collaborators

5 papers

cs.LG2026

Cross-Tokenizer On-Policy Distillation via Byte-Prefix Marginalization

Hao Wang, Kun Yuan, Wenlin Zhong +4

Open-weight language models from different families exhibit complementary capabilities, motivating their consolidation into a compact student through on-policy distillation (OPD).…

cs.LG2026

GNMR: Runtime Stability Control for Low-Precision Large Language Model Training

Boao Kong, Weichen Jia, Engao Zhang +6

Training stability is a key bottleneck in low-precision language model training: efficient low-cost paths can still produce short-lived numerical risks at a small set of operators.…

cs.LG2026

Row-Stochastic Matrices Can Provably Outperform Doubly Stochastic Matrices in Decentralized Learning

Bing Liu, Boao Kong, Limin Lu +2

Decentralized learning often involves a weighted global loss with heterogeneous node weights . We revisit two natural strategies for incorporating these weights: (i) embedding t…

cs.LG2026

BROS: Bias-Corrected Randomized Subspaces for Memory-Efficient Single-Loop Bilevel Optimization

Hengrui Zhang, Boao Kong, Engao Zhang +1

Stochastic bilevel optimization (SBO) has become a standard framework for hyperparameter learning, data reweighting, representation learning, and data-mixture optimization in deep…

cs.LG2026

Synergistic Intra- and Cross-Layer Regularization Losses for MoE Expert Specialization

Rizhen Hu, Yuan Cao, Boao Kong +2

Sparse Mixture-of-Experts (MoE) models scale Transformers efficiently but suffer from expert overlap -- redundant representations across experts and routing ambiguity, resulting in…