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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 2026Show all

4 papers · 1 filter

cs.CL2026

Beyond Tokens: A Survey on Decoding Methods for Large Language and Vision-Language Models

Haoran Wang, Xiongxiao Xu, Philip S. Yu +1

Large language models (LLMs) and large vision-language models (LVLMs) have demonstrated impressive generative capabilities, yet ensuring their outputs align with user intent is sti…

cs.AI2026

Query-Only Backdoor Attacks on Self-Evolving Skills via Trajectory Poisoning

Yuyang Luo, Haoran Wang, Kai Shu

Agentic skills improve large language model (LLM) agents by encoding reusable procedures for complex tasks. However, manually authored skills often adapt poorly to long-horizon tas…

cs.CL2026

Do LLMs Know What Is Private Internally? Probing and Steering Contextual Privacy Norms in Large Language Model Representations

Haoran Wang, Li Xiong, Kai Shu

Large language models (LLMs) are increasingly deployed in high-stakes settings, yet they frequently violate contextual privacy by disclosing private information in situations where…

cs.LG2026

Big2Small: A Unifying Neural Network Framework for Model Compression

Jing-Xiao Liao, Haoran Wang, Tao Li +4

With the development of foundational models, model compression has become a critical requirement. Various model compression approaches have been proposed such as low-rank decomposi…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.