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cs.CV2026
Efficient Long-Context Modeling in Diffusion Language Models via Block Approximate Sparse Attention
Wenhu Zhang, Yiming Wu, Huanyu Wang +6
Diffusion Language Models (DLMs) enable globally coherent, bidirectional, and controllable text generation, offering advantages over traditional autoregressive LLMs, while scaling…
cs.LG2026
Convex Dataset Valuation for Post-Training
Siqi Zeng, Christopher Jung, Rui Li +7
Improving LLM performance on downstream tasks sometimes requires leveraging auxiliary datasets during post-training. In practice, however, developers face constraints on compute, l…
cs.LG2026
Expectation Error Bounds for Transfer Learning in Linear Regression and Linear Neural Networks
Meitong Liu, Christopher Jung, Rui Li +2
In transfer learning, the learner leverages auxiliary data to improve generalization on a main task. However, the precise theoretical understanding of when and how auxiliary data h…