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Xiang Liu

4 papers hereh-index 291 citations6 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author4

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.IR2
  • cs.AI1
  • cs.CL1
same name
  • Xiang Liu — 14 papers, h 12
  • Xiang Liu — 8 papers, h 4
  • Xiang Liu — 8 papers, h 1
  • Xiang Liu — 7 papers, h 4
  • Xiang Liu — 7 papers, h 4
  • Xiang Liu — 7 papers, h 2

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

collaborators

4 papers

cs.AI2026

GlobalDentBench: A Multinational Benchmark for Evaluating LLM Clinical Reasoning in Dentistry with Expert Calibration

Junjie Zhao, Jingyi Liang, Zhenyang Cai +22

While large language models (LLMs) hold transformative potential for medicine, their reasoning robustness and safety in real-world clinical scenarios remain critically underexplore…

cs.IR2026

RAG-Match: Retrieval-Augmented Knowledge Injection and Hierarchical Reasoning for Calibrated Semantic Relevance

Hengjun Jiang, Liansheng Sun, Yan Jiang +6

Semantic relevance judgment for search is particularly challenging in knowledge-intensive scenarios, where accurate ranking requires not only semantic matching but also background…

cs.IR2026

ResRank: Unifying Retrieval and Listwise Reranking via End-to-End Joint Training with Residual Passage Compression

Xiaojie Ke, Shuai Zhang, Liansheng Sun +6

Large language model (LLM) based listwise reranking has emerged as the dominant paradigm for achieving state-of-the-art ranking effectiveness in information retrieval. However, its…

cs.CL2026

How Does Alignment Enhance LLMs' Multilingual Capabilities? A Language Neurons Perspective

Shimao Zhang, Zhejian Lai, Xiang Liu +5

Multilingual Alignment is an effective and representative paradigm to enhance LLMs' multilingual capabilities, which transfers the capabilities from the high-resource languages to…

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