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20232026
most citedMetaDiff: Meta-Learning with Conditional Diffusion for Few-Shot Learning

4 citations · 9 across the 19 of their papers we have counts for

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Showing 2026Show all

7 papers · 1 filter

cs.CV2026

SJD-SV: Speculative Jacobi Decoding with Semantics Verification for Autoregressive Image Generation

Baoquan Zhang, Bingqi Shan, Shihao Fang +3

Speculative Jacobi Decoding (SJD) is an important approach for accelerating autoregressive image generation. Although SJD has shown superior performance, recent studies point out t…

cs.SE2026

An Empirical Study for Android-to-OpenHarmony GUI Test Migration

Yakun Zhang, Xinjia Chen, Yiyun Chen +6

To reduce the substantial engineering effort required to test the corresponding applications from Android to OpenHarmony, migrating existing GUI test cases has become a critical pr…

cs.CV2026

Head-Aware Key-Value Compression for Efficient Autoregressive Image Generation

Guotao Liang, Baoquan Zhang, Zhiyuan Wen +1

Autoregressive (AR) visual generation has achieved remarkable performance but suffers from high memory usage and low throughput, as it requires caching previously generated visual…

cs.CV2026

S2FT: Parameter-Efficient Fine-Tuning in Sparse Spectrum Domain

Baoquan Zhang, Zhehao Yu, Lisai Zhang +5

Parameter Efficient Fine-Tuning (PEFT) is a key technique for adapting a large pretrained model to downstream tasks by fine-tuning only a small number of parameters. Recent methods…

cs.CV2026

SJD-VP: Speculative Jacobi Decoding with Verification Prediction for Autoregressive Image Generation

Bingqi Shan, Baoquan Zhang, Xiaochen Qi +3

Speculative Jacobi Decoding (SJD) has emerged as a promising method for accelerating autoregressive image generation. Despite its potential, existing SJD approaches often suffer fr…

cs.CV2026

SJD-PV: Speculative Jacobi Decoding with Phrase Verification for Autoregressive Image Generation

Zhehao Yu, Baoquan Zhang, Bingqi Shan +5

Autoregressive (AR) image models have recently demonstrated remarkable generative capability, but their sequential nature results in significant inference latency. Existing trainin…

cs.SE2026

LogiDroid: Individual Functional Test Generation via Business Logic Extraction and Adaptation

Yakun Zhang, Zihan Wang, Xinzhi Peng +6

Functional testing is essential for verifying that the business logic of mobile applications aligns with user requirements. Despite its importance, functional testing remains heavi…