activity
20202026
most citedLearning Prediction Intervals for Regression: Generalization and Calibration

8 citations · 18 across the 16 of their papers we have counts for

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5 papers · 1 filter

cs.AI2026

MassAlloc Attention: Let Attention Allocate Its Own Compute

Jingze Shi, Zhangyang Peng, Xianduo Li +6

FullAttn often assigns negligible normalized mass to much of the causal score space, yet dense kernels execute the complete post-score path after forming each QK tile. We introduce…

cs.AI2026

CoWindow Attention: Full Causal Coverage Is a Collective Property

Jingze Shi, Zhangyang Peng, Xianduo Li +6

FullAttn repeatedly exposes the complete causal history to every attention head, creating substantial redundant computation and memory traffic even with IO-efficient dense kernels.…

cs.AI2026

Spec2Twin-Chain: Orchestrating Bi-Level Optimization with LLMs for Blockchain Digital Twin Construction

Haoting Zhang, Haoxian Chen, Jiayuan Sheng +4

Building a blockchain digital twin largely requires translating domain knowledge and specific system descriptions into a simulator architecture, calibrating its parameters against…

cs.LG2026

OPD+: Rethinking the Advantage Design for On-Policy Distillation

Hanyang Zhao, Haoxian Chen, Han Lin +3

On-policy distillation (OPD) is a widely used technique to transfer capabilities from capable teacher language models to the base student models, and can be formulated in a reinfor…

cs.CV2026

VMonarch: Efficient Video Diffusion Transformers with Structured Attention

Cheng Liang, Haoxian Chen, Liang Hou +4

The quadratic complexity of the attention mechanism severely limits the context scalability of Video Diffusion Transformers (DiTs). We find that the highly sparse spatio-temporal a…