arXiv:2603. 29875v3 Announce Type: replace-cross Abstract: One of the key problems in Retrieval-augmented generation (RAG) systems is that chunk-based retrieval pipelines represent the source chunks as atomic objects, mixing the information contained within such a chunk into a single vector.
By Ryszard Tuora, Mateusz Gali\'nski, Micha{\l} Godziszewski, Micha{\l} Karpowicz, Mateusz Czy\.znikiewicz, Adam Kozakiewicz, Tomasz Zi\k{e}tkiewicz
arXiv:2606. 29860v1 Announce Type: new Abstract: Knowledge graphs (KGs) organize real-world knowledge as triplets and underpin many downstream applications.
By Zihao Zheng, Borui Cai, Yao Zhao, Keshav Sood, Yong Xiang
post-graph-rag is an open‑source PostgreSQL‑native engine that unifies chunks, embeddings, a canonical entity graph, and community summaries in a single database, using pgvector for search and edge tables for traversal. It validates extraction output—rejecting vague predicates, normalising predicates, resolving entities to unique vertices, and flagging negations—before writing, and employs a bi‑temporal layer to record when a relation held and when the system believed it, superseding incompatible earlier assertions. In benchmarks against LightRAG, it builds denser, more queryable graphs and achieves higher scores on LongMemEval, largely due to its temporal grounding in prompts.
By Chandan Rajah
The article discusses why retrieval quality should be inherent to the system rather than dependent on how a question is phrased. It proposes reconstructing the knowledge layer by performing graph traversal on every query, incorporating bitemporal edges, and applying a two‑threshold entity resolution approach. These techniques aim to make the knowledge graph more dynamic and responsive to user queries.
By Miodrag Cekikj
Knowledge graphs (KGs) organize real-world knowledge as triplets and underpin many downstream applications. Due to their inherent incompleteness, knowledge graph completion (KGC) is widely studied and is typically formulated as triplet prediction, with link prediction as the dominant paradigm.
arXiv:2609.01525v1 Announce Type: cross
Abstract: A durable assumption holds that graph analytics requires a purpose-built graph engine, and that relational systems are ill-suited to connected data....
By Gene Zhang