Syntactically robust NLI for semantics of imperfectly generated text? [R]
Mirrored from r/MachineLearning for archival readability. Support the source by reading on the original site.
Hi all,
I'm looking for literature on relatively specific tooling.
In autoregressive LLMs, there is substantial published work that used NLI on sub-claims produced by LLMs to gauge correctness of LLM answers.
In diffusion (or D-) LLMs, the SoTA model generations that I see (outside of perhaps LLaDA) seem to struggle to be as correct syntactically as the generations from premier AR LLMs, in addition to the issue of semantic correctness.
My intuition is that this complicates the usage of NLI (the syntactic noise).
What is the SoTA on syntax-robust NLI?
[link] [comments]
More from r/MachineLearning
-
Loss functions in Instance Representation Learning [R]
Jun 29
-
Price elasticity model [R]
Jun 29
-
Rejected MICCAI paper: workshop -> journal/conference or directly journal/conference [R]
Jun 29
-
I built a demo agricultural planning system with an AI advisor for small-scale farmers in Nicaragua using NASA data [p]
Jun 29
Discussion (0)
Sign in to join the discussion. Free account, 30 seconds — email code or GitHub.
Sign in →No comments yet. Sign in and be the first to say something.