42 citations · 94 across the 32 of their papers we have counts for
6 papers · 1 filter
TRACE: Trajectory Representation and Consistency Estimation for AI-Generated Video Detection
Huangsen Cao, Hongkang chu, Siyao Yu +3
Recent advances in generative video models have enabled the synthesis of visually realistic content, posing significant challenges to synthetic video detection. Existing detectors…
ClueAegis: Heuristic-to-Reasoning Cognitive-skill Learning for Unified Evidence-based Synthetic Image Detection
Huangsen Cao, Hongkang Chu, Yuxi Li +6
The rapid advancement of generative models has made synthetic images increasingly realistic, challenging reliable detection. Existing methods are often limited to end-to-end classi…
Graph Topology Information Enhanced Heterogeneous Graph Representation Learning
He Zhao, Zhiwei Zeng, Yongwei Wang +1
Real-world heterogeneous graphs are inherently noisy and usually not in the optimal graph structures for downstream tasks, which often adversely affects the performance of GRL mode…
Enhancing Diffusion-Based Quantitatively Controllable Image Generation via Matrix-Form EDM and Adaptive Vicinal Training
Xin Ding, Yun Chen, Sen Zhang +5
Continuous Conditional Diffusion Model (CCDM) is a diffusion-based framework designed to generate high-quality images conditioned on continuous regression labels. Although CCDM has…
PretrainRL: Alleviating Factuality Hallucination of Large Language Models at the Beginning
Langming Liu, Kangtao Lv, Haibin Chen +8
Large language models (LLMs), despite their powerful capabilities, suffer from factual hallucinations where they generate verifiable falsehoods. We identify a root of this issue: t…
Data Distribution Matters: A Data-Centric Perspective on Context Compression for Large Language Model
Kangtao Lv, Jiwei Tang, Langming Liu +7
The deployment of Large Language Models (LLMs) in long-context scenarios is hindered by computational inefficiency and significant information redundancy. Although recent advanceme…