7 citations · 7 across the 8 of their papers we have counts for
9 papers
Beyond Selection: Token Parameterization for Extreme Visual Token Compression
Rui Zhong, Yu Li, Zheyu Yan +1
Visual-token compression is effective for improving the efficiency of vision-language models, but under extreme compression budgets, token pruning can break visual grounding while…
TrainSDC: Characterizing and Mitigating Silent Data Corruption in Large Language Model Training
Zhipeng Xia, Haotian Xu, Siyu Yun +4
LLM training is increasingly vulnerable to silent data corruption (SDC), yet existing protection methods largely treat Transformer computations uniformly because their vulnerabilit…
LithoDreamer: A Physics-Informed World Model for Multi-Stage Computational Lithography
Yuqi Jiang, Yumeng Liu, Zimu Li +7
As semiconductor technology nodes scale, computational lithography is essential for ensuring yield and performance. However, lithography is a continuous physical process involving…
SafeSpec: Fast and Safe LLM via Dynamic Reflective Sampling
Haotian Xu, Zeyang Zhang, Linbao Li +3
Speculative inference accelerates large language model (LLM) decoding but provides no inherent safety guarantees. Existing safety defenses are largely incompatible with speculative…
Light Interaction: Training-Free Inference Acceleration for Interactive Video World Models
Jiacheng Lu, Haoyi Zhu, Sipei Yi +3
Interactive video world models generate video chunk by chunk in response to user-controlled camera movements, enabling applications such as real-time game simulation, virtual scene…
ScoRe-Flow: Complete Distributional Control via Score-Based Reinforcement Learning for Flow Matching
Xiaotian Qiu, Lukai Chen, Jinhao Li +3
Flow Matching (FM) policies have emerged as an efficient backbone for robotic control, offering fast and expressive action generation that underpins recent large-scale embodied AI…
FluxEDA: A Unified Execution Infrastructure for Stateful Agentic EDA
Zhengrui Chen, Zixuan Song, Yu Li +2
Large language models and autonomous agents are increasingly explored for EDA automation, but many existing integrations still rely on script-level or request-level interactions, w…
Unitho: A Unified Multi-Task Framework for Computational Lithography
Qian Jin, Yumeng Liu, Yuqi Jiang +2
Reliable, generalizable data foundations are critical for enabling large-scale models in computational lithography. However, essential tasks-mask generation, rule violation detecti…
SEM-CLIP: Precise Few-Shot Learning for Nanoscale Defect Detection in Scanning Electron Microscope Image
Qian Jin, Yuqi Jiang, Xudong Lu +5
In the field of integrated circuit manufacturing, the detection and classification of nanoscale wafer defects are critical for subsequent root cause analysis and yield enhancement.…