27 citations · 81 across the 17 of their papers we have counts for
17 papers
Are LLMs Ready for Neural-integrated Mechanistic Modeling? A Benchmark and Agentic Framework
Zihan Guan, Rituparna Datta, Mengxuan Hu +5
Large language models (LLMs) have shown promise in constructing mechanistic models from data. However, existing evaluations largely focus on simplified settings and fail to capture…
Enhanced Diagnostic Performance via Large-Resolution Inference Optimization for Pathology Foundation Models
Mengxuan Hu, Zihan Guan, John Kang +2
Despite their prominent performance on tasks such as ROI classification and segmentation, many pathology foundation models remain constrained by a specific input size e.g. 224 x 22…
BEACON: Bayesian Optimal Stopping for Efficient LLM Sampling
Guangya Wan, Zixin Stephen Xu, Sasa Zorc +4
Sampling multiple responses is a common way to improve LLM output quality, but it comes at the cost of additional computation. The key challenge is deciding when to stop generating…
BalancEdit: Dynamically Balancing the Generality-Locality Trade-off in Multi-modal Model Editing
Dongliang Guo, Mengxuan Hu, Zihan Guan +2
Large multi-modal models inevitably decay over time as facts update and previously learned information becomes outdated. Traditional approaches such as fine-tuning are often imprac…
Benign Samples Matter! Fine-tuning On Outlier Benign Samples Severely Breaks Safety
Zihan Guan, Mengxuan Hu, Ronghang Zhu +2
Recent studies have uncovered a troubling vulnerability in the fine-tuning stage of large language models (LLMs): even fine-tuning on entirely benign datasets can lead to a signifi…
Backdoor in Seconds: Unlocking Vulnerabilities in Large Pre-trained Models via Model Editing
Dongliang Guo, Mengxuan Hu, Zihan Guan +3
Large pre-trained models have achieved notable success across a range of downstream tasks. However, recent research shows that a type of adversarial attack ( backdo…
No Free Lunch: Retrieval-Augmented Generation Undermines Fairness in LLMs, Even for Vigilant Users
Mengxuan Hu, Hongyi Wu, Zihan Guan +4
Retrieval-Augmented Generation (RAG) is widely adopted for its effectiveness and cost-efficiency in mitigating hallucinations and enhancing the domain-specific generation capabilit…
Causal Inference with Latent Variables: Recent Advances and Future Prospectives
Yaochen Zhu, Yinhan He, Jing Ma +3
Causality lays the foundation for the trajectory of our world. Causal inference (CI), which aims to infer intrinsic causal relations among variables of interest, has emerged as a c…
UFID: A Unified Framework for Input-level Backdoor Detection on Diffusion Models
Zihan Guan, Mengxuan Hu, Sheng Li +1
Diffusion models are vulnerable to backdoor attacks, where malicious attackers inject backdoors by poisoning certain training samples during the training stage. This poses a signif…
Img2Loc: Revisiting Image Geolocalization using Multi-modality Foundation Models and Image-based Retrieval-Augmented Generation
Zhongliang Zhou, Jielu Zhang, Zihan Guan +5
Geolocating precise locations from images presents a challenging problem in computer vision and information retrieval.Traditional methods typically employ either classification, wh…
Large Language Models for Causal Discovery: Current Landscape and Future Directions
Guangya Wan, Yunsheng Lu, Yuqi Wu +2
Causal discovery (CD) and Large Language Models (LLMs) have emerged as transformative fields in artificial intelligence that have evolved largely independently. While CD specialize…
Task-Driven Causal Feature Distillation: Towards Trustworthy Risk Prediction
Zhixuan Chu, Mengxuan Hu, Qing Cui +2
Since artificial intelligence has seen tremendous recent successes in many areas, it has sparked great interest in its potential for trustworthy and interpretable risk prediction.…
XAI meets Biology: A Comprehensive Review of Explainable AI in Bioinformatics Applications
Zhongliang Zhou, Mengxuan Hu, Mariah Salcedo +7
Artificial intelligence (AI), particularly machine learning and deep learning models, has significantly impacted bioinformatics research by offering powerful tools for analyzing co…
Identification of Causal Relationship between Amyloid-beta Accumulation and Alzheimer's Disease Progression via Counterfactual Inference
Haixing Dai, Mengxuan Hu, Qing Li +12
Alzheimer's disease (AD) is a neurodegenerative disorder that is beginning with amyloidosis, followed by neuronal loss and deterioration in structure, function, and cognition. The…
PharmacyGPT: The AI Pharmacist
Zhengliang Liu, Zihao Wu, Mengxuan Hu +12
In this study, we introduce PharmacyGPT, a novel framework to assess the capabilities of large language models (LLMs) such as ChatGPT and GPT-4 in emulating the role of clinical ph…
BadSAM: Exploring Security Vulnerabilities of SAM via Backdoor Attacks
Zihan Guan, Mengxuan Hu, Zhongliang Zhou +3
Recently, the Segment Anything Model (SAM) has gained significant attention as an image segmentation foundation model due to its strong performance on various downstream tasks. How…
Text2Seg: Remote Sensing Image Semantic Segmentation via Text-Guided Visual Foundation Models
Jielu Zhang, Zhongliang Zhou, Gengchen Mai +4
Remote sensing imagery has attracted significant attention in recent years due to its instrumental role in global environmental monitoring, land usage monitoring, and more. As imag…