LT-Mem: Volatility-Aware Spatio-Temporal Memory for Lifelong Scene Understanding

LT-Mem introduces a volatility‑aware memory evolution framework for lifelong scene understanding, combining spatially aligned instance‑level 3D perception with temporal reasoning. It uses a multi‑session SLAM backbone, a reasoning layer that scores evidence and selects memory actions, and a Tri‑Memory structure (Live, Delta, Meta) to preserve current states and event histories. The accompanying LT‑VQA dataset provides multi‑session recordings, persistent identity annotations, and temporal QA pairs, and experiments show LT‑Mem outperforms baselines while using far fewer tokens.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at Hugging Face Trending Papers.

• llms
• robotics