1 citations · 1 across the 8 of their papers we have counts for
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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…