7 papers
MoPe: Motion Permanence for Robust Monocular Gaussian Mapping in Dynamic Environments
Qixin Xiao
Robust robot autonomy depends on scene representations that remain stable enough to support localization, navigation, and downstream decision making in dynamic environments. Monocu…
MACD: Model-Aware Contrastive Decoding via Counterfactual Data
Qixin Xiao, Kun Zhou
Video language models (Video-LLMs) are prone to hallucinations, generating plausible but ungrounded content when visual evidence is weak, ambiguous, or biased. Existing methods, su…
CryptoBench: A Dynamic Benchmark for Expert-Level Evaluation of LLM Agents in Cryptocurrency
Jiacheng Guo, Suozhi Huang, Zixin Yao +16
This paper introduces CryptoBench, the first expert-curated, dynamic benchmark designed to rigorously evaluate the real-world capabilities of Large Language Model (LLM) agents in t…
LaWM: Least Action World Models for Long-Horizon Physical Consistency from Visual Observations
Qixin Xiao, Maani Ghaffari
Learning predictive world models from visual observations is a core problem in embodied AI, with applications to model-based reinforcement learning and robotic planning. Existing l…
LongNav-R1: Horizon-Adaptive Multi-Turn RL for Long-Horizon VLA Navigation
Yue Hu, Avery Xi, Qixin Xiao +4
This paper develops LongNav-R1, an end-to-end multi-turn reinforcement learning (RL) framework designed to optimize Visual-Language-Action (VLA) models for long-horizon navigation.…
CCAD: Compressed Global Feature Conditioned Anomaly Detection
Xiao Jin, Liang Diao, Qixin Xiao +4
Anomaly detection holds considerable industrial significance, especially in scenarios with limited anomalous data. Currently, reconstruction-based and unsupervised representation-b…