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Haoran Wang

Emory University

17 papers hereh-index 11786 citations22 works total

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

author position
  • first author7
  • middle author9

Across the 16 of 17 papers where every author was matched, so the position is known.

fields
  • cs.CL9
  • cs.AI2
  • cs.CY2
  • cs.SI2
  • cs.CR1
  • cs.LG1
affiliations
  • Emory University
HomepageORCID 0000-0002-5787-3131
same name
  • Haoran Wang — 10 papers, h 15
  • Haoran Wang — 10 papers, h 6
  • Haoran Wang — 10 papers, h 5
  • Haoran Wang — 9 papers, h 12
  • Haoran Wang — 8 papers, h 3
  • Haoran Wang — 8 papers, h 3

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

activity
20222026
most citedTrustLLM: Trustworthiness in Large Language Models

54 citations · 81 across the 15 of their papers we have counts for

collaborators
Showing 2025 · cs.CLShow all

4 papers · 2 filters

cs.CL2025

Towards Effective Model Editing for LLM Personalization

Baixiang Huang, Limeng Cui, Jiapeng Liu +7

Personalization is becoming indispensable for LLMs to align with individual user preferences and needs. Yet current approaches are often computationally expensive, data-intensive,…

cs.CL2025★ 2 cited

Privacy-Aware Decoding: Mitigating Privacy Leakage of Large Language Models in Retrieval-Augmented Generation

Haoran Wang, Xiongxiao Xu, Baixiang Huang +1

Retrieval-Augmented Generation (RAG) enhances the factual accuracy of large language models (LLMs) by conditioning outputs on external knowledge sources. However, when retrieval in…

cs.CL2025

Can Multimodal LLMs Perform Time Series Anomaly Detection?

Xiongxiao Xu, Haoran Wang, Yueqing Liang +3

Time series anomaly detection (TSAD) has been a long-standing pillar problem in Web-scale systems and online infrastructures, such as service reliability monitoring, system fault d…

cs.CL2025

Benchmarking LLMs for Political Science: A United Nations Perspective

Yueqing Liang, Liangwei Yang, Chen Wang +6

Large Language Models (LLMs) have achieved significant advances in natural language processing, yet their potential for high-stake political decision-making remains largely unexplo…

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