You will be shown an excerpt from a computer science scientific research paper, followed by a question about the paper. Please answer the question. Do not include any text in your response other than the answer.

Context: Recently, large-scale text-to-image models (Rombach et al., 2021; Ramesh et al., 2021, 2022; Nichol et al., 2021; Yu et al., 2022; Saharia et al., 2022) have demonstrated an unprecedented capability to reason over natural language descriptions. They allow users to synthesize novel scenes with unseen compositions and produce vivid pictures in a myriad of styles. These tools have been used for artistic creation, as sources of inspiration, and even to design new, physical products (Yacoubian, 2022). Their use, however, is constrained by the user’s ability to describe the desired target through text. Turning back to Rose, one could then ask: How might she frame her request if she were to approach one of these models? How could we, as users, ask text-to-image models to craft a novel scene containing a cherished childhood toy? Or to pull our child’s drawing from its place on the fridge, and turn it into an artistic showpiece?

Question: They claim that LSTIM can synthesize unseen compositions. Is this true? What are some examples?
Assuming that “LSTIM” stands for “large-scale text-to-image models”, the authors mention a list of related work that demonstrate the efficacy of models such as these to reason over natural language queries and generate new art or images. However, whether this statement is true or not, or examples that would validate this claim are not explicitly spelled out in this paper.