Scaling Agent Learning via Experience Synthesis
arXiv:2511.03773v1 Announce Type: new Abstract: While reinforcement learning (RL) can empower large language model (LLM) agents by enabling self-improvement through…
For An Exciting Tomorrow
arXiv:2511.03773v1 Announce Type: new Abstract: While reinforcement learning (RL) can empower large language model (LLM) agents by enabling self-improvement through…
arXiv:2511.03227v2 Announce Type: replace-cross Abstract: We present a node-based storytelling system for multimodal content generation. The system represents stories as…
arXiv:2511.02659v2 Announce Type: replace-cross Abstract: Focusing on implicit neural representations, we present a novel in situ training protocol that employs…
arXiv:2511.03675v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly deployed in sensitive domains including healthcare, legal services, and…
arXiv:2511.03685v1 Announce Type: cross Abstract: Post-hoc recalibration methods are widely used to ensure that classifiers provide faithful probability estimates. We…