Typed operators for safe context management in long-running AI agents — CIKM 2026
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Updated
Aug 25, 2026 - Python
Typed operators for safe context management in long-running AI agents — CIKM 2026
Reproducibility artifact for the CIKM '26 paper: one query-agnostic preprocessing step takes HNSW from 21.1% to 95.8% recall@10 on attention-derived inner-product workloads, with no index changes.
Divergence-aware multi-agent routing that cuts LLM inference cost 10-100x. One signal routes queries, keys a multilingual cache, and detects hallucinations at AUC 0.90. CIKM 2026.
TelecomAudit (CIKM 2026): origin-aware benchmark auditing & calibration for 5G/Open RAN anomaly detection — exposes the synthetic→controlled-real transfer gap and repairs it with a small calibration budget.
The Recall Ceiling of LLM Recommendation Reranking (CIKM 2026) — code, processed datasets, and every result JSON cited in the paper
[CIKM 2026 Short Paper Track] Official code for the paper "When Can Pre-Trained Policies Be Reused? Inference-Time Policy Composition from Fixed Policy Libraries"
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