3 papers
cs.SE2026
An Empirical Study of Downstream Adaptation for Agent Skills
Xinjian Wu, Jingzhi Gong, Gunel Jahangirova +2
As Large Language Model (LLM) agents become integral to modern software systems, ``skills'' have emerged as a novel unit of software reuse, enabling developers to package workflows…
cs.SE2026
How Does Chunking Affect Retrieval-Augmented Code Completion? A Controlled Empirical Study
Xinjian Wu, Jingzhi Gong, Gunel Jahangirova +1
Retrieval-augmented generation (RAG) pipelines for code completion rely on chunking to segment source files into retrievable units, yet chunking strategies are typically adopted wi…
cs.CL2025
D2O: Dynamic Discriminative Operations for Efficient Long-Context Inference of Large Language Models
Zhongwei Wan, Xinjian Wu, Yu Zhang +8
Generative inference in Large Language Models (LLMs) is impeded by the growing memory demands of Key-Value (KV) cache, especially for longer sequences. Traditional KV cache evictio…