8 papers
MindMemOS: A Portable and Self-Evolving Memory Operating Layer for AI Agents
Kaichao Liang, Yuqi Cui, Hao Kong +13
Memory is a core component of AI agents, enabling them to accumulate experience, maintain personalization, and adapt over long-term interactions. However, existing memory systems o…
Apple Intelligence Foundation Language Models
Tom Gunter, Zirui Wang, Chong Wang +152
We present foundation language models developed to power Apple Intelligence features, including a ~3 billion parameter model designed to run efficiently on devices and a large serv…
Hilbert: Recursively Building Formal Proofs with Informal Reasoning
Sumanth Varambally, Thomas Voice, Yanchao Sun +3
Large Language Models (LLMs) demonstrate impressive mathematical reasoning abilities, but their solutions frequently contain errors that cannot be automatically checked. Formal the…
ReThinker: Scientific Reasoning by Rethinking with Guided Reflection and Confidence Control
Zhentao Tang, Yuqi Cui, Shixiong Kai +10
Expert-level scientific reasoning remains challenging for large language models, particularly on benchmarks such as Humanity's Last Exam (HLE), where rigid tool pipelines, brittle…
From Text to Simulation: A Multi-Agent LLM Workflow for Automated Chemical Process Design
Xufei Tian, Wenli Du, Shaoyi Yang +4
Process simulation is a critical cornerstone of chemical engineering design. Current automated chemical design methodologies focus mainly on various representations of process flow…
RLAX: Large-Scale, Distributed Reinforcement Learning for Large Language Models on TPUs
Runlong Zhou, Lefan Zhang, Shang-Chen Wu +29
Reinforcement learning (RL) has emerged as the de-facto paradigm for improving the reasoning capabilities of large language models (LLMs). We have developed RLAX, a scalable RL fra…