3 papers
cs.AI2026
Quantization Inflates Reasoning: Token Inflation as a Hidden Cost of Low-Bit Reasoning Models
Xinyu Lian, Walid Krichene, Beichen Huang +4
Quantization is widely used to reduce the inference cost of large language models, but its effect on reasoning models is not fully captured by final-answer accuracy or per-token la…
cs.LG2026
Theory-Scale Auto-Formalization of Logics for Computer Science
Yuming Feng, Frederick Pu, One An +5
Auto-formalization is critical for scalable formal verification, but existing progress largely focuses on isolated statements, while theory-scale auto-formalization, which coherent…
cs.CL2025
TurnaboutLLM: A Deductive Reasoning Benchmark from Detective Games
Yuan Yuan, Muyu He, Muhammad Adil Shahid +3
This paper introduces TurnaboutLLM, a novel framework and dataset for evaluating the deductive reasoning abilities of Large Language Models (LLMs) by leveraging the interactive gam…