Amazon's Controversial Memo Reignites Debate on the Future of Remote Work
The battle between employers and employees over remote work arrangements is intensifying, with Amazon's latest memo signaling a potential shift in the balance of power.
실제 의견과 공개 의견 사이의 관계를 고려한 두 층 네트워크에서의 중심성 측정 및 의견 동학
두 층 네트워크에서의 중심성 측정이 의견 동학의 주요 지표인 합의 시간과 승리율에 미치는 영향을 분석하였다.
Centrality Measures and Opinion Dynamics in Two-Layer Networks with Replica Nodes
Network structure has a significant impact on key performance indicators of opinion dynamics processes realized on the network. Centrality measures, such as betweenness, closeness, and game-theoretic centralities, can capture important characteristics of the network structure and influence opinion dynamics.
Mask-Encoded Sparsification: A Communication-Efficient Approach for Split Learning to Mitigate Biased Gradients
Mask-encoded sparsification (MS) is a novel framework that significantly reduces communication overhead in Split Learning (SL) scenarios without compromising model convergence or generalization capabilities.
Leveraging Retrieved Documents to Enhance Conversational Query Reformulation for Improved Search Performance
Conversational Query Reformulation (CQR) can be improved by leveraging key information extracted from initially retrieved documents to generate more retriever-friendly queries.
트위터 프로필 자기소개에 나타난 자기표현 차원 측정과 허위정보 공유와의 연관성
트위터 사용자들의 프로필 자기소개에 나타난 자기표현 차원을 측정하고, 이것이 허위정보 공유와 어떤 연관성이 있는지 분석하였다.
Analyzing Self-Presentation in Twitter Bios and its Associations with Misinformation Sharing
Self-presentation in Twitter bios, as captured through novel embedding models, is associated with increased sharing of low-quality news, particularly for older, right-leaning, and more religious users.
Factors Shaping the Structure of Online Discussions on Reddit: Analyzing the Interplay of Local and Global Features
Both local post-level features (e.g., content, sentiment) and global community-level features (e.g., subreddit topic, age, popularity) significantly shape the structure of online discussions on Reddit, with local features having a greater overall impact.
Improving Binaural Signal Matching for Wearable Microphone Arrays by Incorporating Signal Information
Incorporating signal information, particularly on source direction, can significantly improve the performance of binaural signal matching (BSM) methods for wearable microphone arrays, especially in high direct-to-reverberant ratio scenarios.
인공지능 기반 전지구 기상 모델을 활용한 기후 귀인: 2017년 오로빌 댐 극한 대기 강수 사례 분석
인공지능 기반 데이터 모델(Graphcast, Pangu Weather, Fourcastnet, SFNO)은 추론 시간이 짧아 분석 대상 사례 수를 늘릴 수 있고 대중의 관심이 높은 시기에 실시간 귀인 분석을 제공할 수 있어, 극한 기상 사례에 대한 기후 귀인 연구에 활용될 수 있다.
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