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Jiawei Jiang

4 papers hereh-index 13 citations9 works total

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

author position
  • middle author3
  • last author1

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

fields
  • cs.CL2
  • cs.AI1
  • cs.CV1
same name
  • Jiawei Jiang — 13 papers, h 5
  • Jiawei Jiang — 6 papers, h 1
  • Jiawei Jiang — 4 papers, h 4
  • Jiawei Jiang — 1 paper, h 0
  • Jiawei Jiang — 1 paper, h 25
  • Jiawei Jiang — 1 paper, h 6

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.CV2026

Visual Attention Drifts,but Anchors Hold:Mitigating Hallucination in Multimodal Large Language Models via Cross-Layer Visual Anchors

Chengxu Yang, Jingling Yuan, Chuang Hu +1

Multimodal Large Language Models often suffer from object hallucination. While existing research utilizes attention enhancement and visual retracing, we find these works lack suffi…

cs.CL2026

AdaCultureSafe: Adaptive Cultural Safety Grounded by Cultural Knowledge in Large Language Models

Hankun Kang, Di Lin, Zhirong Liao +5

With the widespread adoption of Large Language Models (LLMs), respecting indigenous cultures becomes essential for models' culturally safety and responsible global applications. Ex…

cs.CL2025

Heaven-Sent or Hell-Bent? Benchmarking the Intelligence and Defectiveness of LLM Hallucinations

Chengxu Yang, Jingling Yuan, Siqi Cai +2

Hallucinations in large language models (LLMs) are commonly regarded as errors to be minimized. However, recent perspectives suggest that some hallucinations may encode creative or…

cs.AI2025

REMISVFU: Vertical Federated Unlearning via Representation Misdirection for Intermediate Output Feature

Wenhan Wu, Zhili He, Huanghuang Liang +4

Data-protection regulations such as the GDPR grant every participant in a federated system a right to be forgotten. Federated unlearning has therefore emerged as a research frontie…

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