3 papers
cs.CL2026
Estimating Semantic Alphabet Size for LLM Uncertainty Quantification
Lucas H. McCabe, Rimon Melamed, Thomas Hartvigsen +1
Many black-box techniques for quantifying the uncertainty of large language models (LLMs) rely on repeated LLM sampling, which can be computationally expensive. Therefore, practica…
cs.CL2025
Demystifying optimized prompts in language models
Rimon Melamed, Lucas H. McCabe, H. Howie Huang
Modern language models (LMs) are not robust to out-of-distribution inputs. Machine generated (``optimized'') prompts can be used to modulate LM outputs and induce specific behavior…
cs.CL2024
Prompts have evil twins
Rimon Melamed, Lucas H. McCabe, Tanay Wakhare +3
We discover that many natural-language prompts can be replaced by corresponding prompts that are unintelligible to humans but that provably elicit similar behavior in language mode…