Chechik, Gal

An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion

Gal, R., Alaluf, Y., Atzmon, Y., Patashnik, O., Bermano, A. H., Chechik, G., & Cohen-Or, D. (2022) · arXiv

Generative Adversarial Networks and Image SynthesisMultimodal Machine Learning Applications

Cited by 611

Learning Canonical Representations for Scene Graph to Image Generation

Herzig, R., Bar, A., Xu, H., Chechik, G., Darrell, T., & Globerson, A. (2020) · Lecture Notes in Computer Science

Generative Adversarial Networks and Image SynthesisMultimodal Machine Learning Applications

Cited by 92

Training-Free Consistent Text-to-Image Generation

Tewel, Y., Kaduri, O., Gal, R., Kasten, Y., Wolf, L., Chechik, G., & Atzmon, Y. (2024) · ACM Transactions on Graphics

Generative Adversarial Networks and Image SynthesisMultimodal Machine Learning Applications

Cited by 68

Reinforcement Learning with a Terminator

Tennenholtz, G., Merlis, N., Shani, L., Mannor, S., Shalit, U., Chechik, G., Hallak, A., & Dalal, G. (2022) · arXiv

Reinforcement Learning in RoboticsArtificial Intelligence in Games

Cited by 0

AblationBench: Evaluating Automated Planning of Ablations in Empirical AI Research

Abramovich, T., & Chechik, G. (2025) · arXiv

Topic ModelingArtificial Intelligence Applications

Cited by 0

Emergent Active Perception and Dexterity of Simulated Humanoids from Visual Reinforcement Learning

Luo, Z., Tessler, C., Lin, T., Yuan, Y., He, T., Xiao, W., Guo, Y., Chechik, G., Kitani, K., Fan, L., et al. (2025) · arXiv

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 0