2 papers
cs.CL2026
Can We Trust LLM's Logic? Quantifying Uncertainty, Coherence, and Robustness via a Graph-Based Framework
Riccardo Revalor, Jalees Rehman, Debjit Pal
Large-Language Models (LLMs) can be prone to flawed and unfaithful reasoning that decoding strategies like Self-Consistency (SC) fail to detect as they evaluate only final-answer a…
cs.LG2025
Are LLMs Ready for Practical Adoption for Assertion Generation?
Vaishnavi Pulavarthi, Deeksha Nandal, Soham Dan +1
Assertions have been the de facto collateral for simulation-based and formal verification of hardware designs for over a decade. The quality of hardware verification, i.e., detecti…