APPO: Agentic Procedural Policy Optimization
Recent advances in agentic Reinforcement Learning (RL) have substantially improved the multi-turn tool-use capabiliti...
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Recent advances in agentic Reinforcement Learning (RL) have substantially improved the multi-turn tool-use capabiliti...
AI agents are increasingly being developed to accelerate scientific discovery, yet their practical capabilities in re...
We identify a new dimension for enhancing rollout diversity in Group Relative Policy Optimization (GRPO) for LLMs. Wh...
Interactive driving exposes a failure mode that is easy to miss in rule-aware autonomous-driving stacks: a hard-rule ...
Retrieval-augmented generation is moving beyond text into long, egocentric video, where systems must select query-rel...
Large language models (LLMs) now reach expert-level scores on medical licensing exams, encouraging the assumption tha...
Large reasoning models typically follow a read-then-think paradigm: they observe the complete input, reason over a st...
Multimodal large language models can write code to produce complex programs as well as use programs to do 3D modeling...
Large and demographically balanced datasets are essential for reliable neuroimaging biomarkers. Full-resolution 3D br...
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