3 papers
cs.LG2025
Dynamic Bayesian Optimization Framework for Instruction Tuning in Partial Differential Equation Discovery
Junqi Qu, Yan Zhang, Shangqian Gao +1
Large Language Models (LLMs) show promise for equation discovery, yet their outputs are highly sensitive to prompt phrasing, a phenomenon we term instruction brittleness. Static pr…
cs.CL2025
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…
cs.CL2025
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…