No official code found. Best implementation: hsp-iit/concon-chi_benchmark (10 stars, BSD-3-Clause, last commit 2024-04-03).
RA-TTA: Retrieval-Augmented Test-Time Adaptation for Vision-Language Models
3DIS: Depth-Driven Decoupled Image Synthesis for Universal Multi-Instance Generation
IVTP: Instruction-Guided Visual Token Pruning for Large Vision-Language Models
EvoControl: Multi-Frequency Bi-Level Control for High-Frequency Continuous Control
DCDM: Diffusion-Conditioned-Diffusion Model for Scene Text Image Super-Resolution
RFMamba: Frequency-Aware State Space Model for RF-Based Human-Centric Perception
@article{rosasco2026conconchi,
title = {ConCon-Chi: Concept-Context Chimera Benchmark for Personalized Vision-Language Tasks},
author = {Andrea Rosasco and Stefano Berti and Giulia Pasquale and Damiano Malafronte and Shogo Sato and Hiroyuki Segawa and Tetsugo Inada and Lorenzo Natale},
year = {2026},
doi = {10.1109/CVPR52733.2024.02099},
url = {https://doi.org/10.1109/CVPR52733.2024.02099},
journal = {CVPR 2024 2024}
}Shows whether official code is linked for this paper.
[](https://codeofpaper.com/paper/559f2ca6819e7777a4d61429ebbdc3fc798fbda9)