2025-08-08
This paper proposes a novel method called Query-Guided Activation Refilling (ACRE) aimed at improving efficiency and performance in processing long contexts within Large Language Models (LLMs). By combining a two-layer KV cache and query-guided refilling, the approach enables processing of contexts beyond the native context window, significantly enhancing the practicality of long-context information retrieval.
2025-08-08
This paper proposes a novel method, "Desiview," for automatically identifying desirable review comments (DRC) that lead to code changes in code reviews. By constructing a high-quality dataset using Desiview and fine-tuning and aligning the LLaMA model, we demonstrate a significant improvement in DRC generation capability. This approach is expected to greatly contribute to code review automation and software development support.
2025-08-08
This paper proposes a hybrid Top-k recommendation system that combines traditional recommendation methods with large language models (LLMs). Users are categorized as "active users" and "weak users," with LLMs employed to improve recommendation accuracy and fairness for the latter group. At the same time, the model controls LLM computational costs to ensure practical feasibility.