Exponentiate regression results in huxtable

I'm putting together some tables with results from a series of Cox Proportional Hazards Models. I'd like to exponentiate the coefficients so the tables display the Hazard Ratios rather than the raw beta values. Does anyone know of a way to do this with huxtable? It's my preferred package for building regression tables. I've done some googling and can't find a solution.

You can use the tidy_args argument to huxreg:

library(huxtable)
library(survival)

test1 <- list(time=c(4,3,1,1,2,2,3), 
              status=c(1,1,1,0,1,1,0), 
              x=c(0,2,1,1,1,0,0), 
              sex=c(0,0,0,0,1,1,1)) 
mod <- coxph(Surv(time, status) ~ x + strata(sex), test1) 

huxreg(mod)
                           ─────────────────────────────────────────────────
                                                              (1)           
                                                   ─────────────────────────
                             x                                      0.802   
                                                                   (0.822)  
                                                   ─────────────────────────
                             N                                      5.000   
                             R2                                     0.144   
                             logLik                                -3.328   
                             AIC                                    8.655   
                           ─────────────────────────────────────────────────
                             *** p < 0.001; ** p < 0.01; * p < 0.05.        

Column names: names, model1

huxreg(mod, tidy_args = list(exponentiate = TRUE))
                           ─────────────────────────────────────────────────
                                                              (1)           
                                                   ─────────────────────────
                             x                                      2.231   
                                                                   (0.822)  
                                                   ─────────────────────────
                             N                                      5.000   
                             R2                                     0.144   
                             logLik                                -3.328   
                             AIC                                    8.655   
                           ─────────────────────────────────────────────────
                             *** p < 0.001; ** p < 0.01; * p < 0.05.        

Column names: names, model1

tidy(mod, exponentiate = TRUE) appears to exponentiate the coefficients but not the standard errors, which is presumably a bug in broom and worth reporting? Confidence intervals appear correct, though, so you can do:

huxreg(mod, tidy_args = list(exponentiate = TRUE), 
       error_format = "[{conf.low}-{conf.high}]", ci_level = 0.95)
                           ─────────────────────────────────────────────────
                                                              (1)           
                                                   ─────────────────────────
                             x                                      2.231   
                                                            [0.445-11.180]  
                                                   ─────────────────────────
                             N                                      5.000   
                             R2                                     0.144   
                             logLik                                -3.328   
                             AIC                                    8.655   
                           ─────────────────────────────────────────────────
                             *** p < 0.001; ** p < 0.01; * p < 0.05.        

Column names: names, model1