1 citations · 1 across the 10 of their papers we have counts for
10 papers
Harbor Adapters and Harbor-Index: Infrastructure and a Curated Meta-Dataset for Large-Scale Agentic Evaluation
Lin Shi, Haowei Lin, Zixuan Zhu +123
Evaluating agents on the growing number of agentic benchmarks is challenging because they often require complex environments and agent integrations. We introduce Harbor Adapters, a…
PrivateHub: Contrastive Diffusion Model for Private Sensor-Intensive Environment Data Generation
Jiechao Gao, Yuandong Pan, Jie Wang +2
Sensor-intensive environments enable many intelligent services by inferring user applications from heterogeneous data streams. However, not all applications should be exposed: user…
EGT-KG: Evidence-Grounded Typed KG Retrieval for Practical Scientific QA with Small Language Models
Muran Yu, Jiechao Gao, Yuandong Pan +5
For emerging scientific research domains, local Small Language Models (SLMs) are becoming more attractive, as they offer stronger privacy control and more stable deployment pipelin…
Clusters are All You Need: Pre-Training the Tsetlin Machine with Semantic Clusters from Language Models for Interpretability
Jiechao Gao, Rohan Kumar Yadav, Yuangang Li +4
Pre-trained language models such as BERT achieve strong text classification performance but lack transparency, limiting their use in high-stakes settings. The Tsetlin Machine (TM)…
The Orchestration Gap: Why Process Automation Stalls in Operationally Complex Industries
Jiechao Gao, Yuandong Pan. Yuangang Li, Jie Wang +2
Agentic systems have advanced quickly on digitally native tasks, yet they have barely touched the industries where coordinated automation could matter most: logistics, healthcare o…
S2D-ALIGN: Shallow-to-Deep Auxiliary Learning for Anatomically-Grounded Radiology Report Generation
Jiechao Gao, Chang Liu, Yuangang Li
Radiology Report Generation (RRG) aims to automatically generate diagnostic reports from radiology images. To achieve this, existing methods have leveraged the powerful cross-modal…
Mitigating Hallucinations in Large Language Models via Causal Reasoning
Yuangang Li, Yiqing Shen, Yi Nian +7
Large language models (LLMs) exhibit logically inconsistent hallucinations that appear coherent yet violate reasoning principles, with recent research suggesting an inverse relatio…
FedMetaMed: Federated Meta-Learning for Personalized Medication in Distributed Healthcare Systems
Jiechao Gao, Yuangang Li
Personalized medication aims to tailor healthcare to individual patient characteristics. However, the heterogeneity of patient data across healthcare systems presents significant c…
H-FedSN: Personalized Sparse Networks for Efficient and Accurate Hierarchical Federated Learning for IoT Applications
Jiechao Gao, Yuangang Li, Jie Wang +3
With the rapid development of the Internet of Things (IoT), federated learning (FL) has gained increasing attention for its privacy-preserving use of distributed data. However, con…
Fed-LDR: Federated Local Data-infused Graph Creation with Node-centric Model Refinement
Jiechao Gao, Yuangang Li, Syeda Faiza Ahmed
The rapid acceleration of global urbanization has introduced novel challenges in enhancing urban infrastructure and services. Spatio-temporal data, integrating spatial and temporal…