behavior, is essential for…
For An Exciting Tomorrow
arXiv:2506.21669v1 Announce Type: new Abstract: Self-evolution, the ability of agents to autonomously improve their reasoning and behavior, is essential for…
arXiv:2506.21333v2 Announce Type: replace-cross Abstract: The co creativity community is making significant progress in developing more sophisticated and tailored systems…
arXiv:2506.22084v1 Announce Type: cross Abstract: We establish connections between the Transformer architecture, originally introduced for natural language processing, and Graph…
arXiv:2506.22039v1 Announce Type: cross Abstract: Time Series Foundation Models (TSFMs) have achieved remarkable success through large-scale pretraining. However, their design…
arXiv:2506.19863v2 Announce Type: replace-cross Abstract: The AI for Nuclear Energy workshop at Oak Ridge National Laboratory evaluated the potential of…
arXiv:2506.20702v1 Announce Type: new Abstract: Rapidly improving AI capabilities and autonomy hold significant promise of transformation, but are also driving…
arXiv:2506.20081v2 Announce Type: replace-cross Abstract: Retrieval-Augmented Code Generation (RACG) is a critical technique for enhancing code generation by retrieving relevant…
arXiv:2506.21298v1 Announce Type: cross Abstract: Fine-tuning large-scale music generation models, such as MusicGen and Mustango, is a computationally expensive process,…
arXiv:2506.21294v1 Announce Type: cross Abstract: In this paper, we explore the use of a text-only, autoregressive language modeling approach for…
arXiv:2506.19683v2 Announce Type: replace-cross Abstract: Understanding medical ultrasound imaging remains a long-standing challenge due to significant visual variability caused by…