2 citations · 2 across the 8 of their papers we have counts for
9 papers
Vis-Poison: Poisoning Visual Knowledge in Multimodal Retrieval-Augmented Generation
Rujin Liang, Zhongpu Chen, Yuhao Lei +1
While multimodal retrieval-augmented generation (RAG) systems increasingly rely on images as external knowledge sources, the introduction of poisoned visual evidence can severely c…
ContiGuard: A Framework for Continual Toxicity Detection Against Evolving Evasive Perturbations
Hankun Kang, Xin Miao, Jianhao Chen +5
Toxicity detection mitigates the dissemination of toxic content (e.g., hateful comments, posts, and messages within online social actions) to safeguard a healthy online social envi…
Beyond Static Snapshots: Dynamic Modeling and Forecasting of Group-Level Value Evolution with Large Language Models
Qiankun Pi, Guixin Su, Jinliang Li +5
Social simulation is critical for mining complex social dynamics and supporting data-driven decision making. LLM-based methods have emerged as powerful tools for this task by lever…
SwiftVLM: Efficient Vision-Language Model Inference via Cross-Layer Token Bypass
Chen Qian, Xinran Yu, Danyang Li +4
Visual token pruning is a promising approach for reducing the computational cost of vision-language models (VLMs), and existing methods often rely on early pruning decisions to imp…
Aligning VLM Assistants with Personalized Situated Cognition
Yongqi Li, Shen Zhou, Xiaohu Li +9
Vision-language models (VLMs) aligned with general human objectives, such as being harmless and hallucination-free, have become valuable assistants of humans in managing visual tas…
Reasoning based on symbolic and parametric knowledge bases: a survey
Mayi Xu, Yunfeng Ning, Yongqi Li +10
Reasoning is fundamental to human intelligence, and critical for problem-solving, decision-making, and critical thinking. Reasoning refers to drawing new conclusions based on exist…
Enhancing Relation Extraction via Supervised Rationale Verification and Feedback
Yongqi Li, Xin Miao, Shen Zhou +3
Despite the rapid progress that existing automated feedback methods have made in correcting the output of large language models (LLMs), these methods cannot be well applied to the…
Toxicity Detection towards Adaptability to Changing Perturbations
Hankun Kang, Jianhao Chen, Yongqi Li +5
Toxicity detection is crucial for maintaining the peace of the society. While existing methods perform well on normal toxic contents or those generated by specific perturbation met…
Prompting Large Language Models for Counterfactual Generation: An Empirical Study
Yongqi Li, Mayi Xu, Xin Miao +2
Large language models (LLMs) have made remarkable progress in a wide range of natural language understanding and generation tasks. However, their ability to generate counterfactual…