43 citations · 151 across the 29 of their papers we have counts for
6 papers · 1 filter
FaithformBench: Benchmarking Faithfulness of Mathematical Chain-of-Thought Autoformalisation
Rob Cornish, Iacopo Ghinassi, Po-Hung Yeh +7
Autoformalisation (AF) systems map natural language reasoning steps into formal statements in a proof assistant such as Lean. We consider how to assess the faithfulness of these sy…
Hierarchical Alignment: Enforcing Hierarchical Instruction-Following in LLMs through Logical Consistency
Shu Yang, Zihao Zhou, Di Wang +1
Large language models increasingly operate under multiple instructions from heterogeneous sources with different authority levels, including system policies, user requests, tool ou…
PiCSAR: Probabilistic Confidence Selection And Ranking for Reasoning Chains
Joshua Ong Jun Leang, Zheng Zhao, Aryo Pradipta Gema +7
Best-of-n sampling improves the accuracy of large language models (LLMs) and large reasoning models (LRMs) by generating multiple candidate solutions and selecting the one with the…
APE-Bench: Evaluating Automated Proof Engineering for Formal Math Libraries
Huajian Xin, Luming Li, Xiaoran Jin +2
While frontier formal mathematics systems now routinely develop repository-scale proof engineering artifacts requiring multi-file coordination and semantic correctness beyond compi…
Multilingual Mathematical Autoformalization
Albert Q. Jiang, Wenda Li, Mateja Jamnik
Autoformalization is the task of translating natural language materials into machine-verifiable formalisations. Progress in autoformalization research is hindered by the lack of a…
Decomposing the Enigma: Subgoal-based Demonstration Learning for Formal Theorem Proving
Xueliang Zhao, Wenda Li, Lingpeng Kong
Large language models~(LLMs) present an intriguing avenue of exploration in the domain of formal theorem proving. Nonetheless, the full utilization of these models, particularly in…