4 papers
Task-Specific Efficiency Analysis: When Small Language Models Outperform Large Language Models
Jinghan Cao, Yu Ma, Xinjin Li +2
Large Language Models achieve remarkable performance but incur substantial computational costs unsuitable for resource-constrained deployments. This paper presents the first compre…
Bridging the Editing Gap in LLMs: FineEdit for Precise and Targeted Text Modifications
Yiming Zeng, Wanhao Yu, Zexin Li +5
Large Language Models (LLMs) have significantly advanced natural language processing, demonstrating strong capabilities in tasks such as text generation, summarization, and reasoni…
TreeDiff: AST-Guided Code Generation with Diffusion LLMs
Yiming Zeng, Jinghan Cao, Zexin Li +7
Code generation is increasingly critical for real-world applications. Still, diffusion-based large language models continue to struggle with this demand. Unlike free-form text, cod…
HyperEdit: Unlocking Instruction-based Text Editing in LLMs via Hypernetworks
Yiming Zeng, Jinghan Cao, Zexin Li +7
Instruction-based text editing is increasingly critical for real-world applications such as code editors (e.g., Cursor), but Large Language Models (LLMs) continue to struggle with…