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Yihang Lou

ACL 2026×2NeurIPS 2026×2推理多模态强化学习与后训练智能体与工具评测与基准
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合作网络9
0 一作 · 4 篇 · ACL 2026 / NeurIPS 2026

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2026 顶会论文

4
作者位次 #4/7ACL 2026Poster· Natural Language Processing

Learning to Edit Knowledge via Instruction-based Chain-of-Thought Prompting

Jinhu Fu · Yan Bai · Longzhu He · Yihang Lou · Yanxiao Zhao · Li Sun · Sen Su

摘要

Large language models (LLMs) can effectively handle outdated information through knowledge editing. However, current approaches face two key limitations: (I) Poor generalization: Most approaches rigidly inject new knowledge without ensuring that the model can use it effectively to solve practical...

检索与知识强化学习与后训练推理OpenReview 项目页
作者位次 #8/10ACL 2026Findings· Findings of ACL

F ront C oder: Scaling Visual Fidelity in Front-End Code Generation

Jun Feng · Jian Yang · Wei Zhang · Jing Wang · Keyi Chen · Xiaokun Yang · Weicheng Gu · Yihang Lou · Yan Bai · Xianglong Liu

摘要

Large language models (LLMs) for code generation have achieved remarkable progress in synthesizing functional code from natural language instructions. However, a critical challenge persists in generating visually accurate and structurally sound front-end code that faithfully renders user-intended...

数据与预训练多模态强化学习与后训练OpenReview 项目页

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