4 papers
Evolving and Detecting Multi-Turn Deception using Geometric Signatures
Surender Suresh Kumar, Mary L. Cummings
Safety defenses for large language models (LLMs) are typically trained and evaluated on single-turn prompts, yet real attacks often unfold as indirect, multi-turn probing. To defen…
Assessing LLM code generation quality through path planning tasks
Wanyi Chen, Meng-Wen Su, Mary L. Cummings
As LLM-generated code grows in popularity, more evaluation is needed to assess the risks of using such tools, especially for safety-critical applications such as path planning. Exi…
To impute or not to impute: How machine learning modelers treat missing data
Wanyi Chen, Mary Cummings
Missing data is prevalent in tabular machine learning (ML) models, and different missing data treatment methods can significantly affect ML model training results. However, little…
Can LLMs plan paths in the real world?
Wanyi Chen, Meng-Wen Su, Nafisa Mehjabin +1
As large language models (LLMs) increasingly integrate into vehicle navigation systems, understanding their path-planning capability is crucial. We tested three LLMs through six re…