46 citations · 54 across the 7 of their papers we have counts for
7 papers
Reasoning-Enhanced Healthcare Predictions with Knowledge Graph Community Retrieval
Pengcheng Jiang, Cao Xiao, Minhao Jiang +4
Large language models (LLMs) have demonstrated significant potential in clinical decision support. Yet LLMs still suffer from hallucinations and lack fine-grained contextual medica…
Certifiably Byzantine-Robust Federated Conformal Prediction
Mintong Kang, Zhen Lin, Jimeng Sun +2
Conformal prediction has shown impressive capacity in constructing statistically rigorous prediction sets for machine learning models with exchangeable data samples. The siloed dat…
KG-FIT: Knowledge Graph Fine-Tuning Upon Open-World Knowledge
Pengcheng Jiang, Lang Cao, Cao Xiao +3
Knowledge Graph Embedding (KGE) techniques are crucial in learning compact representations of entities and relations within a knowledge graph, facilitating efficient reasoning and…
TriSum: Learning Summarization Ability from Large Language Models with Structured Rationale
Pengcheng Jiang, Cao Xiao, Zifeng Wang +3
The advent of large language models (LLMs) has significantly advanced natural language processing tasks like text summarization. However, their large size and computational demands…
PILOT: Legal Case Outcome Prediction with Case Law
Lang Cao, Zifeng Wang, Cao Xiao +1
Machine learning shows promise in predicting the outcome of legal cases, but most research has concentrated on civil law cases rather than case law systems. We identified two uniqu…
ConSequence: Synthesizing Logically Constrained Sequences for Electronic Health Record Generation
Brandon Theodorou, Shrusti Jain, Cao Xiao +1
Generative models can produce synthetic patient records for analytical tasks when real data is unavailable or limited. However, current methods struggle with adhering to domain-spe…
Synthesize High-dimensional Longitudinal Electronic Health Records via Hierarchical Autoregressive Language Model
Brandon Theodorou, Cao Xiao, Jimeng Sun
Synthetic electronic health records (EHRs) that are both realistic and preserve privacy can serve as an alternative to real EHRs for machine learning (ML) modeling and statistical…