7 papers
When Poison Fails After Retrieval: Revisiting Corpus Poisoning under Chunking and Reranking Pipelines
Xi Nie, Hongwei Li, Shenghao Wu +3
Retrieval-Augmented Generation (RAG) systems are vulnerable to corpus poisoning attacks that manipulate downstream model outputs through malicious knowledge injection. Existing stu…
A Sketch+Text Composed Image Retrieval Dataset for Thangka
Jinyu Xu, Yi Sun, Jiangling Zhang +6
Composed Image Retrieval (CIR) enables image retrieval by combining multiple query modalities, but existing benchmarks predominantly focus on general-domain imagery and rely on ref…
Reducing Oracle Feedback with Vision-Language Embeddings for Preference-Based RL
Udita Ghosh, Dripta S. Raychaudhuri, Jiachen Li +2
Preference-based reinforcement learning can learn effective reward functions from comparisons, but its scalability is constrained by the high cost of oracle feedback. Lightweight v…
Progressive Prompt-Guided Cross-Modal Reasoning for Referring Image Segmentation
Jiachen Li, Hongyun Wang, Jinyu Xu +5
Referring image segmentation aims to localize and segment a target object in an image based on a free-form referring expression. The core challenge lies in effectively bridging lin…
SDR-CIR: Semantic Debias Retrieval Framework for Training-Free Zero-Shot Composed Image Retrieval
Yi Sun, Jinyu Xu, Qing Xie +3
Composed Image Retrieval (CIR) aims to retrieve a target image from a query composed of a reference image and modification text. Recent training-free zero-shot methods often employ…
LGD: Leveraging Generative Descriptions for Zero-Shot Referring Image Segmentation
Jiachen Li, Qing Xie, Renshu Gu +3
Zero-shot referring image segmentation aims to locate and segment the target region based on a referring expression, with the primary challenge of aligning and matching semantics a…