7 citations · 7 across the 11 of their papers we have counts for
7 papers · 1 filter
FigMirror: Ground It, Code It, Plot It
Xiaohan Zhao, Jiacheng Liu, Yaxin Luo +1
Converting scientific figures into executable code has gained increasing attention, yet existing methods primarily focus on reproducing the reference figure itself. A more practica…
AutoDesign: Meta-Harness Optimization for Long-Horizon Agentic Design
Yaxin Luo, Haobin Jiang, Jialv Zou +11
Transforming multimodal sources into condensed and structured media outputs can be fundamentally conceptualized as a long-horizon agentic process centered on a model-harness system…
Simple Domain Generalization for Strong Pixel-Level Image Tampering Detection in Modern VLMs
Yi Tang, Xinyi Shang, Jiacheng Cui +12
Modern vision-language models (VLMs) have significantly improved image generation and editing capabilities, making pixel-level image tampering detection increasingly important yet…
BiGain: Unified Token Compression for Joint Generation and Classification
Jiacheng Liu, Shengkun Tang, Jiacheng Cui +2
Acceleration methods for diffusion models (e.g., token merging or downsampling) typically optimize synthesis quality under reduced compute, yet often ignore discriminative capacity…
Exploring 3D Dataset Pruning
Xiaohan Zhao, Xinyi Shang, Jiacheng Liu +1
Dataset pruning has been widely studied for 2D images to remove redundancy and accelerate training, while particular pruning methods for 3D data remain largely unexplored. In this…
Hard Labels In! Rethinking the Role of Hard Labels in Mitigating Local Semantic Drift
Jiacheng Cui, Bingkui Tong, Xinyue Bi +3
Soft labels from teacher models are a de facto practice for knowledge transfer and large-scale dataset distillation (e.g., SRe2L, LPLD). However, when we limit the number of crops…
FADRM: Fast and Accurate Data Residual Matching for Dataset Distillation
Jiacheng Cui, Xinyue Bi, Yaxin Luo +3
Residual connection has been extensively studied and widely applied at the model architecture level. However, its potential in the more challenging data-centric approaches remains…