{"id":1192,"date":"2025-09-08T14:24:01","date_gmt":"2025-09-08T06:24:01","guid":{"rendered":"https:\/\/sigkg.cn\/ccks2025\/?page_id=1192"},"modified":"2025-09-21T09:52:51","modified_gmt":"2025-09-21T01:52:51","slug":"accepted-papers","status":"publish","type":"page","link":"http:\/\/sigkg.cn\/ccks2025\/accepted-papers\/","title":{"rendered":"\u5f55\u7528\u8bba\u6587\u5217\u8868"},"content":{"rendered":"\n
\n

\u4f1a\u8bae\u8bba\u6587<\/h2>\n \n \n \n \n
\u7f16\u53f7<\/th>\n \u4f5c\u8005<\/th>\n \u6807\u9898<\/th>\n <\/tr>\n <\/thead>\n
1<\/td>Yashen Wang, Xiaoling Zhu, Yanhui Li, HUAN CHANG, Xiaoye Ouyang, Tianzhu Chen, Xiaowan Li<\/td>A Cross-Subgraph Attention Fusion and Comparison Method for Contrastive Learning Based Knowledge Graph Completion<\/td><\/tr>\n
2<\/td>Guangyun Yao<\/td>Knowledge Retrieval-Augmented Interest learning for Recommendation<\/td><\/tr>\n
3<\/td>Han Xue, Huiying Li, Shuo Kou<\/td>EDREL: Document-level Relation Extraction with Evidence and Logical Rules<\/td><\/tr>\n
4<\/td>Mao Liangjian<\/td>\u878d\u5408\u591a\u6e90\u65f6\u7a7a\u77e5\u8bc6\u56fe\u8c31\u4e0e\u56fe\u795e\u7ecf\u7f51\u7edc\u7684\u667a\u6167\u9009\u5740\u6a21\u578b<\/td><\/tr>\n
5<\/td>SHANG Jingyi, HOU Wenzhe, Weixin Zeng, Xiang Zhao<\/td>\u591a\u6e90\u5f02\u6784\u573a\u666f\u4e0b\u5bf9RDF-MT\u6280\u672f\u7684\u5b9e\u9a8c\u63a2\u7d22<\/td><\/tr>\n
6<\/td>Zhen Bi, Peng Chen, Kangrui Pan, Kang Zhao, Qing Shen, Zhenfang Liu, Jungang Lou<\/td>Autism Children Education Knowledge Graph: Construction and Validation<\/td><\/tr>\n
7<\/td>Tailai Han, Chuanyuan Tan, Wenbiao Shao, Hao Xiong, Wenliang Chen<\/td>\u9762\u5411\u4e0d\u53ef\u56de\u7b54\u95ee\u9898\u7684\u5927\u8bed\u8a00\u6a21\u578b\u62d2\u7b54\u80fd\u529b\u7efc\u5408\u8bc4\u4f30<\/td><\/tr>\n
8<\/td>Xiaohan He, Yinchi Li, Shuming Zhang, Meiling Wang, Qianyuan Cheng, Longkang Leng<\/td>Multi-granularity Hierarchical RAG for Welding Parameter Recommendation<\/td><\/tr>\n
9<\/td>Meiying Kang, Ruobing Shang, Wenliang Chen<\/td>\u57fa\u4e8e\u5927\u8bed\u8a00\u6a21\u578b\u8bed\u4e49\u589e\u5f3a\u7684\u79fb\u52a8\u5e94\u7528\u4f7f\u7528\u9884\u6d4b\u65b9\u6cd5<\/td><\/tr>\n
10<\/td>Jibing Gong, Xinchao Feng, Qian Zang, Yi Zhao, Le Chen, Yu Qiu, Jun Feng, Haomin Song, Liangying Peng<\/td>Knowledge Graph-based Recommendation via Generative Denoising and Multi-Level Contrastive Learning<\/td><\/tr>\n
11<\/td>Guanfeng Li<\/td>\u4e0d\u786e\u5b9a\u77e5\u8bc6\u56fe\u8c31\u5d4c\u5165\u65b9\u6cd5\u7814\u7a76\u7efc\u8ff0<\/td><\/tr>\n
12<\/td>Cheng Zhang, Qi Huang, Mingwen Wang, Huiqin Xu, Wenbing Luo, Ying ting Zhu<\/td>\u57fa\u4e8e\u6df7\u5408\u4e13\u5bb6\u591a\u89c6\u89d2\u5b66\u4e60\u7684\u77e5\u8bc6\u56fe\u8c31\u8865\u5168<\/td><\/tr>\n
13<\/td>Jiahao Hu, Chaoran Zhou, Hongwei Yang, Zhongbao Wei, Xin Zhang<\/td>\u7ed3\u5408\u534f\u540c\u6ce8\u610f\u529b\u4ea4\u4e92\u4e0e\u591a\u5c3a\u5ea6\u5faa\u73af\u5377\u79ef\u7684\u77e5\u8bc6\u56fe\u8c31\u8865\u5168\u65b9\u6cd5<\/td><\/tr>\n
14<\/td>Langjunqing Jin, Yarong Shang, Chao Yu, Kaiqi Chi<\/td>\u57fa\u4e8e\u7ed3\u6784\u5316\u53cc\u5411\u7f16\u7801\u7684\u6570\u5b66\u77e5\u8bc6\u56fe\u8c31\u8868\u793a\u5b66\u4e60<\/td><\/tr>\n
15<\/td>Huanran Zheng, Xiaoling Wang, Jingwei Zhang, Ya Zhou<\/td>Aggressive Speculative Decoding for Efficient Chain-of-Thought Reasoning<\/td><\/tr>\n
16<\/td>Feng Gao, Yuchen He, Na Zhang, Jinguang Gu<\/td>FEFT: A Feedback-enhanced Evaluation Fine-tuning Framework for Financial Report Summarization<\/td><\/tr>\n
17<\/td>Xi Wu, Bin Wu, Tianyu Lin, Kexin Zhao, Wenzhe Zhang, Xingkun Qin, Jibing Gong<\/td>POMNS: Positive-Offset Mixed Negative Sampling for Graph-Based Recommendation<\/td><\/tr>\n
18<\/td>Chengyuan Jin, Tong Zhou, Yubo Chen, Kang Liu, Jun Zhao<\/td>MAEPS: Multi-Agent Event Prediction System Based on Human Expert Team Collaboration Simulation<\/td><\/tr>\n
19<\/td>Yu Qiu, \u51af\u73fa, \u90d1\u54f2\u6167, Yi Zhao, \u5b8b\u660a\u65fb, \u9648\u7956\u6b4c, \u738b\u7ecd\u5170<\/td>\u7535\u529b\u9886\u57df\u57fa\u4e8e\u4e0a\u4e0b\u6587\u77e5\u8bc6\u63d0\u793a\u7684\u5927\u6a21\u578b\u89c6\u89c9\u95ee\u7b54\u6280\u672f\u7814\u7a76<\/td><\/tr>\n
20<\/td>Yongshen zhu, Chengjie Sun, Lei Lin, Bingquan Liu<\/td>Character-Boundary-Aware and Type-Decoupled Named Entity Recognition Enhanced by a Post-Correction Model<\/td><\/tr>\n
21<\/td>Xi Wang, Xin Xin<\/td>A Preliminary Attempt to Generate a Sichuan Dialect Handbook by LLMs<\/td><\/tr>\n
22<\/td>\u5f90\u8d1e\u987a<\/td>\u57fa\u4e8e\u5c42\u6b21\u5316\u591a\u6a21\u6001\u878d\u5408\u4e0e\u56f0\u96be\u8d1f\u91c7\u6837\u7684\u77e5\u8bc6\u56fe\u8c31\u8865\u5168<\/td><\/tr>\n
23<\/td>Zitian Wang, Kang Xu, Zhenjiang Dong<\/td>CNER-PH\uff1a\u4e00\u4e2a\u7528\u4e8e\u836f\u7269\u8b66\u6212\u7684\u4e2d\u6587\u547d\u540d\u5b9e\u4f53\u8bc6\u522b\u6570\u636e\u96c6<\/td><\/tr>\n
24<\/td>\u8d75\u8f7d\u5143, Hairong Wang, \u9648\u82b3\u840d, \u674e\u7ea2\u82f1<\/td>\u57fa\u4e8e\u63d0\u793a\u5b66\u4e60\u7684\u591a\u6a21\u6001\u547d\u540d\u5b9e\u4f53\u8bc6\u522b\u65b9\u6cd5\u7814\u7a76\u8fdb\u5c55<\/td><\/tr>\n
25<\/td>Letao Han, Yuemei Xu, Qian Yuan<\/td>C-Voice: Culturally-grounded Multi-dimensional Alignment of LLMs with Chinese Social Values<\/td><\/tr>\n
26<\/td>Huanke You, \u534e\u5374\u624d\u8ba9, Haixing Zhao<\/td>\u9762\u5411\u5927\u6a21\u578b\u7684\u6700\u4f18\u85cf\u6587\u5b57\u8868\u6784\u5efa<\/td><\/tr>\n
27<\/td>Manlai Liang, Wanyi Huang, Mandi Liu, Huaijun Li, Jinlong Li<\/td>Lag-Relative Sparse Attention In Long Context Training<\/td><\/tr>\n
28<\/td>bohan xie, Shirui Wang, Ling Ding, Jianting Chen, Yang Xiang<\/td>VIKA: Vectorized Indispensable Knowledge-subgraph Augmentation for Large Language Models<\/td><\/tr>\n
29<\/td>ruolin su, Yongkang Zhou, JUNJIE YAO<\/td>\u591a\u6e90\u77e5\u8bc6\u9a71\u52a8\u7684\u5fc3\u7406\u54a8\u8be2\u6570\u5b57\u4ea4\u4e92\u7cfb\u7edf\uff1a\u77e5\u8bc6\u589e\u5f3a\u4e0e\u5e7b\u89c9\u6291\u5236<\/td><\/tr>\n
30<\/td>Jibing Gong, Le Chen, Qian Zang, Xinchao Feng, Yi Zhao, Yu Qiu, Jun Feng, Haomin Song, Liangying Peng<\/td>DKGFN: Deep Knowledge Graph Fusion Network for Recommendation<\/td><\/tr>\n
31<\/td>Yixuan Wang, Jiamin Lv, Xiaofu Song, Bo Zhao<\/td>\u5927\u6a21\u578b\u9a71\u52a8\u7684\u6a21\u5757\u5316\u5b89\u5168\u672c\u4f53\u6784\u5efa\u65b9\u6848<\/td><\/tr>\n
32<\/td>Yangjuan Hu, Kaile Wang, Fei Yang, Yuling Li<\/td>\u9762\u5411\u5c11\u6837\u672c\u77e5\u8bc6\u56fe\u8c31\u8865\u5168\u7684\u5173\u7cfb\u611f\u77e5\u8bed\u4e49\u5efa\u6a21\u65b9\u6cd5<\/td><\/tr>\n
33<\/td>\u848b\u6c38\u4f73, \u803f\u751f\u73b2, \u8d3e\u6cfd\u5b87, \u674e\u5347\u5b8f<\/td>\u878d\u5408\u5927\u8bed\u8a00\u6a21\u578b\u4e0e\u52a8\u6001\u53cd\u9988\u673a\u5236\u7684\u9e1f\u7c7b\u77e5\u8bc6\u56fe\u8c31\u8865\u5168\u65b9\u6cd5<\/td><\/tr>\n
34<\/td>GengShuobiao, Hairong Wang, \u6768\u632f\u4e1a, YangJianling<\/td>\u591a\u6a21\u6001\u5bf9\u6297\u5b66\u4e60\u4e0e\u7279\u5f81\u589e\u5f3a\u7684\u77e5\u8bc6\u63a8\u7406\u65b9\u6cd5<\/td><\/tr>\n
35<\/td>Jian Zhang, Jin-Tao Tang, Shasha Li, Wang Kaixuan, Ting Wang<\/td>Iterative Generation Method for Factual QA in Large Language Models Based on Semantic Entropy Verification<\/td><\/tr>\n
36<\/td>Chengbiao Yang, Lingyu Zhang, Guilin Qi<\/td>Traff-LLM: A Spatio-Temporal Knowledge-Guided Large Language Model for Traffic Flow Prediction<\/td><\/tr>\n
37<\/td>Feng Gao, YueSun, Yuanyuan Li, Jinguang Gu<\/td>Zero-shot Instruction Generation via Dual-Alignment Instruction Wrappers with Summary-Text fused instruction wrappers<\/td><\/tr>\n
38<\/td>Yi Tang, Yongbin Liu, Chunping Ouyang, Ying Yu<\/td>LADVA: LLM-Augmented Dual-View Alignment for Zero-Shot Extreme Multi-Label Classification<\/td><\/tr>\n
39<\/td>\u6c5f\u6d69, \u4e07\u4e2d\u82f1, Xueqiang Zeng, Mingwen Wang<\/td>\u57fa\u4e8e\u5e38\u8bc6\u77e5\u8bc6\u548c\u60c5\u7eea\u77e5\u8bc6\u8bed\u4e49\u4e0d\u4e00\u81f4\u7684\u8bbd\u523a\u68c0\u6d4b\u65b9\u6cd5<\/td><\/tr>\n
40<\/td>NAIZHOU ZHANG<\/td>\u57fa\u4e8e\u77e5\u8bc6\u589e\u5f3a\u548c\u6f5c\u4e3b\u9898\u5b66\u4e60\u7684\u5c0f\u8bed\u8a00\u6a21\u578b\u4f4e\u8d44\u6e90\u5bf9\u8bdd\u751f\u6210<\/td><\/tr>\n
41<\/td>XuZhaojing, Wanghairong, Zane Yi<\/td>\u5c42\u6b21\u62d3\u6251\u589e\u5f3a\u7684\u751f\u6210\u5f0f\u591a\u6a21\u6001\u63a8\u8350\u7b97\u6cd5<\/td><\/tr>\n <\/tbody>\n <\/table>\n<\/section>\n\n
\n

\u6d77\u62a5\u8bba\u6587<\/h2>\n \n \n \n \n
\u7f16\u53f7<\/th>\n \u4f5c\u8005<\/th>\n \u6807\u9898<\/th>\n <\/tr>\n <\/thead>\n
1<\/td>Yidan Wang, Yubing Ren, Yanan Cao, Binxing Fang<\/td>Trade-off to Synergy: A Versatile Symbiotic Watermarking Framework for Large Language Models<\/td><\/tr>\n
2<\/td>Zhichao Yan\uff0cJiapu Wang\uff0cJiaoyan Chen\uff0cYanyan Wang, Hongyan Tan, Jiye Liang, Xiaoli Li, Ru Li, Jeff Z.Pan<\/td>Prompting Large Language Models with Partial Knowledge for Answering Questions with Unseen Entities<\/td><\/tr>\n
3<\/td>\u9a6c\u73ae\u7490\uff0c\u5b59\u5766\uff0c\u8d75\u745e\u96ea\uff0c\u9c9c\u56fd\u5efa<\/td>\u57fa\u4e8eLLM\u548cGraphRAG\u7684\u79d1\u6280\u6587\u732e\u56fe\u8c31\u5f0f\u6458\u8981\u751f\u6210\u7814\u7a76<\/td><\/tr>\n
4<\/td>Yushi Bai, Shangqing Tu, Jiajie Zhang, Hao Peng, Xiaozhi Wang, Xin Lv, Shulin Cao, Jiazheng Xu, Yijian Lyu, Nianyi Lin, Lei Hou, Yuxiao Dong, Jie Tang, Juanzi Li<\/td>LongBench v2: Towards Deeper Understanding and Reasoning on Realistic Long-context Multitasks<\/td><\/tr>\n
5<\/td>\u82cf\u82e5\u7433\uff0c\u5468\u6c38\u5eb7\uff0c\u59da\u4fca\u6770<\/td>PsyFusion-RAG\uff1a\u591a\u6e90\u77e5\u8bc6\u534f\u540c\u7684\u5fc3\u7406\u5bf9\u8bdd\u751f\u6210\u6a21\u578b<\/td><\/tr>\n
6<\/td>Xueru Wen, Jie Lou, Zichao Li, Yojie Lu, Xing Yu, Yuqiu Ji, Guohai Xu, Hongyu Lin, Ben He, Xianpei Han, Le Sun, Debing Zhang<\/td>Cheems: A Practical Guidance for Building and Evaluating Chinese Reward Models from Scratch<\/td><\/tr>\n
7<\/td>\u9f50\u97f5\u5609\uff0c\u5f6d\u7693\uff0c\u590f\u6d69\u5929\uff0c\u5f6d\u626c\u8fbe\uff0c\u9648\u4e88\u83f2\uff0c\u8bb8\u658c\uff0c\u4faf\u78ca\uff0c\u674e\u6d93\u5b50<\/td>CONE: \u9762\u5411\u590d\u6742\u6307\u4ee4\u7406\u89e3\u7684\u5927\u8bed\u8a00\u6a21\u578b\u80fd\u529b\u8bc4\u4f30<\/td><\/tr>\n
8<\/td>Dan Wang, Boxi Cao, Ning Bian, Xuanang Chen, Yaojie Lu, Hongyu Lin Jia Zheng, Le Sun, Shanshan Jiang, Bin Dong, Xianpei Han<\/td>The Linguistic Connectivities Within Large Language Models<\/td><\/tr>\n
9<\/td>Shiyao Xie, Jian Du<\/td>ClinGuide-Agent: A Knowledge-Graph-Powered Multi-Agent for Executable Clinical Guidelines in Comorbidity Care<\/td><\/tr>\n
10<\/td>Guanghui Deng, Xuanyu Shi, Jian Du<\/td>CKG2DAG: Translating Large Language Model Based Cohort Knowledge Graphs into Directed Acyclic Graphs<\/td><\/tr>\n
11<\/td>\u803f\u7855\u5f6a\uff0c \u738b\u6d77\u8363\uff0c\u6768\u632f\u4e1a\uff0c\u738b\u9759\uff0c\u674e\u7ea2\u82f1<\/td>\u57fa\u4e8e\u5bf9\u6297\u7f51\u7edc\u4e0e\u5173\u7cfb\u5f15\u5bfc\u6ce8\u610f\u529b\u7684\u77e5\u8bc6\u63a8\u7406\u65b9\u6cd5<\/td><\/tr>\n
12<\/td>Lan Yang, Jian Du<\/td>Using Large Language Models to Identify External Validity Gaps in Diabetes RCTs through Scientific Commentaries to Inform Guideline Development<\/td><\/tr>\n
13<\/td>\u6731\u4ef0\u745e\uff0c\u59da\u53cc\u9f99\uff0c\u5218\u70e8\uff0c\u5b59\u4e91\u680b\uff0c\u6768\u4ead\uff0c\u9648\u5409\uff0c\u738b\u661f<\/td>PLM\u4e0e\u56fe\u795e\u7ecf\u7f51\u7edc\u878d\u5408\u7684\u8def\u5f84\u63d0\u793a\u77e5\u8bc6\u56fe\u8c31\u94fe\u8def\u9884\u6d4b\u65b9\u6cd5<\/td><\/tr>\n
14<\/td>Yilong Chen, Junyuan Shang, Zhenyu Zhang, Yanxi Xie, Jiawei Sheng, Tingwen Liu, Shuohuan Wang, Yu Sun, Hua Wu, Haifeng Wang<\/td>Inner Thinking Transformer: Leveraging Dynamic Depth Scaling to Foster Adaptive Internal Thinking<\/td><\/tr>\n
15<\/td>Qian Li , Cheng Ji , Shu Guo , Peng Kun , Qianren Mao , Shangguang Wang<\/td>Variational Multi-Modal Hypergraph Attention Network for Multi-Modal Relation Extraction<\/td><\/tr>\n
16<\/td>Qian Li , Siyuan Liang , Yuzheng Zhang , Cheng Ji , Zongyu Chang , Shangguang Wang<\/td>Meta-Knowledge Path Augmentation for Multi-Hop Reasoning on Satellite Commonsense Multi-Modal Knowledge Graphs<\/td><\/tr>\n
17<\/td>\u9ec4\u690d\u6ec7\uff0c\u5218\u91d1\u946b\uff0c\u59da\u5b50\u4fca\uff0c\u8f9b\u99a8\uff0c\u53f6\u4f73\u7136\uff0c\u4faf\u78ca\uff0c\u674e\u6d93\u5b50<\/td>Are LLMs Syllogistic Reasoners? A Mechanistic Interpretation Perspective via Activation Patching<\/td><\/tr>\n
18<\/td>Zhen Bi, Ningyu Zhang, Yida Xue, Yixin Ou, Daxiong Ji, Guozhou Zheng, Huajun Chen<\/td>OceanGPT\u00b7\u6ca7\u6e0a: \u6d77\u6d0b\u57fa\u7840\u5927\u6a21\u578b<\/td><\/tr>\n
19<\/td>Zichao Li, Aizier Abulaiti, Yaojie Lu, Xuanang Chen, Jia Zheng, Hongyu Lin, Xianpei Han, Shanshan Jiang, Bin Dong, Le Sun<\/td>READOC: A Unified Benchmark for Realistic Document Structured Extraction<\/td><\/tr>\n
20<\/td>\u5f90\u82e5\u66e6\uff0c\u8ba1\u4e91\u6770\uff0c\u66f9\u535a\u5e0c\uff0c\u9646\u579a\u6770\uff0c\u6797\u9e3f\u5b87\uff0c\u97e9\u5148\u57f9\uff0c\u4f55\u82ef\uff0c\u5b59\u5e94\u98de\uff0c\u674e\u663e\u521a\uff0c\u5b59\u4e50<\/td>\u4e0d\u6b62\u4e8e\u6b7b\u8bb0\u786c\u80cc\uff1a\u57fa\u4e8e\u63a8\u7406\u7684\u6df1\u5ea6\u77e5\u8bc6\u6ce8\u5165<\/td><\/tr>\n
21<\/td>\u95e8\u946b\uff0c\u5f90\u540d\u5b87\uff0c\u5f20\u6e05\u5b87\uff0c\u8881\u5343\u7693\uff0c\u738b\u70b3\u5b81\uff0c\u6797\u9e3f\u5b87\uff0c\u9646\u579a\u6770\uff0c\u97e9\u5148\u57f9\uff0c\u5b59\u4e50\uff0c\u9648\u709c\u9e4f<\/td>ShortGPT: Layers in Large Language Models are More Redundant Than You Expect<\/td><\/tr>\n <\/tbody>\n <\/table>\n<\/section>\n\n
\n

Demo \u8bba\u6587<\/h2>\n \n \n \n \n
\u7f16\u53f7<\/th>\n \u4f5c\u8005<\/th>\n \u6807\u9898<\/th>\n <\/tr>\n <\/thead>\n
1<\/td>\u5f6d\u6021\u5fc3\uff0c\u738b\u73ae<\/td>AI\u5927\u6a21\u578b\u5e94\u7528 – \u667a\u80fd\u5065\u5eb7\u9669\u63a8\u8350<\/td><\/tr>\n
2<\/td>\u8d75\u5982\u7389\uff0c\u738b\u5143\u6df3<\/td>AMiner\u4eae\u70b9\uff1aAI\u6211\u7684\u5b66\u672f\u4eae\u70b9\uff0c\u8ba9\u4f18\u79c0\u770b\u5f97\u89c1<\/td><\/tr>\n <\/tbody>\n <\/table>\n<\/section>\n\n
\n

\u4eae\u70b9\u540d\u5355<\/h2>\n \n \n \n \n \n \n \n \n \n \n \n
\u5956\u9879<\/th>\n \u4f5c\u8005<\/th>\n \u6807\u9898<\/th>\n <\/tr>\n <\/thead>\n
\u4eae\u70b9\u8bba\u6587<\/td>\n Tailai Han, Chuanyuan Tan, Wenbiao Shao, Hao Xiong, Wenliang Chen<\/td>\n \u9762\u5411\u4e0d\u53ef\u56de\u7b54\u95ee\u9898\u7684\u5927\u8bed\u8a00\u6a21\u578b\u62d2\u7b54\u80fd\u529b\u7efc\u5408\u8bc4\u4f30<\/td>\n <\/tr>\n
\u4eae\u70b9\u8bba\u6587<\/td>\n Huanran Zheng, Xiaoling Wang, Jingwei Zhang, Ya Zhou<\/td>\n Aggressive Speculative Decoding for Efficient Chain-of-\nThought Reasoning<\/td>\n <\/tr>\n
\u4eae\u70b9\u8bba\u6587\u5019\u9009<\/td>\n SHANG Jingyi, HOU Wenzhe, Weixin Zeng, Xiang Zhao<\/td>\n \u591a\u6e90\u5f02\u6784\u573a\u666f\u4e0b\u5bf9RDF-MT\u6280\u672f\u7684\u5b9e\u9a8c\u63a2\u7d22<\/td>\n <\/tr>\n
\u4eae\u70b9\u8bba\u6587\u5019\u9009<\/td>\n Jibing Gong, Xinchao Feng, Qian Zang, Yi Zhao, Le Chen,\nYu Qiu, Jun Feng, Haomin Song, Liangying Peng<\/td>\n Knowledge Graph-based Recommendation via\nGenerative Denoising and Multi-Level Contrastive Learning<\/td>\n <\/tr>\n
\u4eae\u70b9\u6d77\u62a5<\/td>\n Huanke You, \u534e\u5374\u624d\u8ba9, Haixing Zhao<\/td>\n \u9762\u5411\u5927\u6a21\u578b\u7684\u6700\u4f18\u85cf\u6587\u5b57\u8868\u6784\u5efa<\/td>\n <\/tr>\n
\u4eae\u70b9\u6d77\u62a5<\/td>\n Zhichao Yan\uff0cJiapu Wang\uff0cJiaoyan Chen\uff0cYanyan Wang,\nHongyan Tan, Jiye Liang, Xiaoli Li, Ru Li, Jeff Z.Pan<\/td>\n Prompting Large Language Models with Partial\nKnowledge for Answering Questions with Unseen Entities<\/td>\n <\/tr>\n
\u4eae\u70b9Demo<\/td>\n \u8d75\u5982\u7389\uff0c\u738b\u5143\u6df3<\/td>\n AMiner\u4eae\u70b9\uff1aAI\u6211\u7684\u5b66\u672f\u4eae\u70b9\uff0c\u8ba9\u4f18\u79c0\u770b\u5f97\u89c1<\/td>\n <\/tr>\n\n \n <\/tbody>\n <\/table>\n<\/section>\n","protected":false},"excerpt":{"rendered":"

\u4f1a\u8bae\u8bba\u6587 \u7f16\u53f7 \u4f5c\u8005 \u6807\u9898 1 Yashen Wang, Xiaoling Zhu, Yanhui Li, H […]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"full-width-page-template.php","meta":[],"_links":{"self":[{"href":"https:\/\/sigkg.cn\/ccks2025\/wp-json\/wp\/v2\/pages\/1192"}],"collection":[{"href":"https:\/\/sigkg.cn\/ccks2025\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/sigkg.cn\/ccks2025\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/sigkg.cn\/ccks2025\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/sigkg.cn\/ccks2025\/wp-json\/wp\/v2\/comments?post=1192"}],"version-history":[{"count":10,"href":"https:\/\/sigkg.cn\/ccks2025\/wp-json\/wp\/v2\/pages\/1192\/revisions"}],"predecessor-version":[{"id":1353,"href":"https:\/\/sigkg.cn\/ccks2025\/wp-json\/wp\/v2\/pages\/1192\/revisions\/1353"}],"wp:attachment":[{"href":"https:\/\/sigkg.cn\/ccks2025\/wp-json\/wp\/v2\/media?parent=1192"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}