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- [25.02.07] 2024 SW Talent Festival Grand Prize RISE Team (CSE '23): Interview with Team Leader Jung Gi-yong NEW
- [25.02.07] 2024 SW Talent Festival Grand Prize RISE Team (Department of Computer Science and Engineering '23): Interview with Team Leader Jung Gi-yong From left: Jeong Hee-seong, Jung Gi-yong, Lee Gyu-min, Lee Sang-yeop, Lee Sang-jun On December 5th and 6th, 2024, the 2024 SW Talent Festival was held over two days. The event was hosted by the Ministry of Science and ICT and organized by the Information and Communication Planning and Evaluation Institute and the SW-Centric University Council. Under the theme “An AI World Connected by Software,” the festival showcased, exhibited, and awarded the major achievements and outstanding outcomes from 58 SW-centric universities. At this festival, the RISE team—composed of five students from the Department of Computer Science and Engineering at Sungkyunkwan University—won the Grand Prize (Minister of Science and ICT Award) by enhancing chart recognition performance through the construction of a Korean chart learning dataset. Let’s meet team leader Jung Gi-yong from the RISE team. Q: What motivated you to participate in the 2024 SW Talent Festival? A: In our Department of Computer Science and Engineering, there is a one-year industry–academia collaboration project. Out of roughly 20 teams that complete this program, professors select the most promising teams through meetings and offer them the opportunity to represent the university in competitions. My professor suggested that we participate, and that’s how we entered the contest under the name “RISE” (which carries the meanings “to awaken” and “to soar”). Q: The RISE team won the Grand Prize with “ChartBrain.AI.” Could you please explain what ChartBrain.AI is? A: ChartBrain.AI is a compact AI model that converts chart images into table text. When we started the project in April, we noticed that although the GPT-4o model understood general photographs and images quite well, it struggled with chart images—it lacked the ability to accurately extract numerical data. To address this shortcoming, we set out to develop a small AI module that converts chart images into table text in a format that can be easily understood by a Large Language Model (LLM). Because cloud-based GPT-4o models carry the risk of data leakage, companies typically do not use them for processing internal reports and chart images that require high security; instead, they deploy their own in-house LLMs. Our ChartBrain.AI is well suited for such applications. It is compact and, among domestic models, has achieved state-of-the-art (SOTA) accuracy at its current stage. Q: Could you describe the process of creating ChartBrain.AI? A: We began by taking an English model called Deplot—released by Google Research—and performed initial training to enable it to understand Korean. Then, we built a dataset of 1.12 million chart-to-table data pairs and further trained the Deplot model with this data to complete our system. Out of these, 320,000 pairs were synthetic chart images that our team created to supplement the limited diversity of existing open-source chart image datasets and to enable the model to understand even more complex charts. Note: LLM (Large Language Model): A language model built from neural networks with an enormous number of parameters. Deplot Official Code Link: https://github.com/google-research/google-research/tree/master/deplot Q: I heard that at your university’s booth you explained your award-winning work while wearing the Cheonggeumbok—the traditional attire once worn by Sungkyunkwan students. What prompted you to wear it, and what are your impressions? A: We didn’t prepare the Cheonggeumbok ourselves. The faculty member in charge of the Software Convergence College advised us to wear it during our presentation at the booth. Honestly, I felt a bit self-conscious walking around in it at first, but later, after seeing photos where it was immediately obvious that we were Sungkyunkwan University students, I grew to appreciate it. It seems our professors had remarkable foresight. Q: As the team leader, what was most important to you during the project? A: In an industry–academia collaboration project, the topic is provided by a company and the final deliverable must be submitted to them. This setup creates a greater sense of responsibility compared to typical school assignments—I constantly thought, “If we don’t deliver a proper result, it’ll be a big problem.” No matter how hard we worked, if the final program’s performance was poor, all our efforts would have been in vain. We had to keep pushing until we achieved the desired outcome. Although the process wasn’t easy, I believe that our relentless effort ultimately led us to produce excellent results. Q: What were some of the challenges you faced in submitting your program for the festival, and how did you overcome them? A: Everything was completely new to us. During the summer break, we participated in an “Industry–Academia Summer Intensive Work Program.” We rented a classroom and, much like interns, worked there from 9 a.m. to 6 p.m. every weekday. We dedicated ourselves to technical development and reading research papers. Through this process, we experienced for the first time the full cycle of reading papers, experimenting with prior research, setting a research direction based on experimental results, forming hypotheses, training models, reviewing results, and identifying shortcomings. As the team leader, I felt an even greater sense of responsibility. I believe our advisor’s active guidance and the enthusiastic participation of all team members were key to our success. Without our advisor, it would have been extremely difficult to succeed with this project. Q: Were there any particularly memorable moments during the project’s progress? A: We did not win a major award from the start. Before receiving the Grand Prize, we participated in two other competitions but were eliminated in the first round in both cases. When we entered the first competition, everyone worked incredibly hard—even staying up until 1 a.m. (the dormitory curfew) to continue development. For the second competition, we made further improvements over our previous version. By the time we entered this final competition, our morale was quite low compared to the first attempt; however, it’s very gratifying that our work eventually shone through. Q: You entered several competitions with the same project. Did the performance of the program improve significantly over time? A: Yes, there were significant improvements in performance. As mentioned earlier, our benchmark was the GPT-4 Omni model. While both our ChartBrain.AI and GPT-4 Omni were evolving simultaneously, during the summer break we were confident in stating that our model was superior. However, by December GPT-4 Omni had caught up with us for a period. In the end, our model advanced considerably and regained a comparative edge. This improvement was crucial in helping us win the Grand Prize. Q: Since the RISE team is composed entirely of CSE students, were there any classes or extracurricular activities that helped with this project? A: For me, participating in academic societies was extremely helpful. I joined an AI society called “TNT” at our university and took part in paper study sessions. As a sophomore, I was able to read many research papers, review them, and ask questions in TNT, which taught me how to discern a good paper from a less effective one. Personally, the paper review sessions in TNT were the most beneficial. Q: What do you find most attractive about studying software? A: Ultimately, software is about programming to create documents. In any company, the work I do might involve editing just a word or two in countless documents—and yet, those small changes can have a tremendous impact. Since text can be easily reproduced, even a small idea that improves one part can have infinite influence. I think that is the greatest appeal of software and what continuously fuels my competitive spirit. Q: What are your future career goals or aspirations? A: In the short term, I plan to write an undergraduate paper based on our award-winning project around May or June next year. When I work on development, I feel that roughly 50% of the help comes from GPT and about 30% from other online sources, which sometimes leaves me with the impression that I haven’t fully grasped everything. Therefore, my long-term goal is to pursue graduate studies so that I can deepen my knowledge in mathematics, English, and algorithms. Q: Do you have any advice for students preparing for software-related competitions? A: I believe that students preparing for competitions are already incredibly diligent, so here’s a tip rather than just advice. As you work on your project, you might find yourself deeply attached to your ideas. Explaining these ideas to others, especially to the judges, can be very challenging. This was the aspect that hindered me the most during competitions. I spent a lot of time thinking about how to effectively communicate my beloved idea, particularly to the judges. In my experience, effective persuasion can be achieved within just one or two PowerPoint slides. Focus on that key part, and I hope you achieve excellent results. Convince everyone possible, and I wish you great success.
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- 작성일 2025-02-07
- 조회수 0
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- [25.01.23] IIS Lab, Four Papers Accepted at NAACL 2025 NEW
- [25.01.23] IIS Lab, Four Papers Accepted at NAACL 2025 The Information and Intelligent Systems Lab (IIS Lab), led by Professor Ji-Hyung Lee, has had four papers accepted at NAACL 2025 (2025 Annual Conference of the North American Chapter of the Association for Computational Linguistics), one of the top-tier international conferences in natural language processing (NLP). The papers will be presented in April 2025 in New Mexico, USA. 1. DeCAP: Context-Aware Prompt Generation for Debiased Zero-shot Question Answering in Large Language Models (NAACL 2025) Authors: Sooyoung Bae (PhD Student, Department of Artificial Intelligence) Yoonseok Choi (Assistant Professor, Department of Computer Education, Sungkyunkwan University / PhD Graduate, Department of Software) Large language models (LLMs) perform well in zero-shot question answering (QA) tasks. However, existing methods suffer from performance gaps between ambiguous and clear questions and low debiasing performance due to strong dependence on provided instructions or internal knowledge. To address these issues, we propose DeCAP (Context-Aware Prompt Generation), which: Utilizes a Question Ambiguity Detector to reduce performance gaps caused by ambiguous question types. Employs a Neutral Next Sentence Generator to decrease dependency on internal biased knowledge by providing neutral contextual information. Experiments on BBQ and UNQOVER datasets across six LLMs show that DeCAP achieves state-of-the-art debiasing performance in QA tasks, significantly enhancing the fairness and accuracy of LLMs across diverse QA environments. 2. SALAD: Improving Robustness and Generalization through Contrastive Learning with Structure-Aware and LLM-Driven Augmented Data (NAACL 2025) Authors: Sooyoung Bae (PhD Student, Department of Artificial Intelligence) Hyojun Kim (SKT / MS Graduate, Department of Artificial Intelligence) Yoonseok Choi (Assistant Professor, Department of Computer Education, Sungkyunkwan University / PhD Graduate, Department of Software) This paper introduces SALAD (Structure-Aware and LLM-driven Augmented Data), a novel approach aimed at enhancing robustness and generalization in NLP models using contrastive learning. SALAD generates: Structure-aware positive samples using a tagging-based method. Counterfactual negative samples with diverse sentence patterns generated by LLMs. This allows the model to learn structural relationships between key sentence components while minimizing reliance on spurious correlations. We evaluate SALAD on three tasks: Sentiment Classification Sexism Detection Natural Language Inference (NLI) Results show that SALAD improves robustness and performance across different settings, including out-of-distribution datasets and cross-domain scenarios. 3. CoRAC: Integrating Selective API Document Retrieval with Question Semantic Intent for Code Question Answering (NAACL 2025) Authors: Yoonseok Choi (Assistant Professor, Department of Computer Education, Sungkyunkwan University / PhD Graduate, Department of Software) Cheolwon Na (Integrated MS/PhD Program, Department of Artificial Intelligence) Automated Code Question Answering (AQA) aims to generate precise answers for code-related queries by analyzing code snippets. However, in real-world settings, users often provide only partial code, making it difficult to derive correct answers. To address this challenge, we propose CoRAC, a knowledge-driven framework that improves AQA by: Selective API document retrieval Question semantic intent clustering We evaluate CoRAC on three real-world benchmark datasets, demonstrating its effectiveness. Results show that CoRAC generates high-quality answers outperforming LLM-based solutions like ChatGPT. 4. Q-FAKER: Query-free Hard Black-box Attack via Controlled Generation (NAACL Findings 2025) Authors: Cheolwon Na (Integrated MS/PhD Program, Department of Artificial Intelligence) Yoonseok Choi (Assistant Professor, Department of Computer Education, Sungkyunkwan University / PhD Graduate, Department of Software) Adversarial attack methods for testing language model vulnerabilities often require multiple queries and access to target model information. Even black-box attacks typically depend on target model output data, making them impractical in hard black-box settings where access is restricted. Existing hard black-box attack methods still demand high query counts and expensive adversarial generator training costs. To solve this, we introduce Q-FAKER (Query-free Hard Black-box Attacker), an efficient adversarial example generation method that: Uses a surrogate model to generate adversarial sentences without accessing the target model. Leverages controlled generation techniques for adversarial text generation. We evaluate Q-FAKER across eight datasets, demonstrating its high transferability and effectiveness in hard black-box attack scenarios. Contact Information Professor Ji-Hyung Lee | john@skku.edu IIS Lab | https://iislab.skku.edu/
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- 작성일 2025-02-04
- 조회수 8
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- [25.01.21] Security Engineering Lab, Two Papers Accepted at CHI 2025 NEW
- [25.01.21] Security Engineering Lab, Two Papers Accepted at CHI 2025 The Security Engineering Lab (Advisor: Professor Hyungsik Kim) has had two papers accepted at CHI 2025 (ACM SIGCHI Conference on Human Factors in Computing Systems), one of the top-tier conferences in the field of Human-Computer Interaction (HCI). The papers will be presented in April 2025 in Yokohama, Japan. 1. Paper: "Understanding and Improving User Adoption and Security Awareness in Password Checkup Services" Authors: Sanghak Oh (PhD Student, Department of Electrical and Computer Engineering) Heewon Baek (MS Student, Department of Electrical and Computer Engineering) Taeyoung Kim (PhD Student, Department of Electrical and Computer Engineering) Woojin Jeon (PhD Student, Department of Electrical and Computer Engineering) Junho Heo (Samsung Research) Professor Ian Oakley (KAIST) Professor Hyungsik Kim (Sungkyunkwan University) Password Checkup Services (PCS) help users protect accounts by identifying compromised, reused, or weak passwords. However, these services have low adoption rates. This study conducted an online survey (N=238) to identify factors influencing PCS adoption and barriers to changing compromised passwords. Key findings include: Adoption factors: Perceived usefulness, ease of use, and self-efficacy were significant motivators. Barriers to password changes: Warning fatigue from frequent alerts, low awareness of password compromise risks, and reliance on other security measures discouraged users from taking action. To address these issues, the research team redesigned the PCS interface by: Clarifying warning messages related to compromised passwords. Automating the password change process, such as enabling users to update multiple reused passwords simultaneously or directly linking to password change pages. A task-based interview study (N=50) validated the effectiveness of the new design, showing a significant increase in password change rates in two scenarios: 40% and 74% change rates, compared to 16% and 60% in Google's existing PCS design. 2. Paper: "I Was Told to Install the Antivirus App, but I’m Not Sure I Need It: Understanding the Adoption, Discontinuation, and Non-Use of Smartphone Antivirus Software in South Korea" Authors: Seyoung Jin (MS Student, Department of Software) Heewon Baek (MS Student, Department of Software) Professor Euijin Lee (KAIST) Professor Hyungsik Kim (Sungkyunkwan University) This study investigates the limited effectiveness of smartphone antivirus software, despite recommendations from security firms, due to user misconceptions, regulatory requirements, and improper usage. Using a mixed-methods approach, including in-depth interviews (N=23) and a survey (N=250), the study examined the adoption status of smartphone antivirus software, particularly in South Korea, where it is often mandatory for banking and financial apps. Key findings: Many users confused antivirus software with general security tools and were unaware of its limited scope in addressing mobile malware threats. Factors influencing adoption: Perceived vulnerability, response efficacy, self-efficacy, social norms, and awareness. Factors leading to discontinuation or non-use: Concerns about system performance impact and skepticism about necessity. Additionally, the mandatory installation of antivirus software for financial apps in South Korea has contributed to user misconceptions, negative perceptions, and a false sense of security. This research highlights the need for better user education, clearer communication on mobile-specific security threats, and improved guidance to enhance effective antivirus software usage.
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- 작성일 2025-02-04
- 조회수 7
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- [24.12.26]Eunseok Ryu, Head of the Department of Immersive Media Engineering, Receives Minister of Science and ICT Award NEW
- Professor Eunseok Ryu, Head of the Department of Immersive Media Engineering, Receives Minister of Science and ICT Award Professor Eunseok Ryu, Head of the Department of Immersive Media Engineering, was awarded the Minister of Science and ICT Commendation on Wednesday, December 11, in recognition of his contributions to nurturing key talent in the metaverse field, international collaboration, and standardization efforts for next-generation technology development. Since the inauguration of the Department of Immersive Media Engineering in the second semester of 2023, Professor Ryu has been dedicated to researching and developing immersive media content technologies based on core technologies such as image processing, computer graphics, and artificial intelligence. The department has been actively selecting outstanding full-time graduate students with support from the Metaverse Convergence Graduate School Program, funded by the Ministry of Science and ICT. Additionally, the Department of Immersive Media Engineering operates an ICT and content convergence curriculum. It provides: Internship opportunities for all students in the department Overseas research institute placements for 25% of students Through these initiatives, the department is committed to fostering future global leaders in immersive media technology.
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- 작성일 2025-02-04
- 조회수 7
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- [24.12.23] CSI Lab (Prof. Hongwook Woo), Paper Accepted at AAAI 2025 NEW
- [Prof. Hongwook Woo] CSI Lab , Paper Accepted at AAAI 2025 The CSI Lab (Advisor: Professor Hongwook Woo) has had its paper accepted at AAAI 2025 (The 39th Annual AAAI Conference on Artificial Intelligence), one of the prestigious conferences in the field of artificial intelligence. The paper is scheduled to be presented in February 2025 in Philadelphia, USA. Paper Details The paper, “In-Context Policy Adaptation Via Cross-Domain Skill Diffusion,” was authored by Minjong Yoo (Integrated MS/PhD Program, Department of Software) as the first author, with Wookyung Kim (Integrated MS/PhD Program, Department of Software) as a co-author. This research proposes an In-Context Policy Adaptation (ICPAD) framework for long-horizon, multi-task environments across various domains and introduces diffusion-based skill learning techniques in cross-domain settings. ICPAD is designed to rapidly adapt reinforcement learning (RL) policies to diverse target domains using only limited target domain data—without requiring model updates. To achieve this, ICPAD: Learns domain-invariant prototype skills and domain-grounded skill adapters to maintain consistency across domains while adapting policies to new target domains through cross-domain skill diffusion. Optimizes diffusion-based skill translation by utilizing limited target domain data as prompts, enhancing policy adjustment via dynamic domain prompting. Experimental Results Experiments demonstrated that ICPAD outperforms state-of-the-art (SOTA) methods in adapting to dynamic environmental changes and various domain settings in: MetaWorld (robotic manipulation environment) CARLA (autonomous driving simulator) CSI Lab Research and Funding The CSI Lab focuses on machine learning, reinforcement learning, and self-supervised learning for optimizing networks, cloud systems, robotics, and autonomous drone navigation. This AAAI 2025 research is supported by: Core AI Technology Project for Human-Centered AI (IITP) National Research Foundation of Korea (NRF) Individual Basic Research Program Graduate School of AI ICT Elite Talent Development Program BK21 FOUR Program (BK21) Institute for Information & Communications Technology Planning & Evaluation (IITP) Samsung Electronics Contact Information Professor Hongwook Woo | hwoo@skku.edu CSI Lab | https://sites.google.com/view/csi-agent-group
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- 작성일 2025-02-04
- 조회수 6
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- [24.12.13] CSI Lab(Prof. Hongwook Woo), Excellence & Encouragement Awards at 2024 SKKU Graduate Student Paper Awards NEW
- [Prof. Hongwook Woo] CSI Lab, Excellence & Encouragement Awards at 2024 SKKU Graduate Student Paper Awards ■ 2024 Science and Engineering Field 1. Excellence Award Category: ICT Title: LLM-based Skill Diffusion for Zero-shot Policy Adaptation Recipient: Wookyung Kim (Department of Software) 2. Encouragement Award Category: ICT Title: Exploratory Retrieval-Augmented Planning for Continual Embodied Instruction Following Recipient: Minjong Yoo (Department of Software)
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- 작성일 2025-02-04
- 조회수 10
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- [24.12.02] LearnData Lab, Research on Graph Neural Networks Accepted at WSDM 2025 NEW
- LearnData Lab's Research on Graph Neural Networks Accepted at WSDM 2025 (Master's Graduate: Jongwon Park, PhD Candidate: Heesoo Jeong) A research paper from LearnData Lab (Advisor: Professor Hogun Park) has been accepted at The 18th ACM International Conference on Web Search and Data Mining (WSDM 2025), one of the top-tier conferences in the field of artificial intelligence. Paper Details The paper, “CIMAGE: Exploiting the Conditional Independence in Masked Graph Auto-encoders”, was published with Jongwon Park (Master’s Graduate, AI Department) as the first author, and Heesoo Jeong (PhD Candidate, Software Department) as the co-first author. Research Highlights Professor Hogun Park's research team at Sungkyunkwan University has achieved significant advancements in Graph Neural Network (GNN) learning based on self-supervised learning. This study introduces a novel model called CIMAGE (Conditional Independence Aware Masked Graph Auto-Encoder), which overcomes the limitations of conventional random masking techniques and significantly enhances the expressive power of GNNs. The CIMAGE model leverages conditional independence to design a more effective masking strategy, significantly improving both efficiency and accuracy in graph representation learning. A key aspect of this research is the use of high-confidence pseudo-labels to generate two independent contexts, enabling a novel pretext task that enhances the masking and reconstruction processes. The effectiveness of CIMAGE has been demonstrated across various graph benchmark datasets, achieving outstanding performance in downstream tasks such as node classification and link prediction. This breakthrough establishes a new standard in graph representation learning. Significance and Future Applications This research represents an important milestone in Sungkyunkwan University's commitment to innovative and pioneering research. The findings have high potential for application in graph neural networks and self-supervised learning. LearnData Lab focuses on developing cutting-edge machine learning and data mining technologies across various modalities, including graphs, natural language, sensor data, and images. The lab is also actively involved in explainable AI research. The WSDM 2025 paper was supported by funding from the Graduate School of AI, the Institute for Information & Communications Technology Planning & Evaluation (IITP), and the Korea Creative Content Agency (KOCCA). Contact Information Professor Hogun Park | hogunpark@skku.edu LearnData Lab | https://learndatalab.github.io
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- 작성일 2025-02-04
- 조회수 9
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- [24.11.22] secLab(Prof. Hyoungshick Kim), Wins Top Prize in Financial Security Institute
- [Prof. Hyoungshick Kim] secLab, Wins Top Prize in Financial Security Institute ▲ (From left) Researcher Sang-Yoon Seok, President Chul-Woong Kim of the Financial Security Agency, Graduate Student Hyunmin Choi, and Student Jihoon Kim Jihoon Kim and Hyunmin Choi, members of the Security Engineering Lab (supervised by Professor Hyungshick Kim) in the Department of Electrical, Electronic, and Computer Engineering, collaborated with Sang-Yoon Seok, a researcher at Naver Cloud, to win the top prize at the 8th Financial Security Institute’s Paper Contest. The award ceremony was held on Thursday, November 7, at the Conrad Hotel in Yeouido, Seoul. Hyunmin Choi is currently conducting research on privacy protection at Naver Cloud. The annual paper competition, hosted by the Financial Security Institute, invites submissions on topics such as changes in the financial environment, new technologies, and improvements to laws and regulations. Eight outstanding papers are selected each year, and winners receive preferential benefits when applying to the Financial Security Institute. Hyunmin Choi, the corresponding author and a doctoral candidate in the Department of Computer Science and Engineering, stated, “With the mandatory use of financial MyData APIs, the importance of data privacy technology is increasing. Our paper focused on enhancing security through homomorphic encryption and enabling data combination technologies.” Jihoon Kim, the first author and an undergraduate student in the Department of Mathematics, shared, “This research was a valuable learning experience, and I hope to continue contributing to advancements in security technology.” Professor Hyungshick Kim added, “This project provided students with a meaningful opportunity to apply the latest security technologies in real-world settings through collaboration with Naver Cloud.”
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- 작성일 2024-11-28
- 조회수 412
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- [24.11.05] SALab, Papers Approved for Publication at the ICSE 2025 International Conference
- [Prof. Sooyoung Cha] SALab, Papers Approved for Publication at the ICSE 2025 International Conference ■ Title: TopSeed: Learning Seed Selection Strategies for Symbolic Execution from Scratch ■ Author of a paper: Jaehyeok Lee, Prof. Sooyoung Cha ■ Conference: IEEE/ACM International Conference on Software Engineering (ICSE 2025) ■ Abstract: We present TopSeed, a new approach that automatically selects optimal seeds to enhance symbolic execution. Recently, the performance of symbolic execution has significantly improved through various state-of-the-art techniques, including search strategies and state-pruning heuristics. However, these techniques have typically demonstrated their effectiveness without considering “seeding”, which efficiently initializes program states for exploration. This paper aims to select valuable seeds from candidate inputs generated during interactions with any symbolic execution technique, without the need for a predefined seed corpus, thereby maximizing the technique's effectiveness. One major challenge is the vast number of candidates, making it difficult to identify promising seeds. To address this, we introduce a customized online learning algorithm that iteratively groups candidate inputs, ranks each group, and selects a seed from the top-ranked group based on data accumulated during symbolic execution. Experimental results on 17 open-source C programs show that TopSeed significantly enhances four distinct cutting-edge techniques, implemented on top of two symbolic executors, in terms of branch coverage and bug-finding abilities.
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- 작성일 2024-11-05
- 조회수 632
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- Software Department Lee Ji Hyeong_Challenge & Grace's Gratitude
- People Challenge & Grace's Gratitude 1. Challenge is giving oneself tough and difficult task Through challenge one shall learn. 2. Do not own the Grace you received, pass on to other. Prof. Lee Ji Hyeong Dep. of Software Prof. Lee Ji Hyeong has believed in the potential of A.I on the verge of graduate school choice, which led him choosing A.I Research lab that gave him a life-turning point. Since he became the professor at SKKU, he endeavored to manifest student's full potential, and founded A.I graduate school at 2019. This professor sends the message "True Professionalism" regarding to the education of prodigies, emphasizing responsibilities and problem-solving abilities. Furthermore, Informatics & Intellectual System Research is approved in well-renowned international academic conference LREC-COLING, which proved competence of SKKU research capability. Further details are asked to prof. Lee Ji Hyeong. | What is the motivation for A.I research? I had a hard time choosing the graduate school I should go. CS' essence is A.I to me, and that is the main reason I chose A.I Lab. Being appointed to SKKU is my life-turning choice. In 2002, I was excited for the challenge lying ahead of me when I was appointed to SKKU before the world-cup held in Korea. I had a strong desire of choosing A.I research lab when graduate school of A.I was founded at 2019. I wrote the proposal with effort, since I believed in SKKU's competence. | Most memorable anecdote from educating excellent prodigies. Educating students and researching is different. Graduate school and Undergraduate education is different. A.I graduate school business is about professionalism education rather than research. Educating these students is about drawing student's attention and support, and successfully managing the research. Those who could not graduate, failing exams, leaving of absence, each students need deep attention. I am proud when these students make it to the top on conference competition or challenges. I recall every students achievements and their journey along the process. | 인공지능 인재 양성의 방향성 I ask students to be a professional. Rather than the A.I technology itself, it is important to adapt problem solving ability. Able to complete the task never done before, and finishing the job in the name of honor and responsibilities are the crucial traits students should have. In our nation's perspective, I hope we can educate more prodigies. A.I critical algorithm developer, Technology Propaganda & Adaptation Professionals are the ones. One does not need to be the top of every field, but should be able to adapt A.I in these fields. Gaining control is also important. Although it is important to benchmark U.S' technology, but we should be able to assert dominance over some fields by strategical education. For instance, gaining dominant position in A.I semiconductor and so. | I heard that two papers from the Information and Intelligence Systems Lab have been accepted at the renowned international conference LREC-COLING in the field of natural language processing. Could you briefly explain the research? One paper is about detecting bugs in program code. It involves using large language models to identify logical errors in the code. The second paper focuses on utilizing small training data. We researched methods to effectively learn with limited data through data augmentation. | Which research project do you remember the most? Every research project is memorable in its own way. Research results are unpredictable; sometimes great research isn’t recognized, and other times research that falls short of expectations gets acknowledged. Research includes not just coming up with brilliant ideas but also refining them so they are accepted. Even if a paper gets rejected multiple times, it’s important to not be discouraged and keep revising it until it’s finally accepted. I advise my students not to give up and to keep challenging themselves. | What are your goals or operating philosophy in leading your lab? I focus on the growth of the students. Writing papers and conducting research are tools for education, and it’s important that students learn and grow through the research process. The relationship between professors and students is not one-sided but rather a collaborative one, where we discuss and enjoy the research together. One of the challenges of being the head of the AI department is gaining agreement and cooperation from students on shared goals. Challenges are inevitable, and overcoming them requires perseverance and effort to solve problems until the end. It’s also essential to understand and meet the needs of others. Developing the ability to wisely manage the stress that arises in these processes is important as well. | Is there anything you want to challenge yourself with? Right now, my goal is to accomplish the tasks that have been given to me both socially and personally. I try to live with a mindset of constantly challenging myself and learning new skills through difficult tasks. Challenge isn’t just about achieving big things; it’s also about trying things that are hard and that you don’t want to do. Challenge can also be seen as a process of developing your abilities by tackling tasks that are beyond your current skills. Even if you fail through the challenge, the new abilities you acquire make the effort worthwhile. The value of AI research, as an engineering discipline, lies in developing technology that benefits people. AI is a tool, and depending on how humans use it, it can produce either positive or negative outcomes. AI plays a critical role as an automation and assistance tool for humans. Being a professor is a profession that involves constant challenges, new research, and interactions with students. It’s a career that involves fostering talents who can adapt to the changing world, and it offers the freedom to challenge oneself, which makes it appealing. | How would you like to be remembered as a researcher or educator? This might sound a bit pessimistic, but I don’t particularly want to be remembered. I hope to quietly do my part and then naturally fade away. While I would like my work to have an impact on others, I don’t have any special ambitions. I would be happy if, when people think of me, they feel like they received a lot of help. In my life, I’ve received a great deal of help from others, but it’s difficult to repay that kindness to the same people. Instead, I want to repay that help by helping others in return. Rather than calculating things with a plus-and-minus mentality, I aim to live by giving as much as I’ve received. As an educator, my hope is to be someone who passes on the kindness I’ve received to students and others. I also hope that the students in my lab will carry this mindset of sharing the kindness they’ve received with others. | Any final words for the students at SKKU? The two key messages from today’s discussion are challenge and passing on kindness. First, be someone who embraces challenges. A challenge is doing something difficult and uncomfortable, and through challenges, you can gain learning. It’s important to always maintain a learning mindset. Second, pass on the kindness you’ve received. Don’t think of the kindness you’ve received as something that’s solely yours; you should share it with others. Since it’s often difficult to repay the kindness directly to the person who gave it to you, it’s important to pass it on to others. Whether as an educator or as an individual, it’s important to be someone who passes on kindness to others. I hope the students in the lab will also live by these values.
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- 작성일 2024-09-30
- 조회수 846