8 papers
Exploring Language-Agnosticity in Function Vectors: A Case Study in Machine Translation
Nurkhan Laiyk, Gerard I. Gállego, Javier Ferrando +1
Function vectors (FVs) are vector representations of tasks extracted from model activations during in-context learning. While prior work has shown that multilingual model represent…
Why Don't You Know? Evaluating the Impact of Uncertainty Sources on Uncertainty Quantification in LLMs
Maiya Goloburda, Roman Vashurin, Fedor Chernogorskii +4
As Large Language Models (LLMs) are increasingly deployed in real-world applications, reliable uncertainty quantification (UQ) becomes critical for safe and effective use. Most exi…
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…
Instruction Tuning on Public Government and Cultural Data for Low-Resource Language: a Case Study in Kazakh
Nurkhan Laiyk, Daniil Orel, Rituraj Joshi +4
Instruction tuning in low-resource languages remains underexplored due to limited text data, particularly in government and cultural domains. To address this, we introduce and open…
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 (…
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…