Tag: AI scalability
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Boost Formal Theorem Provers Using Compiler Output Compression
Enhance formal theorem proving efficiency with compiler output compression and learning-to-refine frameworks for scalable, state-of-the-art reasoning.
Efficient Test-Time Search with Ordered Tokens in AR Models
Discover how coarse-to-fine ordered tokens improve test-time search efficiency and scalability in autoregressive generative models for image synthesis.
KumoRFM-2: Advanced Foundation Model for Relational Data
Discover KumoRFM-2, a scalable foundation model enhancing relational learning with superior performance and large-scale data processing capabilities.
Aethon: Fast Reference-Based Instantiation for Stateful AI Agents
Discover Aethon, a reference-based primitive enabling near-constant-time instantiation of stateful AI agents with reduced latency and memory overhead.
Overcoming Context Bottlenecks in LLMs with Reinforcement Learning
Discover how reinforcement learning and active context curation boost LLM efficiency and reasoning by solving the context bottleneck problem.