5 citations · 6 across the 31 of their papers we have counts for
24 papers · 1 filter
Dataforge: Agentic Platform for Autonomous Data Engineering
Xinyuan Wang, Hongyu Cao, Kunpeng Liu +1
The growing demand for artificial intelligence (AI) applications in materials discovery, molecular modeling, and climate science has made data preparation a critical but labor-inte…
Learning to Route: A Rule-Driven Agent Framework for Hybrid-Source Retrieval-Augmented Generation
Haoyue Bai, Haoyu Wang, Shengyu Chen +5
Large Language Models (LLMs) have shown remarkable performance on general Question Answering (QA), yet they often struggle in domain-specific scenarios where accurate and up-to-dat…
Diffusion Policies with Offline and Inverse Reinforcement Learning for Promoting Physical Activity in Older Adults Using Wearable Sensors
Chang Liu, Ladda Thiamwong, Yanjie Fu +1
Utilizing offline reinforcement learning (RL) with real-world clinical data is getting increasing attention in AI for healthcare. However, implementation poses significant challeng…
ISACL: Internal State Analyzer for Copyrighted Training Data Leakage
Guangwei Zhang, Qisheng Su, Jiateng Liu +4
Large Language Models (LLMs) have revolutionized Natural Language Processing (NLP) but pose risks of inadvertently exposing copyrighted or proprietary data, especially when such da…
DELTA: Variational Disentangled Learning for Privacy-Preserving Data Reprogramming
Arun Vignesh Malarkkan, Haoyue Bai, Anjali Kaushik +1
In real-world applications, domain data often contains identifiable or sensitive attributes, is subject to strict regulations (e.g., HIPAA, GDPR), and requires explicit data featur…
Data-Efficient Symbolic Regression via Foundation Model Distillation
Wangyang Ying, Jinghan Zhang, Haoyue Bai +5
Discovering interpretable mathematical equations from observed data (a.k.a. equation discovery or symbolic regression) is a cornerstone of scientific discovery, enabling transparen…
Distribution Shift Aware Neural Tabular Learning
Wangyang Ying, Nanxu Gong, Dongjie Wang +5
Tabular learning transforms raw features into optimized spaces for downstream tasks, but its effectiveness deteriorates under distribution shifts between training and testing data.…
MMTok: Multimodal Coverage Maximization for Efficient Inference of VLMs
Sixun Dong, Juhua Hu, Mian Zhang +3
Vision-Language Models (VLMs) demonstrate impressive performance in understanding visual content with language instruction by converting visual inputs to vision tokens. However, re…
Incremental Causal Graph Learning for Online Cyberattack Detection in Cyber-Physical Infrastructures
Arun Vignesh Malarkkan, Dongjie Wang, Haoyue Bai +1
The escalating threat of cyberattacks on real-time critical infrastructures poses serious risks to public safety, demanding detection methods that effectively capture complex syste…
Rethinking Spatio-Temporal Anomaly Detection: A Vision for Causality-Driven Cybersecurity
Arun Vignesh Malarkkan, Haoyue Bai, Xinyuan Wang +3
As cyber-physical systems grow increasingly interconnected and spatially distributed, ensuring their resilience against evolving cyberattacks has become a critical priority. Spatio…
Supply Chain Optimization via Generative Simulation and Iterative Decision Policies
Haoyue Bai, Haoyu Wang, Nanxu Gong +4
High responsiveness and economic efficiency are critical objectives in supply chain transportation, both of which are influenced by strategic decisions on shipping mode. An integra…
Teaching Time Series to See and Speak: Forecasting with Aligned Visual and Textual Perspectives
Sixun Dong, Wei Fan, Teresa Wu +1
Time series forecasting traditionally relies on unimodal numerical inputs, which often struggle to capture high-level semantic patterns due to their dense and unstructured nature.…
LLM-ML Teaming: Integrated Symbolic Decoding and Gradient Search for Valid and Stable Generative Feature Transformation
Xinyuan Wang, Haoyue Bai, Nanxu Gong +4
Feature transformation enhances data representation by deriving new features from the original data. Generative AI offers potential for this task, but faces challenges in stable ge…
PageLLM: A Multi-Grained Reward Framework for Whole-Page Optimization with Large Language Models
Xinyuan Wang, Liang Wu, Dongjie Wang +1
Whole-page optimization (WPO) decides how search and recommendation results are surfaced to users, and large language models (LLMs) open a new route to it by treating page generati…
Efficient Post-Training Refinement of Latent Reasoning in Large Language Models
Xinyuan Wang, Dongjie Wang, Wangyang Ying +5
Reasoning is a key component of language understanding in Large Language Models. While Chain-of-Thought prompting enhances performance via explicit intermediate steps, it suffers f…
Brownian Bridge Augmented Surrogate Simulation and Injection Planning for Geological CO Storage
Haoyue Bai, Guodong Chen, Wangyang Ying +7
Geological CO2 storage (GCS) involves injecting captured CO2 into deep subsurface formations to support climate goals. The effective management of GCS relies on adaptive injection…
Bridging the Domain Gap in Equation Distillation with Reinforcement Feedback
Wangyang Ying, Haoyue Bai, Nanxu Gong +4
The data-to-equation (Data2Eqn) task aims to discover interpretable mathematical equations that map observed values to labels, offering physical insights and broad applicability ac…
Sculpting Features from Noise: Reward-Guided Hierarchical Diffusion for Task-Optimal Feature Transformation
Nanxu Gong, Zijun Li, Sixun Dong +4
Feature Transformation (FT) crafts new features from original ones via mathematical operations to enhance dataset expressiveness for downstream models. However, existing FT methods…
Agentic Feature Augmentation: Unifying Selection and Generation with Teaming, Planning, and Memories
Nanxu Gong, Sixun Dong, Haoyue Bai +3
As a widely-used and practical tool, feature engineering transforms raw data into discriminative features to advance AI model performance. However, existing methods usually apply f…
Weaver: Interweaving SQL and LLM for Table Reasoning
Rohit Khoja, Devanshu Gupta, Yanjie Fu +2
Querying tables with unstructured data is challenging due to the presence of text (or image), either embedded in the table or in external paragraphs, which traditional SQL struggle…
Unsupervised Feature Transformation via In-context Generation, Generator-critic LLM Agents, and Duet-play Teaming
Nanxu Gong, Xinyuan Wang, Wangyang Ying +4
Feature transformation involves generating a new set of features from the original dataset to enhance the data's utility. In certain domains like material performance screening, di…
A Survey on Data-Centric AI: Tabular Learning from Reinforcement Learning and Generative AI Perspective
Wangyang Ying, Cong Wei, Nanxu Gong +7
Tabular data is one of the most widely used data formats across various domains such as bioinformatics, healthcare, and marketing. As artificial intelligence moves towards a data-c…
MixLLM: Dynamic Routing in Mixed Large Language Models
Xinyuan Wang, Yanchi Liu, Wei Cheng +5
Large Language Models (LLMs) exhibit potential artificial generic intelligence recently, however, their usage is costly with high response latency. Given mixed LLMs with their own…
Towards Data-Centric AI: A Comprehensive Survey of Traditional, Reinforcement, and Generative Approaches for Tabular Data Transformation
Dongjie Wang, Yanyong Huang, Wangyang Ying +11
Tabular data is one of the most widely used formats across industries, driving critical applications in areas such as finance, healthcare, and marketing. In the era of data-centric…