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cs.CL2026
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…
cs.CL2025
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…
cs.CL2025
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…