activity
20212026
most citedRethinking Image Forgery Detection via Soft Contrastive Learning and Unsupervised Clustering

8 citations · 22 across the 11 of their papers we have counts for

collaborators

13 papers

cs.CV2026

RiSE: Residual Subspace Expert for Generalizable Text-Centric Image Forgery Localization

Kahim Wong, Kemou Li, Yiming Chen +2

As AI-assisted image editing becomes increasingly prevalent, Text-Centric Image Forgery Localization (TFL) is essential for protecting trust in financial and legal records. However…

cs.CL2026

EASE: Entropy-Adaptive Distribution Shaping for Evading AI-generated Text Detectors

Jicheng Zhou, Kahim Wong, Jialong Wang +1

AI-generated text (AIGT) detection can be sensitive to the decoding choices of the source large language model (LLM). We observe that perturbing next-token logits or adjusting samp…

cs.AI2026

CABAL: Multi-Agent Simulacra for Tracing the Effects of Collusive Bidding in Peer Review

Jicheng Zhou, Kemou Li, Kahim Wong +5

Recent reports during the AAAI-27 review cycle highlight the risk of reviewers coordinating bids for reciprocal assignment advantage. Prior work treats bidding, reviewer assignment…

cs.CR2026

When Modalities Fail to Tango: Conformal Backdoor Detection in Multimodal Contrastive Learning

Yiming Chen, Kemou Li, Haiwei Wu +1

Backdoor attacks in multimodal contrastive learning (MCL) have garnered growing attention in recent years, as many downstream tasks critically depend on pre-trained MCL models. Exi…

cs.CV2026

Efficient, Robust, and Anti-Collusion Fingerprinting of Image Diffusion Models

Jianwei Fei, Yunshu Dai, Zhihua Xia +4

Model fingerprinting, embedding user-specific identifiers (fingerprints) into generated outputs, has recently emerged as a popular solution to protect the intellectual property rig…

cs.CV2026

SEED: Simple ViT and Evolving Harness for Explainable Text Forgery Detection

Kahim Wong, Kemou Li, Yiming Chen +2

AI-assisted image editing threatens trust in financial, legal, and identity records. The GenText-Forensics Challenge at ACM MM 2026 addresses this by requiring structured forensic…

cs.CL2026

NNProxy: Efficient Training-Free Proxy Alignment for Black-Box Zero-Shot LLM-Generated Text Detection

Kahim Wong, Kemou Li, Haiwei Wu +1

LLM-generated text (LGT) detection is essential for reliable forensic analysis and for mitigating LLM misuse. Existing LGT detectors can generally be categorized into two broad cla…

cs.CR2025

An End-to-End Model for Logits-Based Large Language Models Watermarking

Kahim Wong, Jicheng Zhou, Jiantao Zhou +1

The rise of LLMs has increased concerns over source tracing and copyright protection for AIGC, highlighting the need for advanced detection technologies. Passive detection methods…

cs.CR2023

Progressive Poisoned Data Isolation for Training-time Backdoor Defense

Yiming Chen, Haiwei Wu, Jiantao Zhou

Deep Neural Networks (DNN) are susceptible to backdoor attacks where malicious attackers manipulate the model's predictions via data poisoning. It is hence imperative to develop a…

cs.CV2023★ 8 cited

Rethinking Image Forgery Detection via Soft Contrastive Learning and Unsupervised Clustering

Haiwei Wu, Yiming Chen, Jiantao Zhou +1

Image forgery detection aims to detect and locate forged regions in an image. Most existing forgery detection algorithms formulate classification problems to classify pixels into f…

cs.CV2023★ 7 cited

Generalizable Synthetic Image Detection via Language-guided Contrastive Learning

Haiwei Wu, Jiantao Zhou, Shile Zhang

The heightened realism of AI-generated images can be attributed to the rapid development of synthetic models, including generative adversarial networks (GANs) and diffusion models…

cs.CV2022★ 7 cited

Exploring Spatial-Temporal Features for Deepfake Detection and Localization

Wu Haiwei, Zhou Jiantao, Zhang Shile +1

With the continuous research on Deepfake forensics, recent studies have attempted to provide the fine-grained localization of forgeries, in addition to the coarse classification at…

cs.CV2021

GIID-Net: Generalizable Image Inpainting Detection via Neural Architecture Search and Attention

Haiwei Wu, Jiantao Zhou

Deep learning (DL) has demonstrated its powerful capabilities in the field of image inpainting, which could produce visually plausible results. Meanwhile, the malicious use of adva…