Tidyr's crossing() function not producing expected names in output - r

Question

I apologize in advance that I could not create a reproducible example, but when I do tidyr::crossing on some dataframes, I get a crossed tibble where the x variables have the form: x$col_name and the y variables have y$col_name. If I do:
crossing(iris,mtcars)
I get names that don't have the x$ prefix, as desired. I checked that the class of the input dataframes are the same as the example above, and there are no duplicate names in the example I'm working with. I can't share the data for the usual privacy reasons. I realize there is not much to work with here, but I'm hoping someone here is experience enough with tidyr to understand this issue.
Here is some session info:
R version 4.2.0 (2022-04-22 ucrt)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 19044)
Matrix products: default
locale:
[1] LC_COLLATE=English_United States.utf8 LC_CTYPE=English_United States.utf8
[3] LC_MONETARY=English_United States.utf8 LC_NUMERIC=C
[5] LC_TIME=English_United States.utf8
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] writexl_1.4.0 readxl_1.4.0 lubridate_1.8.0 forcats_0.5.1 stringr_1.4.0 dplyr_1.0.9
[7] purrr_0.3.4 readr_2.1.2 tidyr_1.2.0 tibble_3.1.7 ggplot2_3.3.6 tidyverse_1.3.1
loaded via a namespace (and not attached):
[1] cellranger_1.1.0 pillar_1.7.0 compiler_4.2.0 dbplyr_2.2.0 tools_4.2.0
[6] jsonlite_1.8.0 lifecycle_1.0.1 gtable_0.3.0 pkgconfig_2.0.3 rlang_1.0.2
[11] reprex_2.0.1 rstudioapi_0.13 DBI_1.1.3 cli_3.3.0 haven_2.5.0
[16] xml2_1.3.3 withr_2.5.0 httr_1.4.3 fs_1.5.2 generics_0.1.2
[21] vctrs_0.4.1 hms_1.1.1 grid_4.2.0 tidyselect_1.1.2 glue_1.6.2
[26] R6_2.5.1 fansi_1.0.3 tzdb_0.3.0 modelr_0.1.8 magrittr_2.0.3
[31] backports_1.4.1 scales_1.2.0 ellipsis_0.3.2 rvest_1.0.2 assertthat_0.2.1
[36] colorspace_2.0-3 utf8_1.2.2 stringi_1.7.6 munsell_0.5.0 broom_0.8.0
[41] crayon_1.5.1

Answer 1

Okay, the answer is simple:
crossing(iris,mtcars)
crossing(x = iris,y = mtcars)
This is rather odd behavior in my opinion.