8 papers
Measure, Don't Optimize: Forecasting Recovery in LLM Unlearning
Zirui Song, Huaxing Liu, Xiang Wang +8
Prior white-box studies show that large language models can retain latent traces of target knowledge after unlearning, even when the knowledge is no longer expressed in their outpu…
VeinCast: Physics-Guided Dynamic Field Graphs with Graph-Conditioned Fusion for Global Medium-Range Weather Forecasting
Zhisheng Chen, Jinhan Li, Yuxuan Li +6
Global medium-range weather forecasting requires modeling structured yet state-dependent interactions among heterogeneous atmospheric fields. Existing data-driven models largely le…
MemPrism: Task-Conditioned Relational Memory Views for Long-Horizon Agents
Zhisheng Chen, Bingfan Zeng, Bangde Cao +8
Long-horizon agents rely on memory to reuse experiences, yet existing memory systems often assume that evidence can be directly consumed through a fixed representation. This leads…
Token Predictors Are Not Planners: Building Physically Grounded Causal Reasoners
Zheng Lu, Mingqi Gao, Qinlei Xie +8
Current benchmarks for embodied vision-language planning often favor linguistic next-token prediction over physically grounded next-state reasoning. This rewards models that mimic…
MiMo-Embodied: X-Embodied Foundation Model Technical Report
Xiaoshuai Hao, Lei Zhou, Zhijian Huang +41
We open-source MiMo-Embodied, the first cross-embodied foundation model to successfully integrate and achieve state-of-the-art performance in both Autonomous Driving and Embodied A…
DSBench: A Comprehensive Benchmark for Evaluating External and In-Cabin Risks
Xianhui Meng, Yuchen Zhang, Zhijian Huang +12
Vision-Language Models (VLMs) show great promise for autonomous driving, but their suitability for safety-critical scenarios is largely unexplored, raising safety concerns. This is…