Author

Hai-Yan Zhao

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#artificial intelligence Jun 2026

LC-QAT: Data-Efficient 2-Bit QAT for LLMs via Linear-Constrained Vector Quantization

LC-QAT is proposed, a 2-bit weight-only VQ-QAT framework that represents quantized weights via a learned affine mapping over discrete vectors, which yields a high-quality PTQ initialization and enables fully differentiable end-to-end optimization without explicit codebook lookup in the training forward pass.

Hao-Yu Wang, Xingyu Yu, Hai-Yan Zhao et al. · arXiv.org · 2 citations

#machine learning May 2026

Universal Activation Verbalizer: A Unified Framework for Cross-Model Activation Explanation

Universal Activation Verbalizer (UAV), a framework that uses a shared decoder to explain activations from heterogeneous donor models, and provides the activation-grounded factual and semantic information needed for faithful explanations.

Hai-Yan Zhao, Zirui He, Guan-Chun Wang et al. · arXiv.org · 1 citation