3 papers
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.LG2025
Making Every Head Count: Sparse Attention Without the Speed-Performance Trade-off
Mingkuan Zhao, Wentao Hu, Jiayin Wang +5
The design of Large Language Models (LLMs) has long been hampered by a fundamental conflict within their core attention mechanism: its remarkable expressivity is built upon a compu…