activity
20242026
collaborators

7 papers

cs.LG2026

Dictionary-Aligned Concept Control for Safeguarding Multimodal LLMs

Jinqi Luo, Jinyu Yang, Tal Neiman +5

Multimodal Large Language Models (MLLMs) have been shown to be vulnerable to malicious queries that can elicit unsafe responses. Recent work uses prompt engineering, response class…

cs.CL2026

SECA: Semantically Equivalent and Coherent Attacks for Eliciting LLM Hallucinations

Buyun Liang, Liangzu Peng, Jinqi Luo +3

Large Language Models (LLMs) are increasingly deployed in high-risk domains. However, state-of-the-art LLMs often exhibit hallucinations, raising serious concerns about their relia…

cs.CV2025

Voyaging into Perpetual Dynamic Scenes from a Single View

Fengrui Tian, Tianjiao Ding, Jinqi Luo +2

The problem of generating a perpetual dynamic scene from a single view is an important problem with widespread applications in augmented and virtual reality, and robotics. However,…

cs.AI2025

LogiCity: Advancing Neuro-Symbolic AI with Abstract Urban Simulation

Bowen Li, Zhaoyu Li, Qiwei Du +10

Recent years have witnessed the rapid development of Neuro-Symbolic (NeSy) AI systems, which integrate symbolic reasoning into deep neural networks. However, most of the existing b…

cs.CL2024

PaCE: Parsimonious Concept Engineering for Large Language Models

Jinqi Luo, Tianjiao Ding, Kwan Ho Ryan Chan +4

Large Language Models (LLMs) are being used for a wide variety of tasks. While they are capable of generating human-like responses, they can also produce undesirable output includi…

cs.CV2024

Contextual Knowledge Pursuit for Faithful Visual Synthesis

Jinqi Luo, Kwan Ho Ryan Chan, Dimitris Dimos +1

Modern text-to-vision generative models often hallucinate when the prompt describing the scene to be generated is underspecified. In large language models (LLMs), a prevalent strat…