From Table 2, it appears that the word-level RL baseline performs better than Lite-Cat in terms of rewards.
figure 2 shows that the two LaRL models achieve strong task rewards with a much smaller performance drop in language quality (PPL), whereas the word-level  model can only increase its task rewards by deviating significantly from natural language.