Natural Language Processing · Large Language Models · Interpretability
Linfeng Liu
I am a PhD student in the Department of Computer Science at the University of Cincinnati, advised by Prof. Tianyu Jiang in the cincyNLP Lab. My research explores how language and multimodal AI systems represent meaning beyond surface form.
I am especially interested in evaluation settings where literal pattern matching is not enough: non-compositional language, indirect visual reference, multilingual figurative generation, and geometric views of model-question interactions.
Research Interests
- Natural language processing
- Large language models
- Machine translation
- Multimodality
- Interpretability
Experience
- University of Cincinnati, PhD student, 2025-present
- University of Cincinnati, MS student, 2024-2025
- University of Cincinnati, undergraduate student, 2019-2024
- Chongqing University, undergraduate student, 2019-2024
Selected Publications
Evaluating the Impact of Verbal Multiword Expressions on Machine Translation
Linfeng Liu, Saptarshi Ghosh, Tianyu Jiang
ACL 2026 Main Conference
Evaluates how verbal multiword expressions affect machine translation quality across seven language pairs and eight machine translation systems.
evaluation · multiword expressions · machine translation
A Computational Approach to Visual Metonymy
Saptarshi Ghosh, Linfeng Liu, Tianyu Jiang
EACL 2026 Main Conference Oral
Introduces ViMET, a visual metonymy benchmark for testing whether vision-language models can interpret indirect associative cues rather than only literal depiction.
metonymy · semiotic theory · dataset · cognitive reasoning
A Geometric Lens on LLM Abilities through Joint Embedding Item Response Theory
Louie Hong Yao, Nicholas Jarvis, Tiffany Zhan, Saptarshi Ghosh, Linfeng Liu, Tianyu Jiang
Transactions on Machine Learning Research (TMLR), accepted, to appear
Introduces JE-IRT, a framework for analyzing LLM evaluation through shared geometric representations of abilities, item semantics, and difficulty.
large language models · interpretability · item response theory · joint embeddings
Preprints
Cross-Lingual Steering for Figurative Language Generation
Linfeng Liu, Tiffany Zhan, Louie Hong Yao, Saptarshi Ghosh, Tianyu Jiang
Uses activation steering to test whether figurative-language generation signals in multilingual LLMs are language-specific or reusable across languages.
figurative language · multilingual large language models · activation steering