3 papers
cs.CL2025
LLMs are Frequency Pattern Learners in Natural Language Inference
Liang Cheng, Zhaowei Wang, Mark Steedman
While fine-tuning LLMs on NLI corpora improves their inferential performance, the underlying mechanisms driving this improvement remain largely opaque. In this work, we conduct a s…
cs.CL2025
S2LPP: Small-to-Large Prompt Prediction across LLMs
Liang Cheng, Tianyi LI, Zhaowei Wang +1
The performance of pre-trained Large Language Models (LLMs) is often sensitive to nuances in prompt templates, requiring careful prompt engineering, adding costs in terms of comput…
cs.CL2025
Neutralizing Bias in LLM Reasoning using Entailment Graphs
Liang Cheng, Tianyi Li, Zhaowei Wang +2
LLMs are often claimed to be capable of Natural Language Inference (NLI), which is widely regarded as a cornerstone of more complex forms of reasoning. However, recent works show t…