Author

Yujin Jo

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#artificial intelligence Oct 2025

Memory-Free Continual Learning with Null Space Adaptation for Zero-Shot Vision-Language Models

Experiments show that the NuSA-CL framework not only effectively preserves zero-shot transfer capabilities but also achieves highly competitive performance on continual learning benchmarks, positioning NuSA-CL as a practical and scalable solution for continually evolving zero-shot VLMs in real-world applications.

Yujin Jo, Taesup Kim · arXiv.org · 2 citations

Preprint Aug 2026

K-EXAONE 2.0 Technical Report

K-EXAONE 2.0 improves over K-EXAONE and remains competitive with open-weight models, showing its largest gains in agentic coding and long-context understanding and its clearest strengths in long-context retrieval and safety.

Eunbi Choi, Kibong Choi, Sehyun Chun et al. · 0 citations