tewiSong/MemPlan: LLM agents are flexible in language interaction, but using them as long-horizon planners is costly and prone to hallucinated or invalid actions. This paper targets a different role for LLMs: constrained bridges between language and symbolic planning. We propose MemPlan, a memo...
Pillar = mean of 3 scaled values = 0.0.
Awaiting first reading — these signals apply to this agent and will be ingested on the next tier tick: Product Hunt upvotes, Docker Hub pulls, Crates.io downloads (90d), Tech-news mentions (30d)
Not applicable — this agent doesn't have the prerequisite (no GitHub repo, no HF mirror, etc.) for these signals to ever apply: HF downloads (30d), npm weekly installs, PyPI monthly installs
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