9 papers
Text-Attributed Knowledge Graph Enrichment with Large Language Models for Medical Concept Representation
Mohsen Nayebi Kerdabadi, Arya Hadizadeh Moghaddam, Chen Chen +2
In electronic health record (EHR) mining, learning high-quality representations of medical concepts (e.g., standardized diagnosis, medication, and procedure codes) is fundamental f…
RePrompT: Recurrent Prompt Tuning for Integrating Structured EHR Encoders with Large Language Models
Arya Hadizadeh Moghaddam, Drew Ross, Mohsen Nayebi Kerdabadi +2
Large Language Models (LLMs) have shown strong promise for mining Electronic Health Records (EHRs) by reasoning over longitudinal clinical information to capture context-rich patie…
Neural Structure Embedding for Symbolic Regression via Continuous Structure Search and Coefficient Optimization
Fateme Memar, Tao Zhe, Dongjie Wang
Symbolic regression aims to discover human-interpretable equations that explain observational data. However, existing approaches rely heavily on discrete structure search (e.g., ge…
City Editing: Hierarchical Agentic Execution for Dependency-Aware Urban Geospatial Modification
Rui Liu, Steven Jige Quan, Zhong-Ren Peng +6
As cities evolve over time, challenges such as traffic congestion and functional imbalance increasingly necessitate urban renewal through efficient modification of existing plans,…
Robust and Efficient Tool Orchestration via Layered Execution Structures with Reflective Correction
Tao Zhe, Haoyu Wang, Bo Luo +6
Tool invocation is a core capability of agentic systems, yet failures often arise not from individual tool calls but from how multiple tools are organized and executed together. Ex…
Permutation-Invariant Representation Learning for Robust and Privacy-Preserving Feature Selection
Rui Liu, Tao Zhe, Yanjie Fu +3
Feature selection eliminates redundancy among features to improve downstream task performance while reducing computational overhead. Existing methods often struggle to capture intr…