Verified65% confidenceFactTime unknown
MemGAS uses an Entropy Router to adaptively select the optimal memory granularity based on the entropy of the query's similarity distribution across different granularities.
3
Sources
65%
Confidence
Long-term
Relevance
6/1/2026
First Seen
Sources
MemGAS: Multi-Granularity Memory Association for Precise AI Agent Recall
bilibiliAgent智能体深度研究院
Related Entities
Related Claims
UnverifiedIn entropy-regularized reinforcement learning, the optimal policy is exactly of the Gibbs distribution form, and the coefficient of the entropy regularization term and the temperature are reciprocals of each other, making maximizing the entropy-regularized reward mathematically equivalent to matching the Gibbs distribution.70% similarVerifiedThe semantic entropy method is technically implemented by obtaining candidate answers through multiple samplings, using an NLI model to determine semantic equivalence for clustering, and then computing entropy over the semantic categories.70% similarUnverifiedSemantic entropy successfully recovers a usable confidence signal, filling the blind spot of token-level entropy on SLMs.69% similarUnverifiedThe concept of perplexity originates from entropy (Shannon Entropy) in information theory, and is essentially the average branching factor per prediction step of a language model.68% similarUnverifiedThe recursive entropic risk measure applies the risk operator in a nested fashion at each time step, satisfies time consistency, and can therefore be directly combined with the Bellman equation.68% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/20094API
curl https://kongchang.com/api/v1/knowledge/claims/20094MCP
get_claim(id=20094)