3 citations · 7 across the 14 of their papers we have counts for
13 papers
Mitigating Entangled Steering in Large Vision-Language Models for Hallucination Reduction
Yuanhong Zhang, Zhaoyang Wang, Xin Zhang +2
Large Vision-Language Models (LVLMs) have achieved remarkable success across cross-modal tasks but remain hindered by hallucinations, producing textual outputs inconsistent with vi…
Reinforcement-Guided Synthetic Data Generation for Privacy-Sensitive Identity Recognition
Xuemei Jia, Jiawei Du, Hui Wei +3
High-fidelity generative models are increasingly needed in privacy-sensitive scenarios, where access to data is severely restricted due to regulatory and copyright constraints. Thi…
IMS3: Breaking Distributional Aggregation in Diffusion-Based Dataset Distillation
Chenru Wang, Yunyi Chen, Zijun Yang +2
Dataset Distillation aims to synthesize compact datasets that can approximate the training efficacy of large-scale real datasets, offering an efficient solution to the increasing c…
SCOPE: Saliency-Coverage Oriented Token Pruning for Efficient Multimodel LLMs
Jinhong Deng, Wen Li, Joey Tianyi Zhou +1
Multimodal Large Language Models (MLLMs) typically process a large number of visual tokens, leading to considerable computational overhead, even though many of these tokens are red…
AEGIS: Authenticity Evaluation Benchmark for AI-Generated Video Sequences
Jieyu Li, Xin Zhang, Joey Tianyi Zhou
Recent advances in AI-generated content have fueled the rise of highly realistic synthetic videos, posing severe risks to societal trust and digital integrity. Existing benchmarks…
Modelship Attribution: Tracing Multi-Stage Manipulations Across Generative Models
Zhiya Tan, Xin Zhang, Joey Tianyi Zhou
As generative techniques become increasingly accessible, authentic visuals are frequently subjected to iterative alterations by various individuals employing a variety of tools. Cu…