helpResearch question人机协同标注与示例选择如何设计一款结合专家知识和自动算法的图像标注工具,以减少对大量标注数据的需求并提升标注效率?IUI '25HEPHA: A Mixed-Initiative Image Labeling Tool for Specialized Domains
helpResearch question人机协同标注与示例选择在数据稀缺的场景中,如何通过逻辑规则生成高质量、可解释的图像标注?IUI '25HEPHA: A Mixed-Initiative Image Labeling Tool for Specialized Domains
helpResearch question人机协同标注与示例选择如何通过交互式界面优化图像标注规则编辑过程并提升用户体验?IUI '25HEPHA: A Mixed-Initiative Image Labeling Tool for Specialized Domains
lightbulbPractical problem人机协同标注与示例选择领域专家标注图像数据成本高、效率低且规则难以解释。IUI '25HEPHA: A Mixed-Initiative Image Labeling Tool for Specialized Domains
helpResearch question人机协同标注与示例选择如何应对文本到SQL模型在新领域数据库模式下性能显著下降的问题?IUI '25Text-to-SQL Domain Adaptation via Human-LLM Collaborative Data Annotation
helpResearch question人机协同标注与示例选择是否可以通过人机协作的动态注释工具提高文本到SQL数据标注的效率和质量?IUI '25Text-to-SQL Domain Adaptation via Human-LLM Collaborative Data Annotation
helpResearch question人机协同标注与示例选择如何结合规则生成方法和语言大模型(LLMs)生成多样性和高质量的SQL及自然语言查询数据?IUI '25Text-to-SQL Domain Adaptation via Human-LLM Collaborative Data Annotation
lightbulbPractical problem人机协同标注与示例选择文本到SQL模型在新领域使用中因数据不足表现不佳。IUI '25Text-to-SQL Domain Adaptation via Human-LLM Collaborative Data Annotation
helpResearch question人机协同标注与示例选择如何通过结合认知理论(变异理论和结构匹配理论)生成对比数据以支持主观或模糊任务的标注?CHI '25Supporting Co-Adaptive Machine Teaching through Human Concept Learning and Cognitive Theories
helpResearch question人机协同标注与示例选择如何设计交互界面以帮助用户在标注过程中快速感知数据关键差异?CHI '25Supporting Co-Adaptive Machine Teaching through Human Concept Learning and Cognitive Theories
helpResearch question人机协同标注与示例选择认知支持工具如何影响人机协同标注效率和模型性能?CHI '25Supporting Co-Adaptive Machine Teaching through Human Concept Learning and Cognitive Theories
lightbulbPractical problem人机协同标注与示例选择用户在复杂或主观任务的标注中难以理解模型状态和数据边界。CHI '25Supporting Co-Adaptive Machine Teaching through Human Concept Learning and Cognitive Theories
helpResearch question人机协同标注与示例选择多模态语言模型(LLMs)能否通过视觉和XML文件解析UI元素,从而无需后端访问高效操作智能手机应用?CHI '25AppAgent: Multimodal Agents as Smartphone Users
helpResearch question人机协同标注与示例选择如何通过自探索和人类演示学习,使智能体快速适应新的应用程序操作?CHI '25AppAgent: Multimodal Agents as Smartphone Users
helpResearch question人机协同标注与示例选择结合上下文学习策略,多模态代理如何在减少标注数据依赖的情况下提高任务成功率?CHI '25AppAgent: Multimodal Agents as Smartphone Users
lightbulbPractical problem人机协同标注与示例选择当前智能助手缺乏通用能力、安全性和隐私保护,难以高效操作各种手机应用。CHI '25AppAgent: Multimodal Agents as Smartphone Users
helpResearch question人机协同标注与示例选择在没有标准数据的情况下,用户如何设计提示以优化LLMs(大型语言模型)的数据标注性能?CHI '25Prompting in the Dark: Assessing Human Performance in Prompt Engineering for Data Labeling When Gold Labels Are Absent
helpResearch question人机协同标注与示例选择面向动态数据标注,哪些设计策略可以提高用户的提示调整能力和标注质量?CHI '25Prompting in the Dark: Assessing Human Performance in Prompt Engineering for Data Labeling When Gold Labels Are Absent
helpResearch question人机协同标注与示例选择基于“无标准数据”的场景,提示设计工具需要具备哪些核心功能?CHI '25Prompting in the Dark: Assessing Human Performance in Prompt Engineering for Data Labeling When Gold Labels Are Absent
lightbulbPractical problem人机协同标注与示例选择普通用户在缺乏标准数据时难以优化提示以进行高质量数据标注。CHI '25Prompting in the Dark: Assessing Human Performance in Prompt Engineering for Data Labeling When Gold Labels Are Absent
helpResearch question人机协同标注与示例选择如何通过增强特征信息,帮助标签员更好地理解和标注机器人轨迹偏好?IUI '24FARPLS: A Feature-Augmented Robot Trajectory Preference Labeling System to Assist Human Labelers’ Preference Elicitation
helpResearch question人机协同标注与示例选择动态调整标注顺序如何提升标注一致性和效率?IUI '24FARPLS: A Feature-Augmented Robot Trajectory Preference Labeling System to Assist Human Labelers’ Preference Elicitation
helpResearch question人机协同标注与示例选择提供实时反馈是否能够有效减少疲劳并优化用户体验?IUI '24FARPLS: A Feature-Augmented Robot Trajectory Preference Labeling System to Assist Human Labelers’ Preference Elicitation
lightbulbPractical problem人机协同标注与示例选择人类在标注机器人轨迹偏好时常感到认知负担重,标注一致性差。IUI '24FARPLS: A Feature-Augmented Robot Trajectory Preference Labeling System to Assist Human Labelers’ Preference Elicitation
helpResearch question人机协同标注与示例选择AI辅助灾害管理中的数据标注接口设计如何减少新手和专家的标注差距?IUI '24Closing the Knowledge Gap in Designing Data Annotation Interfaces for AI-powered Disaster Management Analytic Systems
helpResearch question人机协同标注与示例选择哪些因素导致新手在灾害管理数据标注中产生知识差距?IUI '24Closing the Knowledge Gap in Designing Data Annotation Interfaces for AI-powered Disaster Management Analytic Systems
helpResearch question人机协同标注与示例选择Context接口中提示和隐藏上下文信息如何改善新手的数据标注表现?IUI '24Closing the Knowledge Gap in Designing Data Annotation Interfaces for AI-powered Disaster Management Analytic Systems
lightbulbPractical problem人机协同标注与示例选择灾害管理中,新手标注的数据常与专家存在较大差异,影响AI模型质量。IUI '24Closing the Knowledge Gap in Designing Data Annotation Interfaces for AI-powered Disaster Management Analytic Systems
helpResearch question人机协同标注与示例选择如何设计一个初学者友好的平台,使其能够利用人机协作高效进行定性数据分析?IUI '24SenseMate: An Accessible and Beginner-Friendly Human-AI Platform for Qualitative Data Analysis
helpResearch question人机协同标注与示例选择解释性人工智能模型如何帮助初学者在定性编码中提升一致性和质量?IUI '24SenseMate: An Accessible and Beginner-Friendly Human-AI Platform for Qualitative Data Analysis
helpResearch question人机协同标注与示例选择用户反馈机制如何影响人机协同定性数据分析平台的性能和用户体验?IUI '24SenseMate: An Accessible and Beginner-Friendly Human-AI Platform for Qualitative Data Analysis
lightbulbPractical problem人机协同标注与示例选择社区组织缺乏易用工具来高效分析调查和访谈数据。IUI '24SenseMate: An Accessible and Beginner-Friendly Human-AI Platform for Qualitative Data Analysis
helpResearch question人机协同标注与示例选择如何通过偏好学习(RankNet)在低预算条件下预测游戏玩家的唤醒水平?UbiComp '24Progress of PREFAB: Preference-based Self-Annotation on a Low-Budget
helpResearch question人机协同标注与示例选择如何高效识别情绪唤醒水平中的峰值区域以减少自我标注负担?UbiComp '24Progress of PREFAB: Preference-based Self-Annotation on a Low-Budget
helpResearch question人机协同标注与示例选择偏好学习与传统回归方法相比,在情绪变化的时序预测上有哪些优势?UbiComp '24Progress of PREFAB: Preference-based Self-Annotation on a Low-Budget
lightbulbPractical problem人机协同标注与示例选择玩家在实时游戏中难以快速且准确地完成情绪自我标注。UbiComp '24Progress of PREFAB: Preference-based Self-Annotation on a Low-Budget
helpResearch question人机协同标注与示例选择在社区环境(如Wikipedia)中,如何实现由社区主导的数据标注以支持AI评估?CHI '24Wikibench: Community-Driven Data Curation for AI Evaluation on Wikipedia
helpResearch question人机协同标注与示例选择社区驱动的数据集策展能否提高标签一致性并减少数据偏差?CHI '24Wikibench: Community-Driven Data Curation for AI Evaluation on Wikipedia
helpResearch question人机协同标注与示例选择什么样的工具和机制可以支持社区成员共同定义标签标准、解决标注争议并提升数据透明度?CHI '24Wikibench: Community-Driven Data Curation for AI Evaluation on Wikipedia
lightbulbPractical problem人机协同标注与示例选择AI评估数据集未反映社区价值,产生偏差影响用户体验。CHI '24Wikibench: Community-Driven Data Curation for AI Evaluation on Wikipedia
helpResearch question人机协同标注与示例选择如何通过引入验证模型来提高LLM生成标签的准确性与效率?CHI '24Human-LLM Collaborative Annotation Through Effective Verification of LLM Labels
helpResearch question人机协同标注与示例选择在协作注释中,LLM生成的解释能否有效帮助人类理解和校正标签?CHI '24Human-LLM Collaborative Annotation Through Effective Verification of LLM Labels
helpResearch question人机协同标注与示例选择多步协作框架是否能够在减少人工注释成本的同时,保证数据注释的质量?CHI '24Human-LLM Collaborative Annotation Through Effective Verification of LLM Labels
lightbulbPractical problem人机协同标注与示例选择数据标注依赖人工,耗时且成本高,LLM标注错误和偏差难以完全避免。CHI '24Human-LLM Collaborative Annotation Through Effective Verification of LLM Labels
helpResearch question人机协同标注与示例选择如何实现基于自动交互的用户界面语义数据的持续学习?UIST '23Never-ending Learning of User Interfaces
helpResearch question人机协同标注与示例选择自动数据爬取系统如何解决传统数据集动态更新不匹配的问题?UIST '23Never-ending Learning of User Interfaces
helpResearch question人机协同标注与示例选择如何保证UI语义模型在动态变化中的准确性和适配性?UIST '23Never-ending Learning of User Interfaces
lightbulbPractical problem人机协同标注与示例选择UI语义标注昂贵且易出错,难以满足动态应用需求。UIST '23Never-ending Learning of User Interfaces
helpResearch question人机协同标注与示例选择人机协作如何提升音视频数据标注的效率和质量?UIST '23PEANUT: A Human-AI Collaborative Tool for Annotating Audio-Visual Data
helpResearch question人机协同标注与示例选择跨模态(如音频和视频)标注工具应如何设计以兼顾用户效率与模型性能?UIST '23PEANUT: A Human-AI Collaborative Tool for Annotating Audio-Visual Data