Tag
ConvMemory v3 introduces a validity context layer that detects outdated or superseded conversational memories using a target-conditioned dual-evidence gate, achieving high accuracy on synthetic benchmarks and zero-shot transfer to role binding tasks.
ConvMemory v2 is a recall-preserving reranker that reorders the top-10 candidates from ConvMemory v1 using a fine-tuned cross-encoder, improving MRR on the LoCoMo benchmark while preserving recall.
MemoryDocDataSet is a new synthetic benchmark of 50 micro-worlds and 1,000 QA pairs designed to evaluate AI systems on the joint task of conversational memory and long-document reasoning simultaneously. The best baseline (RAG-Both) achieves only 0.358 overall F1, highlighting a significant gap in current systems' ability to unify conversational memory with long-document navigation.
A novel memory retrieval system inspired by episodic memory theory achieves state-of-the-art 96.4% top-50 accuracy on the LongMemEval benchmark using Gemini Flash, outperforming larger Pro-based baselines by isolating retrieval quality from model capability.
EviMem combines IRIS for evidence-gap detection and LaceMem for layered memory to improve long-term conversational memory retrieval, achieving higher accuracy on temporal and multi-hop questions with lower latency.