Beyond Memory: Harnessing Long-Horizon Agents with Explicit Belief States
PoS gives long-horizon agents an explicit, maintained belief state instead of relying on compressed history alone.
The framework tracks both the estimated world state and unresolved task requirements as the agent’s decision context. It validates consistency and watches for “Belief Trapping,” where the agent keeps acting without meaningful progress. Recovery is then matched to the trapping pattern and the unmet requirement. In experiments across four execution and diagnosis benchmarks, PoS led overall performance for all three tested LLM backbones. HF Daily Papers' note
The framework tracks both the estimated world state and unresolved task requirements as the agent’s decision context. It validates consistency and watches for “Belief Trapping,” where the agent keeps acting without meaningful progress. Recovery is then matched to the trapping pattern and the unmet requirement. In experiments across four execution and diagnosis benchmarks, PoS led overall performance for all three tested LLM backbones. HF Daily Papers' note
score 5