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researcher

Jiacheng Zhang

4 papers here

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

author position
  • first author1
  • middle author3

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

fields
  • cs.CV2
  • cs.LG2
same name
  • Jiacheng Zhang — 8 papers
  • Jiacheng Zhang — 5 papers, h 9
  • Jiacheng Zhang — 5 papers
  • Jiacheng Zhang — 5 papers, h 7
  • Jiacheng Zhang — 4 papers
  • Jiacheng Zhang — 2 papers

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

Let's Roll a BiFTA: Bi-refinement for Fine-grained Text-visual Alignment in Vision-Language Models

Yuhao Sun, Chengyi Cai, Jiacheng Zhang +3

Recent research has shown that aligning fine-grained text descriptions with localized image patches can significantly improve the zero-shot performance of pre-trained vision-langua…

cs.LG2025

MoRA: On-the-fly Molecule-aware Low-Rank Adaptation Framework for LLM-based Multi-Modal Molecular Assistant

Tao Yin, Xiaohong Zhang, Jiacheng Zhang +5

Effectively integrating molecular graph structures with Large Language Models (LLMs) is a key challenge in drug discovery. Most existing multi-modal alignment methods typically pro…

cs.CV2025

NTIRE 2025 Challenge on Day and Night Raindrop Removal for Dual-Focused Images: Methods and Results

Xin Li, Yeying Jin, Xin Jin +134

This paper reviews the NTIRE 2025 Challenge on Day and Night Raindrop Removal for Dual-Focused Images. This challenge received a wide range of impressive solutions, which are devel…

cs.LG2025

One Stone, Two Birds: Enhancing Adversarial Defense Through the Lens of Distributional Discrepancy

Jiacheng Zhang, Benjamin I. P. Rubinstein, Jingfeng Zhang +1

Statistical adversarial data detection (SADD) detects whether an upcoming batch contains adversarial examples (AEs) by measuring the distributional discrepancies between clean exam…

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