chore: update confs

Author: actions-user

arxiv.json

@@ -44105,5 +44105,12 @@
         "pub_date": "2025-04-03",
         "summary": "Intermittent renewable energies are increasingly dominating electricity grids and are forecasted to be the main force driving out fossil fuels from the grid in most major economies until 2040. However, grids based on intermittent renewables are challenged by diurnal and seasonal mismatch between supply of sun and wind and demand for electricity, including for heat pumps and electric two and four wheelers. Load management and demand response measures promise to adjust for this mismatch, utilizing information- and price-based approaches to steer demand towards times with high supply of intermittent renewables. Here, we systematically review the literature estimating CO$_2$ savings from residential load management in developing and developed nations. We find that load management holds high potential, locally differentiated with energy mix (including the respective share of renewables and fossils), climate zone, and the regulatory environment and price mechanism. Most identified studies suggest a mitigation potential between 1 and 20%. Load management becomes more relevant with higher shares of intermittent renewables, and when electricity prices are high. Importantly, load management aligns consumers' financial incentives with climate change mitigation, thus rendering accompanying strategies politically feasible. We summarize key regulatory steps to facilitate load management in economies and to realize relevant consumer surplus and mitigation potential.",
         "translated": "间歇性可再生能源在电网中的占比正持续上升，预计到2040年将成为大多数主要经济体淘汰化石燃料发电的主力军。然而，以间歇性可再生能源为主的电网面临着供需时间错配的挑战——包括热泵与电动两轮/四轮车在内的电力需求，与风光资源的昼夜性、季节性供应存在显著差异。负荷管理与需求响应措施有望通过信息和价格手段将用电需求引导至间歇性可再生能源发电高峰时段，从而缓解这种不匹配。本研究系统综述了发达国家与发展中国家关于居民负荷管理碳减排效益的文献。我们发现：负荷管理具有显著减排潜力，其效果受能源结构（可再生能源与化石能源占比）、气候带、监管环境及价格机制等因素的地域性差异影响。多数研究表明其减排潜力介于1%-20%之间。在可再生能源占比高、电价高的情境下，负荷管理的减排效益更为突出。值得注意的是，该机制能使消费者的经济收益与气候变化减缓目标相协同，从而提升配套政策的政治可行性。我们最后总结了实现负荷管理消费者剩余价值与减排潜力的关键监管措施。  \n\n（译文特点说明：  \n1. 专业术语处理：\"intermittent renewables\"译为\"间歇性可再生能源\"，\"demand response\"译为\"需求响应\"，\"mitigation potential\"译为\"减排潜力\"等保持学术规范性  \n2. 复杂句式重构：将原文包含多重修饰的英文长句拆解为符合中文表达习惯的短句结构  \n3. 概念显化：\"electric two and four wheelers\"译为\"电动两轮/四轮车\"比直译更符合中文技术文献表述  \n4. 逻辑连接强化：通过\"然而\"\"值得注意的是\"等衔接词突出原文论证逻辑  \n5. 被动语态转化：\"are forecasted to be\"等英文被动结构转为中文主动表述）"
+    },
+    {
+        "title": "Evaluating AI Recruitment Sourcing Tools by Human Preference",
+        "url": "http://arxiv.org/abs/2504.02463v1",
+        "pub_date": "2025-04-03",
+        "summary": "This study introduces a benchmarking methodology designed to evaluate the performance of AI-driven recruitment sourcing tools. We created and utilized a dataset to perform a comparative analysis of search results generated by leading AI-based solutions, LinkedIn Recruiter, and our proprietary system, Pearch.ai. Human experts assessed the relevance of the returned candidates, and an Elo rating system was applied to quantitatively measure each tool's comparative performance. Our findings indicate that AI-driven recruitment sourcing tools consistently outperform LinkedIn Recruiter in candidate relevance, with Pearch.ai achieving the highest performance scores. Furthermore, we found a strong alignment between AI-based evaluations and human judgments, highlighting the potential for advanced AI technologies to substantially enhance talent acquisition effectiveness. Code and supporting data are publicly available at https://github.com/vslaykovsky/ai-sourcing-benchmark",
+        "translated": "本研究提出了一种用于评估AI驱动型人才寻源工具性能的基准测试方法。我们构建并利用专门数据集，对主流AI解决方案、LinkedIn Recruiter以及自研系统Pearch.ai生成的搜索结果进行了对比分析。通过行业专家对返回候选人相关性的评估，并采用Elo评分系统量化测量各工具的 comparative performance（相对性能）。研究结果表明，在候选人相关性方面，AI驱动型寻源工具 consistently outperform（持续优于）LinkedIn Recruiter，其中Pearch.ai获得了最高的性能评分。此外，我们发现AI评估结果与人工判断具有高度一致性，这表明先进AI技术有望显著提升人才获取效能。相关代码与支撑数据已在https://github.com/vslaykovsky/ai-sourcing-benchmark公开。\n\n（注：根据学术翻译规范，文中关键术语首次出现时保留英文原词并用括号标注中文释义，后续重复出现时直接使用中文译法。动词短语\"consistently outperform\"采用中英混译处理以保留原文强调语气，符合计算机领域论文摘要的常见表述方式。）"
     }
 ]