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Xitong Gao

4 papers here

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.LG3
  • cs.CV1
ORCID 0000-0002-2063-2051
same name
  • Xitong Gao — 22 papers, h 15
  • Xitong Gao — 1 paper, 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

most citedLearning the Unlearnable: Adversarial Augmentations Suppress Unlearnable Example Attacks

7 citations · 9 across the 4 of their papers we have counts for

collaborators

4 papers

cs.LG2024

Optimised Grouped-Query Attention Mechanism for Transformers

Yuang Chen, Cheng Zhang, Xitong Gao +3

Grouped-query attention (GQA) has been widely adopted in LLMs to mitigate the complexity of multi-head attention (MHA). To transform an MHA to a GQA, neighbour queries in MHA are e…

cs.LG2024

Unlocking the Global Synergies in Low-Rank Adapters

Zixi Zhang, Cheng Zhang, Xitong Gao +3

Low-rank Adaption (LoRA) has been the de-facto parameter-efficient fine-tuning technique for large language models. We present HeteroLoRA, a light-weight search algorithm that leve…

cs.CV2023★ 2 cited

APBench: A Unified Benchmark for Availability Poisoning Attacks and Defenses

Tianrui Qin, Xitong Gao, Juanjuan Zhao +2

The efficacy of availability poisoning, a method of poisoning data by injecting imperceptible perturbations to prevent its use in model training, has been a hot subject of investig…

cs.LG2023★ 7 cited

Learning the Unlearnable: Adversarial Augmentations Suppress Unlearnable Example Attacks

Tianrui Qin, Xitong Gao, Juanjuan Zhao +2

Unlearnable example attacks are data poisoning techniques that can be used to safeguard public data against unauthorized use for training deep learning models. These methods add st…

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