3 citations · 7 across the 30 of their papers we have counts for
33 papers
SPIDER: Multi-Layer Semantic Token Pruning and Adaptive Sub-Layer Skipping in Multimodal Large Language Models
Tianxiang Chen, Zhentao Tan, Zi Ye +9
Multimodal Large Language Models face significant efficiency challenges that stem from two distinct yet coupled sources: data redundancy and computational redundancy. While most me…
PlanGuard: A Guardrail for Multi-Step Plan Safety in Embodied Agents
Junchi Chen, Changtao Miao, Yuxiao Xiang +9
Embodied task planners may produce multi-step plans whose subtask dependencies and interactions with the environment create physical risks during execution. Yet existing safeguards…
EraseSAE: Surgical Concept Erasure in Text-to-Video Diffusion Models via Sparse Autoencoders
Xinghao Wang, Dong Li, Wei Yu +5
Recent advances in text-to-video (T2V) diffusion models have demonstrated remarkable generative capabilities, yet their reliance on loosely curated training data raises pressing sa…
TimeSteer: Inference-Time Speech Scheduling in Joint Audio-Visual Diffusion Models
Chao Zhou, Yiling Chen, Qi Chu +3
Although pretrained joint audio-visual diffusion models offer rich control over \emph{what} to generate, they provide no explicit control over \emph{when} an utterance should occur…
Multi2AV-Safety: Benchmarking Safety in Multimodal-to-Audio-Video Generation
Kaichao Jiang, Changtao Miao, Baiqi Wu +9
Recent audio-video generators increasingly support joint conditioning on text, images, audio, and video. These capabilities also enable attacks that exploit cross-modal interaction…
Yesterday's Shield, Today's Spear: A Self-Evolving Safety Guardrail in Production
Cong Ming, Jingyi Chen, Bin Liu +4
Deployed LLM safety guardrails are predominantly static: trained once and frozen at release, while new jailbreak techniques and previously un-addressed harmful categories emerge wi…
VisCo: Leveraging Large Language Models as Intrinsic Encoders for Visual Token Compression
Yupeng Zheng, Kai Zou, Bin Liu +1
Vision-language models (VLMs) process large numbers of visual tokens, resulting in substantial inference latency and memory overhead. This has motivated extensive research on visua…
ANFI: Rethinking Neighbor Feature Interaction in Person Re-ID
Xulin Li, Yan Lu, Bin Liu +5
In person re-identification, neighbor-based methods have achieved significant success by interacting with neighbor samples to obtain more robust representations. However, existing…
SGF-CDNet: A Consistency-Discrepancy Graph Network over Semantic-Geometric Fused Nodes for Face Forgery Detection
Jiayao Jiang, Bin Liu, Nenghai Yu
The rapid advancement of deepfakes necessitates robust face forgery detection. Although forged faces may lack obvious artifacts, they often contain subtle disharmony among differen…
MFEN:Multi-Frequency Expert Network for Visible-Infrared Person Re-ID
Xulin Li, Yan Lu, Bin Liu +4
Visible-infrared person re-identification (VI-ReID) is challenging due to the large modality discrepancy between visible and infrared images. We contend that this discrepancy is la…
Advancing Aesthetic Image Generation via Composition Transfer
Kai Zou, Zhiwei Zhao, Bin Liu +1
Composition is a cornerstone of visual aesthetics, influencing the appeal of an image. While its principles operate independently of specific content, in practice, composition is o…
When Agents Look the Same: Quantifying Distillation-Induced Similarity in Tool-Use Behaviors
Chenghao Yang, Yuning Zhang, Zhoufutu Wen +4
Model distillation is a primary driver behind the rapid progress of LLM agents, yet it often leads to behavioral homogenization. Many emerging agents share nearly identical reasoni…
Learning to Focus and Precise Cropping: A Reinforcement Learning Framework with Information Gaps and Grounding Loss for MLLMs
Xuanpu Zhao, Zhentao Tan, Dianmo Sheng +6
To enhance the perception and reasoning capabilities of multimodal large language models in complex visual scenes, recent research has introduced agent-based workflows. In these wo…
SWIFT: Sliding Window Reconstruction for Few-Shot Training-Free Generated Video Attribution
Chao Wang, Zijin Yang, Yaofei Wang +4
Recent advancements in video generation technologies have been significant, resulting in their widespread application across multiple domains. However, concerns have been mounting…
HiAR: Efficient Autoregressive Long Video Generation via Hierarchical Denoising
Kai Zou, Dian Zheng, Hongbo Liu +3
Autoregressive (AR) diffusion offers a promising framework for generating videos of theoretically infinite length. However, a major challenge is maintaining temporal continuity whi…
SiGRRW: A Single-Watermark Robust Reversible Watermarking Framework with Guiding Strategy
Zikai Xu, Bin Liu, Weihai Li +2
Robust reversible watermarking (RRW) enables copyright protection for images while overcoming the limitation of distortion introduced by watermark itself. Current RRW schemes typic…
SAPL: Semantic-Agnostic Prompt Learning in CLIP for Weakly Supervised Image Manipulation Localization
Xinghao Wang, Changtao Miao, Dianmo Sheng +6
Malicious image manipulation threatens public safety and requires efficient localization methods. Existing approaches depend on costly pixel-level annotations which make training e…
GuardTrace-VL: Detecting Unsafe Multimodel Reasoning via Iterative Safety Supervision
Yuxiao Xiang, Junchi Chen, Zhenchao Jin +5
Multimodal large reasoning models (MLRMs) are increasingly deployed for vision-language tasks that produce explicit intermediate rationales. However, reasoning traces can contain u…
Training-Free In-Context Forensic Chain for Image Manipulation Detection and Localization
Rui Chen, Bin Liu, Changtao Miao +5
Advances in image tampering pose serious security threats, underscoring the need for effective image manipulation localization (IML). While supervised IML achieves strong performan…
LAKAN: Landmark-assisted Adaptive Kolmogorov-Arnold Network for Face Forgery Detection
Jiayao Jiang, Bin Liu, Qi Chu +1
The rapid development of deepfake generation techniques necessitates robust face forgery detection algorithms. While methods based on Convolutional Neural Networks (CNNs) and Trans…
Towards Anytime Retrieval: A Benchmark for Anytime Person Re-Identification
Xulin Li, Yan Lu, Bin Liu +6
In real applications, person re-identification (ReID) is expected to retrieve the target person at any time, including both daytime and nighttime, ranging from short-term to long-t…
Flora: Effortless Context Construction to Arbitrary Length and Scale
Tianxiang Chen, Zhentao Tan, Xiaofan Bo +5
Effectively handling long contexts is challenging for Large Language Models (LLMs) due to the rarity of long texts, high computational demands, and substantial forgetting of short-…
MARS-Bench: A Multi-turn Athletic Real-world Scenario Benchmark for Dialogue Evaluation
Chenghao Yang, Yinbo Luo, Zhoufutu Wen +8
Large Language Models (\textbf{LLMs}), e.g. ChatGPT, have been widely adopted in real-world dialogue applications. However, LLMs' robustness, especially in handling long complex di…
Context-Aware Weakly Supervised Image Manipulation Localization with SAM Refinement
Xinghao Wang, Tao Gong, Qi Chu +2
Malicious image manipulation poses societal risks, increasing the importance of effective image manipulation detection methods. Recent approaches in image manipulation detection ha…