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researcher

Xin Jiang

4 papers hereh-index 25 citations5 works total

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.CL1
  • cs.CV1
  • cs.GR1
  • cs.LG1
same name
  • Xin Jiang — 10 papers, h 6
  • Xin Jiang — 7 papers, h 4
  • Xin Jiang — 7 papers, h 6
  • Xin Jiang — 6 papers, h 3
  • Xin Jiang — 6 papers, h 6
  • Xin Jiang — 5 papers, h 5

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.CL2026

YouZhi: Towards High-Concurrency Financial LLMs via Adaptive GQA-to-MLA Transition

PSBC LLM Team, Huawei LLM Team, Ruihan Long +56

Large language models (LLMs) drive significant financial innovations, yet their high-concurrency deployment is severely bottlenecked by KV cache memory overhead, which inflates inf…

cs.CV2026

VLM-Pruner: Buffering for Spatial Sparsity in an Efficient VLM Centrifugal Token Pruning Paradigm

Zhenkai Wu, Xiaowen Ma, Zhenliang Ni +4

Vision-language models (VLMs) excel at image understanding tasks, but the large number of visual tokens imposes significant computational costs, hindering deployment on mobile devi…

cs.GR2026

IMAGAgent: Orchestrating Multi-Turn Image Editing via Constraint-Aware Planning and Reflection

Fei Shen, Chengyu Xie, Lihong Wang +4

Existing multi-turn image editing paradigms are often confined to isolated single-step execution. Due to a lack of context-awareness and closed-loop feedback mechanisms, they are p…

cs.LG2025

Expert Merging: Model Merging with Unsupervised Expert Alignment and Importance-Guided Layer Chunking

Dengming Zhang, Xiaowen Ma, Zhenliang Ni +4

Model merging, which combines multiple domain-specialized experts into a single model, offers a practical path to endow Large Language Models (LLMs) and Multimodal Large Language M…

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