repoGitHubTrust 82 · PrimaryPublished 1mo agoLive · 1mo ago
lotus-data/lotus
Optimized Agentic and LLM Bulk Processing Over Your Data
Lineage graph
Paper → model → repo connections mined from source citations (Tier-1 exact match).
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Every edge carries a method, confidence, and the source snippet that justified it — so bad links are debuggable.
- PossiblePossibly related (embedding) · 48%Structured memory filtering with metadata in AgentCore Memory →
- PossiblePossibly related (embedding) · 47%TraceLab: Characterizing Coding Agent Workloads for LLM Serving →
- PossiblePossibly related (embedding) · 47%MaDI-Bench: An End-to-End Data Integration Benchmark →
- PossiblePossibly related (embedding) · 46%AI agents need context everywhere they run, even where the cloud can't follow →
- PossiblePossibly related (embedding) · 46%A system-level approach to prompt injection: separating instruction and data channels in LLM agents [P] →
- PossiblePossibly related (embedding) · 50%PACE: A Proxy for Agentic Capability Evaluation →
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Implements
Related across the graph
paperTraceLab: Characterizing Coding Agent Workloads for LLM ServingnewsAI agents need context everywhere they run, even where the cloud can't follownewsStructured memory filtering with metadata in AgentCore MemorypaperPACE: A Proxy for Agentic Capability EvaluationpaperMaDI-Bench: An End-to-End Data Integration BenchmarknewsA system-level approach to prompt injection: separating instruction and data channels in LLM agents [P]