collaborators

10 papers

cs.CL2026

Is Human-Like Text Liked by Humans? Multilingual Human Detection and Preference Against AI

Yuxia Wang, Rui Xing, Jonibek Mansurov +23

Prior studies have shown that distinguishing text generated by Large Language Models (LLMs) from human-written one is highly challenging for humans, and often no better than random…

cs.CL2025

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 (…

cs.CL2025

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…

cs.CL2025

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…

cs.CL2025

Data Laundering: Artificially Boosting Benchmark Results through Knowledge Distillation

Jonibek Mansurov, Akhmed Sakip, Alham Fikri Aji

In this paper, we show that knowledge distillation can be subverted to manipulate language model benchmark scores, revealing a critical vulnerability in current evaluation practice…

cs.CL2025

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…