2 citations · 3 across the 9 of their papers we have counts for
10 papers
AfriGuard: Safety and Robust Refusal For African Languages
Israel Abebe Azime, Jesujoba O. Alabi, Iffat Maab +19
Large language models (LLMs) designed to interact with users are typically trained to respond appropriately to harmful or toxic content. However, ensuring appropriate responses bec…
AfrIFact: Cultural Information Retrieval, Evidence Extraction and Fact Checking for African Languages
Israel Abebe Azime, Jesujoba Oluwadara Alabi, Crystina Zhang +16
Assessing the veracity of a claim made online is a complex and important task with real-world implications. When these claims are directed at communities with limited access to inf…
AmharicStoryQA: A Multicultural Story Question Answering Benchmark in Amharic
Israel Abebe Azime, Abenezer Kebede Angamo, Hana Mekonen Tamiru +4
With the growing emphasis on multilingual and cultural evaluation benchmarks for large language models, language and culture are often treated as synonymous, and performance is com…
Decoding Partial Differential Equations: Cross-Modal Adaptation of Decoder-only Models to PDEs
Paloma García-de-Herreros, Philipp Slusallek, Dietrich Klakow +1
While large language models are primarily used on natural language tasks, they have also shown great promise when adapted to new modalities, e.g., for scientific machine learning t…
Accept or Deny? Evaluating LLM Fairness and Performance in Loan Approval across Table-to-Text Serialization Approaches
Israel Abebe Azime, Deborah D. Kanubala, Tejumade Afonja +4
Large Language Models (LLMs) are increasingly employed in high-stakes decision-making tasks, such as loan approvals. While their applications expand across domains, LLMs struggle t…
Bridging the Culture Gap: A Framework for LLM-Driven Socio-Cultural Localization of Math Word Problems in Low-Resource Languages
Israel Abebe Azime, Tadesse Destaw Belay, Dietrich Klakow +2
Large language models (LLMs) have demonstrated significant capabilities in solving mathematical problems expressed in natural language. However, multilingual and culturally-grounde…
Evaluating the Capabilities of Large Language Models for Multi-label Emotion Understanding
Tadesse Destaw Belay, Israel Abebe Azime, Abinew Ali Ayele +5
Large Language Models (LLMs) show promising learning and reasoning abilities. Compared to other NLP tasks, multilingual and multi-label emotion evaluation tasks are under-explored…
ProverbEval: Exploring LLM Evaluation Challenges for Low-resource Language Understanding
Israel Abebe Azime, Atnafu Lambebo Tonja, Tadesse Destaw Belay +11
With the rapid development of evaluation datasets to assess LLMs understanding across a wide range of subjects and domains, identifying a suitable language understanding benchmark…
What explains the success of cross-modal fine-tuning with ORCA?
Paloma García-de-Herreros, Vagrant Gautam, Philipp Slusallek +2
ORCA (Shen et al., 2023) is a recent technique for cross-modal fine-tuning, i.e., applying pre-trained transformer models to modalities beyond their training data. The technique co…
EthioLLM: Multilingual Large Language Models for Ethiopian Languages with Task Evaluation
Atnafu Lambebo Tonja, Israel Abebe Azime, Tadesse Destaw Belay +10
Large language models (LLMs) have gained popularity recently due to their outstanding performance in various downstream Natural Language Processing (NLP) tasks. However, low-resour…