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A. Tang

4 papers here

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

author position
  • first author1
  • middle author1

Across the 2 of 4 papers where every author was matched, so the position is known.

fields
  • cs.LG2
  • cs.CL1
  • physics.med-ph1
same name
  • A. Tang — 59 papers, h 71
  • A. Tang — 15 papers, h 51
  • A. Tang — 14 papers, h 18
  • A. Tang — 10 papers, h 31
  • A. Tang — 9 papers, h 4
  • A. Tang — 4 papers, h 19

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

physics.med-ph2025

Unsupervised deep learning model for fast energy layer pre-selection of delivery-efficient proton arc therapy plan optimization of nasopharyngeal carcinoma

Bohan Yang, Gang Liu, Yang Zhong +7

Proton arc therapy (PAT) is an emerging and promising modality in radiotherapy, offering improved dose distribution and treatment robustness over intensity-modulated proton therapy…

cs.CL2025

Mix Data or Merge Models? Balancing the Helpfulness, Honesty, and Harmlessness of Large Language Model via Model Merging

Jinluan Yang, Dingnan Jin, Anke Tang +10

Achieving balanced alignment of large language models (LLMs) in terms of Helpfulness, Honesty, and Harmlessness (3H optimization) constitutes a cornerstone of responsible AI. Exist…

cs.LG2025

Merging Models on the Fly Without Retraining: A Sequential Approach to Scalable Continual Model Merging

Anke Tang, Enneng Yang, Li Shen +4

Deep model merging represents an emerging research direction that combines multiple fine-tuned models to harness their specialized capabilities across different tasks and domains.…

cs.LG2025

Modeling Multi-Task Model Merging as Adaptive Projective Gradient Descent

Yongxian Wei, Anke Tang, Li Shen +3

Merging multiple expert models offers a promising approach for performing multi-task learning without accessing their original data. Existing methods attempt to alleviate task conf…

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