10 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…
Language-Pretraining-Induced Bias: A Strong Foundation for General Vision Tasks
Yaxin Luo, Zhiqiang Shen
The ratio of outlier parameters in language pre-training models and vision pre-training models differs significantly, making cross-modality (language and vision) inherently more ch…
From Masks to Pixels and Meaning: A New Taxonomy, Benchmark, and Metrics for VLM Image Tampering
Xinyi Shang, Yi Tang, Jiacheng Cui +9
Existing tampering detection benchmarks largely rely on object masks, which severely misalign with the true edit signal: many pixels inside a mask are untouched or only trivially m…
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…
A Frustratingly Simple Yet Highly Effective Attack Baseline: Over 90% Success Rate Against the Strong Black-box Models of GPT-4.5/4o/o1
Zhaoyi Li, Xiaohan Zhao, Dong-Dong Wu +2
Despite promising performance on open-source large vision-language models (LVLMs), transfer-based targeted attacks often fail against closed-source commercial LVLMs. Analyzing fail…
Dataset Distillation via Committee Voting
Jiacheng Cui, Zhaoyi Li, Xiaochen Ma +3
Dataset distillation aims to synthesize a compact yet representative dataset that preserves the essential characteristics of the original data for efficient model training. Existin…
MoD: Exploring Mixture-of-Depth Adaptation for Multimodal Large Language Models
Yaxin Luo, Gen Luo, Jiayi Ji +4
Despite the significant progress in multimodal large language models (MLLMs), their high computational cost remains a barrier to real-world deployment. Inspired by the mixture of d…