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This paper presents TRACE, a query processing framework that models conversational data as temporal evidence graphs to enable state-aware reasoning over evolving user states, improving temporal and multi-hop reasoning for long-conversation QA.
DBOSify is a drop-in replacement for Temporal Python that uses Postgres instead of a Temporal server, enabling durable workflows without additional infrastructure.
This blog post describes the architecture for a scalable ingestion pipeline using Temporal to handle crawling, extracting, chunking, and embedding customer documentation from various sources, emphasizing durability, statefulness, and concurrency control.
Graphiti is an open-source tool that builds human-like memory for AI agents using a continuously evolving, temporally-aware knowledge graph, achieving up to 18.5% higher accuracy and 90% lower latency compared to MemGPT.
Introduces the Temporal Contrastive Transformer (TCT), a self-supervised framework for learning temporal embeddings from financial transactions for fraud detection. Achieves AUC 0.8644 with embeddings alone but does not improve over strong engineered features (AUC 0.9205 vs 0.9245), indicating learned representations overlap with existing features.