paper-with-me

홈 › Papers

CS-Insights: A System for Analyzing Computer Science Research

2022-10-13 · Terry Ruas, Jan Philip Wahle, Lennart Küll, Saif M. Mohammad, Bela Gipp

This paper presents CS-Insights, an interactive web application to analyze computer science publications from DBLP through multiple perspectives. The dedicated interfaces allow its users to identify trends in research activity, productivity, accessibility, author's productivity, venues' statistics, topics of interest, and the impact of computer science research on other fields. CS-Insightsis publicly available, and its modular architecture can be easily adapted to domains other than computer science.

📄 PDF Abstract BibTeX arXiv:2210.06878

Code (2)

jpwahle/cs-insights 공식 구현
gipplab/cs-insights-main

Similar Papers 제목 키워드 기반

Language Cognition and Language Computation -- Human and Machine Language Understanding

2023-01-12 · Shaonan Wang, Nai Ding, Nan Lin, Jiajun Zhang 외

Language understanding is a key scientific issue in the fields of cognitive and computer science. However, the two disciplines differ substantially in the specific research questions. Cognitive science focuses on analyzi…

Analyzing 16,193 LLM Papers for Fun and Profits

2025-04-11 · Zhiqiu Xia, Lang Zhu, Bingzhe Li, Feng Chen 외

Large Language Models (LLMs) are reshaping the landscape of computer science research, driving significant shifts in research priorities across diverse conferences and fields. This study provides a comprehensive analysis…

Analyzing the State of Computer Science Research with the DBLP Discovery Dataset

2022-12-01 · Lennart Küll

The number of scientific publications continues to rise exponentially, especially in Computer Science (CS). However, current solutions to analyze those publications restrict access behind a paywall, offer no features for…

Articles

In Transformer We Trust? A Perspective on Transformer Architecture Failure Modes

2026-02-15 · Trishit Mondal, Ameya D. Jagtap arxiv

Transformer architectures have revolutionized machine learning across a wide range of domains, from natural language processing to scientific computing. However, their growing deployment in high-stakes applications, such…

Automated Theorem ProvingDrug Discovery

"Which LLM should I use?": Evaluating LLMs for tasks performed by Undergraduate Computer Science Students

2024-01-22 · Vibhor Agarwal, Madhav Krishan Garg, Sahiti Dharmavaram, Dhruv Kumar

This study evaluates the effectiveness of various large language models (LLMs) in performing tasks common among undergraduate computer science students. Although a number of research studies in the computing education co…

Code Generation