Can LLM answers with messy grammar still be checked reliably?
have been studied with methods that split an answer into smaller claims and use NLI to judge whether those claims are correct. Some , apart from possible exceptions such as LLaDA, can produce text that is less syntactically clean than leading . That creates a separate problem from whether the meaning is correct.
If the wording or sentence structure is noisy, NLI may struggle to judge the real meaning of the answer. The main need is NLI that stays reliable even when generated text has .
Key points
- NLI is often used to check smaller claims made inside LLM answers.
- may produce less syntactically clean text than top .
- Messy sentence structure can make meaning checks less reliable.
- The useful research area is NLI that can handle .