15 papers
Extreme Compression of Per-Layer Embeddings via Cross-Layer Latent Vector Quantization
Jiacheng Liu, Yaxin Luo, Xiaohan Zhao +5
Scaling embedding capacity alongside Transformer computation is an emerging trend in language models. This trend makes high compression rates increasingly useful. Hence, we study e…
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…
Operation-Guided Progressive Human-to-AI Text Transformation Benchmark for Multi-Granularity AI-Text Detection
Sondos Mahmoud Bsharat, Jiacheng Liu, Xiaohan Zhao +9
As AI writing assistants become increasingly integrated into real-world drafting and revision workflows, many documents are no longer purely human-written or AI-generated, but inst…
LLMSurgeon: Diagnosing Data Mixture of Large Language Models
Yaxin Luo, Jiacheng Cui, Xiaohan Zhao +5
The pretraining data mixture of Large Language Models (LLMs) constitutes their "digital DNA", shaping model behaviors, capabilities, and failure modes. Yet this composition is rare…
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…
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…
Pushing the Frontier of Black-Box LVLM Attacks via Fine-Grained Detail Targeting
Xiaohan Zhao, Zhaoyi Li, Yaxin Luo +2
Black-box adversarial attacks on Large Vision-Language Models (LVLMs) are challenging due to missing gradients and complex multimodal boundaries. Prior state-of-the-art transfer-ba…
Next-Gen CAPTCHAs: Leveraging the Cognitive Gap for Scalable and Diverse GUI-Agent Defense
Jiacheng Liu, Yaxin Luo, Jiacheng Cui +3
The rapid evolution of GUI-enabled agents has rendered traditional CAPTCHAs obsolete. While previous benchmarks like OpenCaptchaWorld established a baseline for evaluating multimod…
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…
Learning Robust Diffusion Models from Imprecise Supervision
Dong-Dong Wu, Jiacheng Cui, Wei Wang +2
Conditional diffusion models have achieved remarkable success in various generative tasks recently, but their training typically relies on large-scale datasets that inevitably cont…
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…
Open CaptchaWorld: A Comprehensive Web-based Platform for Testing and Benchmarking Multimodal LLM Agents
Yaxin Luo, Zhaoyi Li, Jiacheng Liu +3
CAPTCHAs have been a critical bottleneck for deploying web agents in real-world applications, often blocking them from completing end-to-end automation tasks. While modern multimod…
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…