2 citations · 2 across the 8 of their papers we have counts for
6 papers · 1 filter
In the Guise of Correction: How Framing and Cultural Adaptation Erode LLM Safety on Real-World Criminal Cases
Mohsinul Kabir, Md. Tariquzzaman, Karam S. R. Elradie +4
Existing safety benchmarks rely largely on synthetic prompts with loosely grounded taxonomies and offer little focused analysis of severe crime categories. We introduce GUISE, a be…
Janus: A Benchmark for Goal-Conditioned Information Distortion in LLMs
Polydoros Giannouris, Mohsinul Kabir, Sophia Ananiadou
LLM deception is often evaluated through direct markers such as fabricated claims, explicit lies, or strategic concealment. However, many real-world misleading communications do no…
Same Claim, Different Judgment: Benchmarking Scenario-Induced Bias in Multilingual Financial Misinformation Detection
Zhiwei Liu, Yupen Cao, Yuechen Jiang +22
Large language models (LLMs) have been widely applied across various domains of finance. Since their training data are largely derived from human-authored corpora, LLMs may inherit…
Semantic Label Drift in Cross-Cultural Translation
Mohsinul Kabir, Tasnim Ahmed, Md Mezbaur Rahman +2
Machine Translation (MT) is widely employed to address resource scarcity in low-resource languages by generating synthetic data from high-resource counterparts. While sentiment pre…
MultiFinBen: Benchmarking Large Language Models for Multilingual and Multimodal Financial Application
Xueqing Peng, Lingfei Qian, Yan Wang +44
Real-world financial analysis involves information across multiple languages and modalities, from reports and news to scanned filings and meeting recordings. Yet most existing eval…
Plutus: Benchmarking Large Language Models in Low-Resource Greek Finance
Xueqing Peng, Triantafillos Papadopoulos, Efstathia Soufleri +7
Despite Greece's pivotal role in the global economy, large language models (LLMs) remain underexplored for Greek financial context due to the linguistic complexity of Greek and the…