7 papers
Statement-Tuning Enables Efficient Cross-lingual Generalization in Encoder-only Models
Ahmed Elshabrawy, Thanh-Nhi Nguyen, Yeeun Kang +8
Large Language Models (LLMs) excel in zero-shot and few-shot tasks, but achieving similar performance with encoder-only models like BERT and RoBERTa has been challenging due to the…
Crosslingual Reasoning through Test-Time Scaling
Zheng-Xin Yong, M. Farid Adilazuarda, Jonibek Mansurov +7
Reasoning capabilities of large language models are primarily studied for English, even when pretrained models are multilingual. In this work, we investigate to what extent English…
Sherkala-Chat: Building a State-of-the-Art LLM for Kazakh in a Moderately Resourced Setting
Fajri Koto, Rituraj Joshi, Nurdaulet Mukhituly +31
Llama-3.1-Sherkala-8B-Chat, or Sherkala-Chat (8B) for short, is a state-of-the-art instruction-tuned open generative large language model (LLM) designed for Kazakh. Sherkala-Chat (…
GenAI Content Detection Task 1: English and Multilingual Machine-Generated Text Detection: AI vs. Human
Yuxia Wang, Artem Shelmanov, Jonibek Mansurov +23
We present the GenAI Content Detection Task~1 -- a shared task on binary machine generated text detection, conducted as a part of the GenAI workshop at COLING 2025. The task consis…
Qorgau: Evaluating LLM Safety in Kazakh-Russian Bilingual Contexts
Maiya Goloburda, Nurkhan Laiyk, Diana Turmakhan +11
Large language models (LLMs) are known to have the potential to generate harmful content, posing risks to users. While significant progress has been made in developing taxonomies f…
KazMMLU: Evaluating Language Models on Kazakh, Russian, and Regional Knowledge of Kazakhstan
Mukhammed Togmanov, Nurdaulet Mukhituly, Diana Turmakhan +11
Despite having a population of twenty million, Kazakhstan's culture and language remain underrepresented in the field of natural language processing. Although large language models…