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238            <p><span class="anchor" id="about-me"></span></p>
239<p style="text-align: justify;">
240I am a Ph.D. candidate at <a href="https://www.njust.edu.cn/">Nanjing University of Science and Technology (NJUST)</a>. In 2024, I was a visiting Ph.D. student in the Department of Computing Science at the <a href="https://www.ualberta.ca/en/computing-science/index.html">University of Alberta</a>, working with Prof. <a href="https://webdocs.cs.ualberta.ca/~drafiei/">Davood Rafiei</a> on AI-assisted content generation. My research explores how <strong>natural language processing</strong> and <strong>large language models</strong> can help researchers extract, organize, and synthesize scientific knowledge. My recent work focuses on automated scientific survey generation, scientific named entity recognition, and scientific document summarization. Please feel free to contact me at <a href="mailto:[email protected]">[email protected]</a>.
241</p>
242

243<h1 id="-news">🔥 News</h1>
244<ul>
245  <li><em>2026.09</em>: 🎉 SurveyAgent-HKA has been accepted by <strong>Knowledge-Based Systems</strong>.</li>
246  <li><em>2026.08</em>: 🎉 TdSciNER has been accepted by <strong>Expert Systems with Applications</strong>.</li>
247  <li><em>2026.06</em>: 🎉 One paper has been accepted by <strong>ASIST 2026</strong>.</li>
248  <li><em>2025.09</em>: 🎉 SurveyGen has been accepted by <strong>EMNLP 2025</strong>.</li>
249</ul>
250
251<h1 id="-publications">📝 Publications</h1>
252
253<p>J = Journal article; C = Conference paper.</p>
254
255<ul>
256  <li>
257    <p>[J8] <strong>Tong Bao</strong>, Yi Zhao, Heng Zhang, and Chengzhi Zhang*. Enhancing Scientific Named Entity Recognition via Large Language Models: A Type-driven Multi-task Learning Approach. <strong><em>Expert Systems with Applications</em></strong>, 333: 133983, 2027. [<a href="https://doi.org/10.1016/j.eswa.2026.133983">doi</a>] [<a href="https://arxiv.org/abs/2608.08636">arXiv</a>]</p>
258  </li>
259  <li>
260    <p>[J7] <strong>Tong Bao</strong>, Mir Tafseer Nayeem, Yi Zhao, Davood Rafiei, and Chengzhi Zhang*. SurveyAgent-HKA: A Multi-agent Framework for Scientific Survey Generation with LLMs and Human Knowledge Augmentation. <strong><em>Knowledge-Based Systems</em></strong>, 352: 117011, 2026. [<a href="https://doi.org/10.1016/j.knosys.2026.117011">doi</a>] [<a href="https://arxiv.org/abs/2609.05938">arXiv</a>]</p>
261  </li>
262  <li>
263    <p>[J6] Wenqing Wu, Chengzhi Zhang, Yi Zhao, <strong>Tong Bao</strong>. Impact of Large Language Models on Peer Review Opinions from a Fine-grained Perspective: Evidence from Top Conference Proceedings in AI. <strong><em>Scientometrics</em></strong>, 131(5): 3547–3584, 2026. [<a href="https://doi.org/10.1007/s11192-026-05645-7">doi</a>] [<a href="https://arxiv.org/abs/2604.19578">arXiv</a>]</p>
264  </li>
265  <li>
266    <p>[J5] Yi Zhao, Heng Zhang, Yuzhuo Wang, Wenqing Wu, <strong>Tong Bao</strong>, and Chengzhi Zhang*. Measuring the Novelty of Biomedical Papers Using the Latent Distances between Knowledge Units. <strong><em>Journal of Information Science</em></strong>, 2027. [<a href="https://doi.org/10.1177/01655515261489497">doi</a>] [<a href="https://arxiv.org/abs/2609.05175">arXiv</a>]</p>
267  </li>
268  <li>
269    <p>[C4] Shuai Chen, <strong>Tong Bao</strong>, Jitong Peng, and Chengzhi Zhang*. More Computational Resources Do Not Ensure Higher Scholarly Impact: Evidence from Leading NLP Conference Papers. In <strong>Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing (EMNLP 2026)</strong>, 2026. [<a href="https://arxiv.org/abs/2608.21806">arXiv</a>]</p>
270  </li>
271  <li>
272    <p>[C3] <strong>Tong Bao</strong>, Xinyi Yan, Yi Zhao, Heng Zhang, and Chengzhi Zhang*. Structure before Text: Evaluating LLMs on Hierarchical Outline Generation for Scientific Surveys. In <strong>Proceedings of the 89th Annual Meeting of the Association for Information Science and Technology (ASIS&amp;T 2026)</strong>, Bangkok, Thailand, 2026. [<a href="https://www.asist.org/am26/">Poster</a>]</p>
273  </li>
274  <li>
275    <p>[J4] <strong>Tong Bao</strong>, Yi Zhao, Jin Mao, and Chengzhi Zhang*. Examining Linguistic Shifts in Academic Writing Before and After the Launch of ChatGPT: A Study on Preprint Papers. <strong><em>Scientometrics</em></strong>, 130(7): 3597–3627, 2025. [<a href="https://doi.org/10.1007/s11192-025-05341-y">doi</a>] [<a href="https://arxiv.org/abs/2505.12218">arXiv</a>]</p>
276  </li>
277  <li>
278    <p>[J3] Wenqing Wu, Chengzhi Zhang*, <strong>Tong Bao</strong>, and Yi Zhao. SC4ANM: Identifying Optimal Section Combinations for Automated Novelty Prediction in Academic Papers. <strong><em>Expert Systems with Applications</em></strong>, 273: 126778, 2025. [<a href="https://doi.org/10.1016/j.eswa.2025.126778">doi</a>] [<a href="https://arxiv.org/abs/2505.16330">arXiv</a>]</p>
279  </li>
280  <li>
281    <p>[J2] <strong>Tong Bao</strong>, Heng Zhang, and Chengzhi Zhang*. Enhancing Abstractive Summarization of Scientific Papers Using Structure Information. <strong><em>Expert Systems with Applications</em></strong>, 261: 125529, 2025. [<a href="https://doi.org/10.1016/j.eswa.2024.125529">doi</a>] [<a href="https://arxiv.org/abs/2505.14179">arXiv</a>]</p>
282  </li>
283  <li>
284    <p>[C2] <strong>Tong Bao</strong>, Mir Tafseer Nayeem, Davood Rafiei*, and Chengzhi Zhang*. SurveyGen: Quality-Aware Scientific Survey Generation with Large Language Models. In <strong>Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing (EMNLP 2025)</strong>, 2025. [<a href="https://doi.org/10.18653/v1/2025.emnlp-main.136">doi</a>] [<a href="https://arxiv.org/abs/2508.17647">arXiv</a>]</p>
285  </li>
286  <li>
287    <p>[C1] Yi Zhao, Heng Zhang, Wenqing Wu, <strong>Tong Bao</strong>, and Chengzhi Zhang*. Measuring the Novelty of Scientific Papers Based on the Latent Distance Between Pairs of MeSH Terms. In <strong>Proceedings of the 24th ACM/IEEE Joint Conference on Digital Libraries (JCDL 2024)</strong>, Hong Kong, China, 2024. [<a href="https://doi.org/10.1145/3677389.3702533">doi</a>]</p>
288  </li>
289  <li>
290    <p>[J1] <strong>Tong Bao</strong>, Ni Ren*, Rui Luo, Baojia Wang, Gengyu Shen, and Ting Guo. A BERT-based Hybrid Short Text Classification Model Incorporating CNN and Attention-based BiGRU. <strong><em>Journal of Organizational and End User Computing</em></strong>, 33(6): 1–21, 2021. [<a href="https://doi.org/10.4018/JOEUC.20211101.oa5">doi</a>]</p>
291  </li>
292</ul>
293

294<h1 id="-academic-service">🎓 Academic Service</h1>
295
296<ul>
297  <li><strong>Reviewer for:</strong> <em>Scientific data</em>, <em>IPM</em>, <em>ACL ARR</em>, <em>AAAI</em>, <em>ESWA</em>, <em>KBS</em>, <em>HSSC</em> and <em>Scientometrics</em>.</li>
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