Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in Coakley et alK. L. Coakley, T. Snelleman, H. Hoos, and O. E. Gundersen, "The embrace of open science: An analysis of a decade of AI research and 56 800 conference papers," Under Review, 2026..
Token Merging for Training-Free Semantic Binding in Text-to-Image Synthesis
Authors: Taihang Hu, Linxuan Li, Joost van de Weijer, Hongcheng Gao, Fahad Shahbaz Khan, Jian Yang, Ming-Ming Cheng, KAI WANG, Yaxing Wang
NeurIPS 2024 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We conducted extensive experiments to validate the effectiveness of To Me, comparing it against various existing methods on the T2I-Comp Bench and our proposed GPT-4o object binding benchmark. |
| Researcher Affiliation | Academia | 1VCIP, College of Computer Science, Nankai University, 2NKIARI, Shenzhen Futian 3Computer Vision Center, Universitat Autònoma de Barcelona 4University of Chinese Academy of Sciences 5Mohamed bin Zayed University of AI, 6Linkoping University |
| Pseudocode | No | The paper describes the method and its components in text and with diagrams (e.g., Figure 4) but does not include structured pseudocode or an algorithm block. |
| Open Source Code | Yes | The code will be publicly available at https://github.com/hutaihang/To Me. |
| Open Datasets | Yes | Our final method To Me is quantitatively assessed using the widely adopted T2I-Comp Bench [31] and our proposed GPT-4o [1] object binding benchmark. |
| Dataset Splits | Yes | We follow the evaluation protocol [21, 30, 34] that using 300 validation prompts for evaluation under each subset |
| Hardware Specification | Yes | All experiments were conducted on an NVIDIA-A40 GPU. |
| Software Dependencies | No | The paper mentions software like SDXL, Spa Cy, CLIP, BLIP-VQA, Image Reward, and GPT-4o, but does not provide specific version numbers for these components. |
| Experiment Setup | Yes | The iterative composite token update is performed during the first 20% of the denoising steps Topt = 0.2T. ...the overall L = Lent + λ Lsem is computed by these two novel losses to update the composite token during each time t < Topt and λ is the trade-off hyperparameter. |