PAPER Demand \Cite{meir2021market
Research on paper demand within the scientific community focuses on optimizing the peer review process and improving paper accessibility. Current efforts involve developing AI-based tools to detect AI-generated text in reviews and papers, enhancing paper-reviewer matching algorithms by integrating semantic, topic, and citation factors, and creating systems that summarize and contextualize research papers for broader audiences. These advancements aim to improve the efficiency and integrity of scientific publishing and knowledge dissemination, ultimately benefiting both researchers and the wider public.
Papers
PaperWeaver: Enriching Topical Paper Alerts by Contextualizing Recommended Papers with User-collected Papers
Yoonjoo Lee, Hyeonsu B. Kang, Matt Latzke, Juho Kim, Jonathan Bragg, Joseph Chee Chang, Pao Siangliulue
AdAM: Adaptive Fault-Tolerant Approximate Multiplier for Edge DNN Accelerators
Mahdi Taheri, Natalia Cherezova, Samira Nazari, Ahsan Rafiq, Ali Azarpeyvand, Tara Ghasempouri, Masoud Daneshtalab, Jaan Raik, Maksim Jenihhin