4 papers
Improving Symbolic Translation of Language Models for Logical Reasoning
Ramya Keerthy Thatikonda, Jiuzhou Han, Wray Buntine +1
The use of formal language for deductive logical reasoning aligns well with language models (LMs), where translating natural language (NL) into first-order logic (FOL) and employin…
Logical Reasoning with Outcome Reward Models for Test-Time Scaling
Ramya Keerthy Thatikonda, Wray Buntine, Ehsan Shareghi
Logical reasoning is a critical benchmark for evaluating the capabilities of large language models (LLMs), as it reflects their ability to derive valid conclusions from given premi…
Assessing the Sensitivity and Alignment of FOL Closeness Metrics
Ramya Keerthy Thatikonda, Wray Buntine, Ehsan Shareghi
The recent successful paradigm of solving logical reasoning problems with tool-augmented large language models (LLMs) leverages translation of natural language (NL) statements into…
Strategies for Improving NL-to-FOL Translation with LLMs: Data Generation, Incremental Fine-Tuning, and Verification
Ramya Keerthy Thatikonda, Jiuzhou Han, Wray Buntine +1
Logical reasoning is a fundamental task in natural language processing that presents significant challenges to Large Language Models (LLMs). The inherent characteristics of logical…