Lizhou Liang

The OmniAI Group of ZJU ACES Lab introduces EMem-Bench, a long-horizon embodied memory benchmark of 2,554 executable episodes spanning Passive Observation, Dynamic Tracking, Interaction Failure, and Experience Generalization, together with an external memory system EMem and an 8B policy EMem-8B; evaluating 16 open-source and proprietary MLLMs plus representative multimodal memory systems shows the strongest proprietary model Gemini-3-Flash reaches only 64.2% average success rate and most open-source models fall below 45%, while EMem achieves the best overall performance among matched backbones, improving Mistral-Small-3.1-24B by 16.4 points and GPT-5.4-mini by 23.6 points, with EMem-8B improving over Qwen3-VL-8B by 20.6 points.

The OmniAI Group of ZJU ACES Lab introduces EMem-Bench, a long-horizon embodied memory benchmark of 2,554 executable episodes spanning Passive Observation, Dynamic Tracking, Interaction Failure, and Experience Generalization, together with an external memory system EMem and an 8B policy EMem-8B; evaluating 16 open-source and proprietary MLLMs plus representative multimodal memory systems shows the strongest proprietary model Gemini-3-Flash reaches only 64.2% average success rate and most open-source models fall below 45%, while EMem achieves the best overall performance among matched backbones, improving Mistral-Small-3.1-24B by 16.4 points and GPT-5.4-mini by 23.6 points, with EMem-8B improving over Qwen3-VL-8B by 20.6 points.