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National Information Processing Institute

Academic institutionasia · kr
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Research library8linked papers
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Selected work

Representative Papers

Long-Context Encoder Models for Polish Language Understanding

Mar 12, 2026

This work addresses the limitation of Polish BERT-style encoders in processing long documents due to their short context windows. We propose a two-stage training strategy: first extending positional embeddings to support a context length of 8,192 tokens, followed by full-parameter continued pretraining; we further distill this model into a lightweight variant via knowledge distillation. To our knowledge, this is the first high-performance long-context encoder for Polish, accompanied by FinBench—a newly introduced benchmark comprising long financial documents. Evaluated across 25 tasks, including KLEJ and FinBench, our model outperforms existing Polish and multilingual baselines on average, demonstrating substantial gains on long-context tasks while preserving strong performance on short-text understanding.

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IoT and Older Adults: Towards Multimodal EMG and AI-Based Interaction with Smart Home

Jul 25, 2025

This study addresses the limited accessibility of standard interfaces (e.g., voice, touch) for older adults and people with disabilities in smart home environments. We propose a non-invasive, multimodal biosignal interaction paradigm integrating surface electromyography (EMG), electrooculography (EOG), and speech signals. A lightweight AI model enables real-time intent recognition, while participatory design iteratively refines human–machine collaboration logic, implemented in the Sagacity prototype system. Our key contribution is the first integration of low-cost EMG/EOG sensing with edge AI to deliver a contactless, low-cognitive-load control solution tailored to vulnerable users. Experimental evaluation in realistic domestic settings confirms feasibility and robustness, identifies critical technical bottlenecks, and elicits authentic user requirements. The work provides a reproducible design framework and empirical evidence for accessible intelligent interaction.

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Recent publications

Latest Papers

Long-Context Encoder Models for Polish Language Understanding

Mar 12, 2026

This work addresses the limitation of Polish BERT-style encoders in processing long documents due to their short context windows. We propose a two-stage training strategy: first extending positional embeddings to support a context length of 8,192 tokens, followed by full-parameter continued pretraining; we further distill this model into a lightweight variant via knowledge distillation. To our knowledge, this is the first high-performance long-context encoder for Polish, accompanied by FinBench—a newly introduced benchmark comprising long financial documents. Evaluated across 25 tasks, including KLEJ and FinBench, our model outperforms existing Polish and multilingual baselines on average, demonstrating substantial gains on long-context tasks while preserving strong performance on short-text understanding.

0 citationsRead paper

IoT and Older Adults: Towards Multimodal EMG and AI-Based Interaction with Smart Home

Jul 25, 2025

This study addresses the limited accessibility of standard interfaces (e.g., voice, touch) for older adults and people with disabilities in smart home environments. We propose a non-invasive, multimodal biosignal interaction paradigm integrating surface electromyography (EMG), electrooculography (EOG), and speech signals. A lightweight AI model enables real-time intent recognition, while participatory design iteratively refines human–machine collaboration logic, implemented in the Sagacity prototype system. Our key contribution is the first integration of low-cost EMG/EOG sensing with edge AI to deliver a contactless, low-cognitive-load control solution tailored to vulnerable users. Experimental evaluation in realistic domestic settings confirms feasibility and robustness, identifies critical technical bottlenecks, and elicits authentic user requirements. The work provides a reproducible design framework and empirical evidence for accessible intelligent interaction.

0 citationsRead paper