activity
20242026
collaborators

8 papers

cs.LG2026

MAG: MAnifold Guided Semi-Supervised Multi-modal In-Context Learning

Zirui Cheng, Xun Xu, Tiankai Chen +7

Few-shot in-context learning (ICL) with multi-modal large language models (MLLMs) enables task adaptation without parameter updates, but its performance is highly sensitive to the…

cs.CV2026

Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget

Guoxuan Chen, Chufeng Xiao, Haoran Yang +30

We introduce Boogu-Image-0.1, an open-source unified multimodal understanding and generation model family, comprising Base, Turbo, Edit, and Edit-Turbo variants. It delivers compet…

cs.CV2026

VII: Visual Instruction Injection for Jailbreaking Image-to-Video Generation Models

Bowen Zheng, Yongli Xiang, Ziming Hong +4

Image-to-Video (I2V) generation models, which condition video generation on reference images, have shown emerging visual instruction-following capability, allowing certain visual c…

cs.CL2025

SimLens for Early Exit in Large Language Models: Eliciting Accurate Latent Predictions with One More Token

Ming Ma, Bowen Zheng, Zhongqiao Lin +1

Intermediate-layer predictions in large language models (LLMs) are informative but hard to decode accurately, especially at early layers. Existing lens-style methods typically rely…

cs.CV2025

Integrated Pipeline for Monocular 3D Reconstruction and Finite Element Simulation in Industrial Applications

Bowen Zheng

To address the challenges of 3D modeling and structural simulation in industrial environment, such as the difficulty of equipment deployment, and the difficulty of balancing accura…

cs.LG2025

Revisiting Diffusion Models: From Generative Pre-training to One-Step Generation

Bowen Zheng, Tianming Yang

Diffusion distillation is a widely used technique to reduce the sampling cost of diffusion models, yet it often requires extensive training, and the student performance tends to be…

cs.CV2024

Diffusion Models Are Innate One-Step Generators

Bowen Zheng, Tianming Yang

Diffusion Models (DMs) have achieved great success in image generation and other fields. By fine sampling through the trajectory defined by the SDE/ODE solver based on a well-train…

cs.CL2024

Label Words as Local Task Vectors in In-Context Learning

Bowen Zheng, Ming Ma, Zhongqiao Lin +1

Large Language Models (LLMs) have demonstrated remarkable abilities, one of the most important being in-context learning (ICL). With ICL, LLMs can derive the underlying rule from a…