1 citations · 1 across the 8 of their papers we have counts for
10 papers
Learning to Fuse LLMs with Ontology Rankers for Rare-Disease Diagnosis
Zhaoyang Jiang, Zhizhong Fu, Yunsoo Kim +5
Ontology rankers remain useful for rare-disease diagnosis because each candidate can be traced to matched patient phenotypes. Large language models (LLMs) can generate differential…
One Score, Two Decisions: Selective Prediction on the Rare-Disease Tail
Zhaoyang Jiang, Zhizhong Fu, Yunsoo Kim +5
Given a patient's clinical findings, a diagnostic system ranks possible diseases and must decide when to endorse its first prediction or defer it for review. This decision is usual…
Presentation, Not Mechanism: A Render Confound in Deprecation-Aware Memory Evaluation
Zhaoyang Jiang, Zhizhong Fu, Zicheng Li +5
AI systems increasingly retrieve from records that revise themselves: issue threads, encyclopedic histories, policy logs, and long conversations. The challenge is not only finding…
From Rigid to Dynamic: Entropy-Guided Adaptive Inference for Long-Context LLMs
Zhanchao Xu, Haoyang Li, Qingfa Xiao +4
Existing sparse attention and KV cache compression methods for long-context LLM inference typically apply fixed sparsity patterns or uniform budgets across all attention heads, ove…
AGRAG: Advanced Graph-based Retrieval-Augmented Generation for LLMs
Yubo Wang, Haoyang Li, Fei Teng +1
Graph-based retrieval-augmented generation (Graph-based RAG) has demonstrated significant potential in enhancing Large Language Models (LLMs) with structured knowledge. However, ex…
LLMLog: Advanced Log Template Generation via LLM-driven Multi-Round Annotation
Fei Teng, Haoyang Li, Lei Chen
Modern computing systems, such as HDFS and Spark, produce vast quantities of logs that developers use for tasks like anomaly detection and error analysis. To simplify log analysis,…
Understanding the Embedding Models on Hyper-relational Knowledge Graph
Yubo Wang, Shimin Di, Zhili Wang +4
Recently, Hyper-relational Knowledge Graphs (HKGs) have been proposed as an extension of traditional Knowledge Graphs (KGs) to better represent real-world facts with additional qua…
Exposing Numeracy Gaps: A Benchmark to Evaluate Fundamental Numerical Abilities in Large Language Models
Haoyang Li, Xuejia Chen, Zhanchao XU +8
Large Language Models (LLMs) have demonstrated impressive capabilities in natural language processing tasks, such as text generation and semantic understanding. However, their perf…
GORAG: Graph-based Online Retrieval Augmented Generation for Dynamic Few-shot Social Media Text Classification
Yubo Wang, Haoyang Li, Fei Teng +1
Text classification is vital for Web for Good applications like hate speech and misinformation detection. However, traditional models (e.g., BERT) often fail in dynamic few-shot se…
Cardinality Estimation on Hyper-relational Knowledge Graphs
Fei Teng, Haoyang Li, Shimin Di +1
Cardinality Estimation (CE) for query is to estimate the number of results without execution, which is an effective index in query optimization. Recently, CE for queries over knowl…