12 citations · 18 across the 18 of their papers we have counts for
18 papers
From Vulnerable to Resilient: Examining Parent and Teen Perceptions on How to Respond to Unwanted Cybergrooming Advances
Xinyi Zhang, Mamtaj Akter, Heajun An +6
Cybergrooming is a form of online abuse that threatens teens' mental health and physical safety. Yet, most prior work has focused on detecting perpetrators' behaviors, leaving a li…
StagePilot: Stage-Level Planning for Long-Horizon Dialogue Simulation in Cybergrooming
Heajun An, Qi Zhang, Minqian Liu +5
Cybergrooming is an evolving threat to youth, requiring proactive educational interventions. We address this by modeling dialogue progression as a structured planning problem over…
Navigating Ideation Space: Decomposed Conceptual Representations for Positioning Scientific Ideas
Yuexi Shen, Minqian Liu, Dawei Zhou +1
Scientific discovery requires new ideas to be situated within an ever-expanding landscape of existing knowledge. An emerging challenge is how to identify conceptually relevant prio…
How Do Large Language Models Learn Concepts During Continual Pre-Training?
Barry Menglong Yao, Sha Li, Yunzhi Yao +4
Human beings primarily understand the world through concepts (e.g., dog), abstract mental representations that structure perception, reasoning, and learning. However, how large lan…
Scientific Hypothesis Generation and Validation: Methods, Datasets, and Future Directions
Adithya Kulkarni, Fatimah Alotaibi, Xinyue Zeng +7
Large Language Models (LLMs) are transforming scientific hypothesis generation and validation by enabling information synthesis, latent relationship discovery, and reasoning augmen…
LLM Can be a Dangerous Persuader: Empirical Study of Persuasion Safety in Large Language Models
Minqian Liu, Zhiyang Xu, Xinyi Zhang +8
Recent advancements in Large Language Models (LLMs) have enabled them to approach human-level persuasion capabilities. However, such potential also raises concerns about the safety…
Toward Integrated Solutions: A Systematic Interdisciplinary Review of Cybergrooming Research
Heajun An, Marcos Silva, Qi Zhang +8
Cybergrooming exploits minors through online trust-building, yet research remains fragmented, limiting holistic prevention. Social sciences focus on behavioral insights, while comp…
ReFocus: Visual Editing as a Chain of Thought for Structured Image Understanding
Xingyu Fu, Minqian Liu, Zhengyuan Yang +6
Structured image understanding, such as interpreting tables and charts, requires strategically refocusing across various structures and texts within an image, forming a reasoning s…
MetaScientist: A Human-AI Synergistic Framework for Automated Mechanical Metamaterial Design
Jingyuan Qi, Zian Jia, Minqian Liu +15
The discovery of novel mechanical metamaterials, whose properties are dominated by their engineered structures rather than chemical composition, is a knowledge-intensive and resour…
Modality-Specialized Synergizers for Interleaved Vision-Language Generalists
Zhiyang Xu, Minqian Liu, Ying Shen +5
Recent advancements in Vision-Language Models (VLMs) have led to the emergence of Vision-Language Generalists (VLGs) capable of understanding and generating both text and images. H…
Holistic Evaluation for Interleaved Text-and-Image Generation
Minqian Liu, Zhiyang Xu, Zihao Lin +4
Interleaved text-and-image generation has been an intriguing research direction, where the models are required to generate both images and text pieces in an arbitrary order. Despit…
X-Eval: Generalizable Multi-aspect Text Evaluation via Augmented Instruction Tuning with Auxiliary Evaluation Aspects
Minqian Liu, Ying Shen, Zhiyang Xu +5
Natural Language Generation (NLG) typically involves evaluating the generated text in various aspects (e.g., consistency and naturalness) to obtain a comprehensive assessment. Howe…
MULTISCRIPT: Multimodal Script Learning for Supporting Open Domain Everyday Tasks
Jingyuan Qi, Minqian Liu, Ying Shen +2
Automatically generating scripts (i.e. sequences of key steps described in text) from video demonstrations and reasoning about the subsequent steps are crucial to the modern AI vir…
Teamwork Is Not Always Good: An Empirical Study of Classifier Drift in Class-incremental Information Extraction
Minqian Liu, Lifu Huang
Class-incremental learning (CIL) aims to develop a learning system that can continually learn new classes from a data stream without forgetting previously learned classes. When lea…
Iteratively Improving Biomedical Entity Linking and Event Extraction via Hard Expectation-Maximization
Xiaochu Li, Minqian Liu, Zhiyang Xu +1
Biomedical entity linking and event extraction are two crucial tasks to support text understanding and retrieval in the biomedical domain. These two tasks intrinsically benefit eac…
The Art of SOCRATIC QUESTIONING: Recursive Thinking with Large Language Models
Jingyuan Qi, Zhiyang Xu, Ying Shen +4
Chain-of-Thought (CoT) prompting enables large language models to solve complex reasoning problems by generating intermediate steps. However, confined by its inherent single-pass a…
AMELI: Enhancing Multimodal Entity Linking with Fine-Grained Attributes
Barry Menglong Yao, Sijia Wang, Yu Chen +5
We propose attribute-aware multimodal entity linking, where the input consists of a mention described with a text paragraph and images, and the goal is to predict the corresponding…
Incremental Prompting: Episodic Memory Prompt for Lifelong Event Detection
Minqian Liu, Shiyu Chang, Lifu Huang
Lifelong event detection aims to incrementally update a model with new event types and data while retaining the capability on previously learned old types. One critical challenge i…