collaborators

8 papers

cs.RO2026

Bionic Human-Motion Style Transfer for Physically Executable Whole-Body Control of Humanoid Robots

Tianchen Huang, Mingkuan Zhao, Yang Gao +8

Expressive whole-body motion is important for humanoid robots operating in human environments, where robots are expected to move stably while presenting readable and adjustable bod…

cs.CL2026

Regret Pre-training: Bridging Prior and Posterior Views for Enhanced Knowledge Grounding

Mingkuan Zhao, Xiayu Sun, Wentao Hu +5

Causal language models factorize sequence probabilities using only preceding context, leaving future information unexploited during training despite its availability in the trainin…

cs.CL2026

Hallucinations as Orthogonal Noise: Inference-Time Manifold Alignment via Dynamic Contextual Orthogonalization

Mingkuan Zhao, Wentao Hu, Tianchen Huang +6

Hallucination in Large Language Models (LLMs), characterized by the generation of content inconsistent with contextual facts or logical constraints -- remains a persistent challeng…

cs.CL2026

Resonant Context Anchoring: Decoupling Attention Routing and Signal Gain at Inference Time

Mingkuan Zhao, Yide Gao, Wentao Hu +6

Large Language Models (LLMs) frequently exhibit "contextual disregard" when faced with input evidence that conflicts with their internal parametric memory, leading to persistent fa…

cs.AI2026

PropLLM: Propagation-Aware Scene Reconstruction for Network Fault Diagnosis

Zongzong Wu, Ming Zhao, Fengxiao Tang +1

Network faults propagate layer by layer along topology and protocol dependencies, yet operations systems typically observe only symptomatic alerts at the tail end of propagation ch…

cs.LG2026

Awakening Dormant Experts:Counterfactual Routing to Mitigate MoE Hallucinations

Wentao Hu, Yanbo Zhai, Xiaohui Hu +6

Sparse Mixture-of-Experts (MoE) models have achieved remarkable scalability, yet they remain vulnerable to hallucinations, particularly when processing long-tail knowledge. We iden…