Hybrid Reasoning Agents Combine Latent Thinking with Text-Based Actions
Hybrid Reasoning Agents presents an approach to building LLM agents that reason in latent space while interacting with their environments through text. The project explores a hybrid design: internal reasoning can remain in a compact, nonverbal representation, while the agent’s observable actions and tool interactions are expressed as text. This separation aims to connect the efficiency of latent reasoning with the flexibility and compatibility of text-based agent interfaces. The project’s code is available in the Together Computer GitHub repository, with related models and resources collected on Hugging Face. An evaluation section is also included in the accompanying research paper, offering benchmarks for examining how the hybrid approach performs. Researchers and developers can review the announcement, implementation, model collection, and evaluation details through the links provided by the project.