1 citations · 1 across the 7 of their papers we have counts for
8 papers
Model the Edit, Not the Image: Visual Autoregressive Editing from a Source-Centric Perspective
Hongyi Fang, Chuwen Xie, Benjia Zhou +6
Next-scale visual autoregressive models (VARs) have emerged as a powerful generative paradigm, producing high-quality images through efficient coarse-to-fine prediction. However, t…
Nonlinearity-Aware LoRA: Structured Gate Adaptation under Low-Rank Constraints
Shuai Yuan, Sudong Cai, Bingzhi Chen +4
Low-rank adaptation (LoRA) is commonly viewed as an update-space approximation to full fine-tuning, yet this view is incomplete for self-gated Transformer feed-forward networks. In…
Auto-Relate: A Unified Approach to Discovering Reliable Functional Relationships Leveraging Statistical Tests
Ziyan Han, Yeye He, Shuyuan Kang +8
Tables in spreadsheets, computational notebooks, and databases often contain rich inter-column relationships. Yet these relationships are typically implicit and are often lost when…
GRASPrune: Global Gating for Budgeted Structured Pruning of Large Language Models
Ziyang Wang, Jiangfeng Xiao, Chuan Xiao +3
Large language models (LLMs) are expensive to serve because model parameters, attention computation, and KV caches impose substantial memory and latency costs. We present GRASPrune…
Efficient Query Rewrite Rule Discovery via Standardized Enumeration and Learning-to-Rank(extend)
Yuan Zhang, Yuxing Chen, Yuekun Yu +5
Query rewriting is essential for database performance optimization, but existing automated rule enumeration methods suffer from exponential search spaces, severe redundancy, and po…
Automatic String Data Validation with Pattern Discovery
Xinwei Lin, Jing Zhao, Peng Di +7
In enterprise data pipelines, data insertions occur periodically and may impact downstream services if data quality issues are not addressed. Typically, such problems can be invest…
Privacy-Enhanced Database Synthesis for Benchmark Publishing (Technical Report)
Yunqing Ge, Jianbin Qin, Shuyuan Zheng +7
Benchmarking is crucial for evaluating a DBMS, yet existing benchmarks often fail to reflect the varied nature of user workloads. As a result, there is increasing momentum toward c…
BClean: A Bayesian Data Cleaning System
Jianbin Qin, Sifan Huang, Yaoshu Wang +6
There is a considerable body of work on data cleaning which employs various principles to rectify erroneous data and transform a dirty dataset into a cleaner one. One of prevalent…