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cs.CL2026
LIME-LLM: Probing Models with Fluent Counterfactuals, Not Broken Text
George Mihaila, Suleyman Olcay Polat, Poli Nemkova +3
Local explanation methods such as LIME (Ribeiro et al., 2016) remain fundamental to trustworthy AI, yet their application to NLP is limited by a reliance on random token masking. T…
cs.CL2025
Cross-Lingual Stability and Bias in Instruction-Tuned Language Models for Humanitarian NLP
Poli Nemkova, Amrit Adhikari, Matthew Pearson +2
Humanitarian organizations face a critical choice: invest in costly commercial APIs or rely on free open-weight models for multilingual human rights monitoring. While commercial sy…
cs.CL2025
Do Large Language Models Know Conflict? Investigating Parametric vs. Non-Parametric Knowledge of LLMs for Conflict Forecasting
Apollinaire Poli Nemkova, Sarath Chandra Lingareddy, Sagnik Ray Choudhury +1
Large Language Models (LLMs) have shown impressive performance across natural language tasks, but their ability to forecast violent conflict remains underexplored. We investigate w…