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Open nowPosted 44 days ago

信息压缩与知识表示研究实习生

sii-czxy/campus170 open roles

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Your applicationOpen now信息压缩与知识表示研究实习生sii-czxy/campus

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This job: posted 44 days ago

The posting

1. 调研与复现相关方法：阅读并整理语义压缩、知识表示、长上下文建模和智能体记忆等方向的前沿论文，复现代表性方法，建立适用于项目数据的基线实验。 2. 构建信息压缩评测任务：基于长文档、多源事件信号和历史判断记录，整理测试样本，设计评测标准，关注关键事实、证据来源、时间关系及不确定性信息的保留能力。 3. 研究面向持续信息流的压缩方法：探索语义去重、结构化表示、分层记忆和可学习压缩表示等方法，在有限上下文和存储资源下保留对后续检索、推理和预测有价值的信息。 4. 探索增量信息更新机制：分析新信息与历史记录之间的新增、重复、修正和冲突关系，研究信息合并、替换和保留策略，并维护关键判断及其依据的演变过程。 5. 开展方法评估与系统集成：比较不同压缩方法在信息保留率、事实准确性、证据可追溯性、下游任务效果及计算成本方面的表现，将有效方法接入智能体记忆与检索模块。

1. 招募对象：本科生、硕士研究生。 2. 计算机、人工智能、数学、统计、信息与通信工程等相关专业背景优先。 3. 具备机器学习或深度学习基础；了解信息论、自然语言处理、表示学习、信息检索等方向之一者优先。 4. 具备 Python 编程能力，能够完成文本处理、模型调用或基础训练实验，并对实验结果进行定量分析和案例验证。 5. 有文本摘要、检索增强生成（RAG）、长上下文建模、知识图谱、表示学习、智能体记忆或数据压缩相关项目经验者优先。 6. 具备论文阅读与复现实验能力，能够开展对照实验并分析方法优劣。 7. 能够阅读英文论文，对“如何保留关键信息、如何用更高效的表示支持复杂任务”具有研究兴趣。 8. 具备严谨的实验习惯，关注信息遗漏、事实失真和证据丢失等问题。 9. 不要求已有正式科研经历或论文发表，更关注学习能力、实验能力和持续研究意愿。 10. 实习安排：线下科研实习；周期3–6个月；每周投入30小时以上。

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