Publications

J. Yang, B. Yan, R. Li, Z. Zhou, X. Chen, Z. Feng, W. Peng. 2025. Gradient Co-occurrence Analysis for Detecting Unsafe Prompts in Large Language Models. arXive preprint arXiv:2502.12411, https://arxiv.org/abs/2502.12411.
J. Yang, R. Li, W. Wang, Z. Zhou, Z. Feng, W. Peng. 2025. LF-Steering: Latent Feature Activation Steering for Enhancing Semantic Consistency in Large Language Models. arXive preprint arXiv: 2501.11036, https://arxiv.org/abs/2501.11036.
H. Liu, R. Li, W. Xiong, Z. Zhou, W. Peng. 2025. WorkTeam: Constructing Workflow from Natural Language with Multi-Agents. In Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 3: Industry Track), pages 20–35, Albuquerque, New Mexico. Association for Computational Linguistics.
W. Wang, J. Yang, W. Peng. 2025. Semantics-Adaptive Activation Intervention for LLMs via Dynamic Steering Vectors. In Proceedings of the International Conference on Learning Representations (ICLR 2025), Singapore, 2025, Accepted to Appear.
H. Cao, H. Miao, W. Wang, L. Li, W. Peng, T. Zhao. Bilingual phrase induction with local hard negative sampling. CAAI Trans. Intell. Technol. 10(1), 147-159 (2025). https://doi.org/10.1049/cit2.12383.
W. Xiong, Y. Song, X. Zhao, W. Wu, X. Wang, K. Wang, C. Li, W. Peng, S. Li. 2024. Watch Every Step! LLM Agent Learning via Iterative Step-level Process Refinement.In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP 2024), pages 1556-1572, Miami, Florida, USA. Association for Computational Linguistics.
X. Zhao, K. Wang, W. Peng. 2024. An Electoral Approach to Diversify LLM-based Multi-Agent Collective Decision-Making. In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP 2024), pages 2712-2727, Miami, Florida, USA. Association for Computational Linguistics.
Y. Song, W. Xiong, X. Zhao, D. Zhu, W. Wu, K. Wang, C. Li, W. Peng, S. Li. 2024. AgentBank: Towards Generalized LLM Agents via Fine-Tuning on 50000+ Interaction Trajectories. In Findings of the Association for Computational Linguistics: EMNLP 2024, pages 2124-2141, Miami, Florida, USA. Association for Computational Linguistics.
J. Yang, D. Chen, Y. Sun, R. Li, Z. Feng, W. Peng. 2024. Enhancing Semantic Consistency of Large Language Models through Model Editing: An Interpretability-Oriented Approach. In Findings of the Association for Computational Linguistics: ACL 2024, pages 3343-3353, Bangkok, Thailand. Association for Computational Linguistics.
X. Zhao, K. Wang, W. Peng. 2024. Measuring the Inconsistency of Large Language Models in Preferential Ranking. In Proceedings of the 1st Workshop on Towards Knowledgeable Language Models (KnowLLM 2024), pages 171-176, Bangkok, Thailand. Association for Computational Linguistics.
Y. Chen, D. Chen, R. Liu, S. Zhou, W. Xue and W. Peng, “Align Before Adapt: Leveraging Entity-to-Region Alignments for Generalizable Video Action Recognition,” 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Seattle, WA, USA, 2024, pp. 18688-18698, doi: 10.1109/CVPR52733.2024.01768.
W. Wang, B. Haddow, A. Birch, W. Peng. 2024. Assessing Factual Reliability of Large Language Model Knowledge. In Proceedings of the 2024 Annual Conference of the North American Chapter of the Association for Computational Linguistics (Volume 1: Long Papers), pages 805-819, Mexico City, Mexico. Association for Computational Linguistics.
J. Jiang, X. Yin, X. Wan, W. Peng, R. Li, J. Yang, Y. Zhou. 2024. Contextual Modeling for Document-level ASR Error Correction. In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), pages 3855–3867, Torino, Italia. ELRA and ICCL.
J. Jiang, X. Wan, W. Peng, R. Li, J. Yang and Y. Zhou, “Cross Modal Training for ASR Error Correction with Contrastive Learning,” ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Seoul, Korea, Republic of, 2024, pp. 12246-12250, doi: 10.1109/ICASSP48485.2024.10446621.
Z. Yao, H. Zhang, Y. Guo, X. Tian, W. Peng, Y. Zou, LY Zhang, C. Chen, “Reverse Backdoor Distillation: Towards Online Backdoor Attack Detection for Deep Neural Network Models,” in IEEE Transactions on Dependable and Secure Computing, vol. 21, no. 06, pp. 5098-5111, Nov.-Dec. 2024, doi: 10.1109/TDSC.2024.3369751.
Wang, K.; Zhao, X.; and Peng, W. 2024. Learning from Failure: Improving Meeting Summarization without Good Samples. In Proceedings of the AAAI Conference on Artificial Intelligence, 38(17), 19153-19161. https://doi.org/10.1609/aaai.v38i17.29883
Zhang, Z.; Lu, N.; Liao, M.; Huang, Y.; Li, C.; Wang, M.; and Peng, W. 2024. Self-distillation Regularized Connectionist Temporal Classification Loss for Text Recognition: A Simple Yet Effective Approach. In Proceedings of the AAAI Conference on Artificial Intelligence, 38(7), 7441-7449. https://doi.org/10.1609/aaai.v38i7.28575
H. Liu, W. Xue, Y. Chen, D. Chen, X. Zhao, K. Wang, L. Hou, R. Li, W. Peng. 2024. A Survey on Hallucination in Large Vision-Language Models. arXive preprint arXiv:2402.00253, https://arxiv.org/abs/2402.00253.
Z. Wan, X. Wan, W. Peng, R. Li. 2023. New Datasets and Controllable Iterative Data Augmentation Method for Code-switching ASR Error Correction. In Findings of the Association for Computational Linguistics: EMNLP 2023, pages 8075-8087, Singapore. Association for Computational Linguistics.
X. Zhao, K. Wang, W. Peng. 2023. ORCHID: A Chinese Debate Corpus for Target-Independent Stance Detection and Argumentative Dialogue Summarization. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP 2023, Long Paper), pages 9358-9375, Singapore. Association for Computational Linguistics.
K. Wang, X. Zhao, Y. Li, W. Peng. 2023. PROSE: A Pronoun Omission Solution for Chinese-English Spoken Language Translation. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP 2023, Long Paper), pages 2297-2311, Singapore. Association for Computational Linguistics.
K. Wang, X. Zhao, Y. Li, W. Peng. 2023. M^3Seg: A Maximum-Minimum Mutual Information Paradigm for Unsupervised Topic Segmentation in ASR Transcripts. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP 2023), pages 7928-7934, Singapore. Association for Computational Linguistics.
R. Li and W. Peng. 2023. Dictionary-driven Chinese ASR Entity Correction with Controllable Decoding. In 2023 Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC), pages 1542-1548, Taipei, Taiwan.
R. Liu, N. Lu, D. Chen, C. Li, Z. Yuan, and W. Peng. 2023. PBFormer: Capturing Complex Scene Text Shape with Polynomial Band Transformer. In Proceedings of the 31st ACM International Conference on Multimedia (MM’23). pages 2112-2120, Ottawa, Canada. https://doi.org/10.1145/3581783.3612059
Y. Chen, D. Chen, R. Liu, H. Li and W. Peng, “Video Action Recognition with Attentive Semantic Units,” 2023 IEEE/CVF International Conference on Computer Vision (ICCV), Paris, France, 2023, pp. 10170-10180, doi: 10.1109/ICCV51070.2023.00933.
H. Liu, D. Chen, R. Li, W. Xue, W. Peng. 2023. Video Summarization Leveraging Multi-modal Information for Presentations. In Proceedings of Interspeech 2023, pages 5251-5252, Dublin, Ireland.
W. Xue, D. Chen, B. Yu, Y. Chen, S. Zhou, W. Peng. 2023. ChartDETR: A Multi-shape Detection Network for Visual Chart Recognition. arXive preprint arXiv:2308.07743, https://arxiv.org/abs/2308.07743.
Y. Sun, R. Zhang, J. Yang, W. Peng. 2023. Intent Discovery with Frame-guided Semantic Regularization and Augmentation. In Findings of the Association for Computational Linguistics: ACL 2023, pages 14254-14261, Toronto, Canada. Association for Computational Linguistics.
H. Cao, T. Zhao, W. Wang, W. Peng, Bilingual word embedding fusion for robust unsupervised bilingual lexicon induction, Information Fusion, Volume 97, 2023, 101818, ISSN 1566-2535, https://doi.org/10.1016/j.inffus.2023.101818.
Y. Huang, N. Lu, D. Chen, Y. Li, Z. Xie, S. Zhu, L. Gao, W. Peng, “Improving Table Structure Recognition with Visual-Alignment Sequential Coordinate Modeling,” 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Vancouver, BC, Canada, 2023, pp. 11134-11143, doi: 10.1109/CVPR52729.2023.01071.
R. Zhang, Y. Sun, J. Yang and W. Peng, “Knowledge-Augmented Frame Semantic Parsing with Hybrid Prompt-Tuning,” ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Rhodes Island, Greece, 2023, pp. 1-5, doi: 10.1109/ICASSP49357.2023.10095476.
W. Wang, C. Lee, J. Liu, T. Colakoglu, W. Peng. 2023. An Empirical Study of Cyclical Learning Rate on Neural Machine Translation, Natural Language Engineering, 29(2):316-336. Cambridge University Press.
W. Wang, W. Peng, Q. Liu. 2023. Learning Homographic Disambiguation Representation for Neural Machine Translation. arXiv preprint arXiv:2304.05860, https://arxiv.org/abs/2304.05860.
W. Wang, X. Meng, S. Yan, Y. Tian, W. Peng. 2022. Huawei BabelTar NMT at WMT22 Biomedical Translation Task: How we further improve domain-specific NMT. In Proceedings of the Seventh Conference on Machine Translation (WMT22): Shared Task Papers, pages 930-935, Abu Dhabi, United Arab Emirates. Association for Computational Linguistics.
Z. Feng, H. Cao, T. Zhao, W. Wang, W. Peng. 2022. Cross-lingual Feature Extraction from Monolingual Corpora for Low-resource Unsupervised Bilingual Lexicon Induction. In Proceedings of the 29th International Conference on Computational Linguistics (COLING 2022), pages 5278-5287, Gyeongju, Republic of Korea. International Committee on Computational Linguistics.
B. Zeng, B. Liu, H. Li, X. Liu, J. Liu, D. Chen, W. Peng, B. Zhang. 2022. FNeVR: Neural Volume Rendering for Face Animation. In Proceedings of the 36th International Conference on Neural Information Processing Systems (NeurIPS 2022), pages 22451-22462, New Orleans, USA.
D. Chen, M. Wang, H. Chen, L. Wu, J. Qin, and W. Peng. 2022. Cross-Modal Retrieval with Heterogeneous Graph Embedding. In Proceedings of the 30th ACM International Conference on Multimedia (MM’22), pages 3291-3300, Lisbon, Portugal. https://doi.org/10.1145/3503161.3548195
J. Yang, R. Li, W. Peng. 2022. ASR Error Correction with Constrained Decoding on Operation Prediction. In Proceedings of Interspeech 2022, pages 3874-3878, Incheon, Korea.
W. Wang, W. Peng, C. Huang, H. Wang. 2022. Positively Transitioned Sentiment Dialogue Corpus for Developing Emotion-affective Open-domain Chatbots. arXive preprint arXiv:2208.04565, https://arxiv.org/abs/2208.04565.
W. Wang, W. Peng, M. Zhang, Q. Liu. 2021. Neural Machine Translation with Heterogeneous Topic Knowledge Embeddings. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (EMNLP 2021), pages 3197-3202, Punta Cana, Dominican Republic. Association for Computational Linguistics.
W. Wang, W. Peng, X. Meng, Q. Liu. 2021. Huawei AARC’s submissions to the WMT21 Biomedical Translation Task: Domain Adaption from a Practical Perspective. In Proceedings of the Sixth Conference on Machine Translation (WMT21): Shared Task Papers, pages 868-873. Association for Computational Linguistics.
Q. Zhu, Y. Gu, L. Luo, B. Li, C. Li, W. Peng, X. Zhu, M. Huang. 2021. When does Further Pre-training MLM Help? An Empirical Study on Task-Oriented Dialog Pre-training. In Proceedings of the Second Workshop on Insights from Negative Results in NLP (collocated EMNLP), pages 54-61, Punta Cana, Dominican Republic. Association for Computational Linguistics, Best Paper Award.
T. Han, X. Liu, R. Takanabu, Y. Lian, C. Huang, D. Wan, W. Peng, M. Huang. 2021. MultiWOZ 2.3: A Multi domain Task-Oriented Dialogue Dataset Enhanced with Annotation Corrections and Co-Reference Annotation. In Proceedings of CCF International Conference on Natural Language Processing and Chinese Computing (NLPCC 2021), pages 206-218, Qingdao, China. Springer.
M. Huang, W. Peng, D. Wang. 2021. TPRM: A Topic-based Personalized Ranking Model for Web Search. arXiv preprint arXiv:2108.06014, https://arxiv.org/abs/2108.06014.
W. Wang, X. Cai, C. Huang, H. Wang, H. Lu, X. Liu, W. Peng. 2021. Emily: Developing an Emotion-affective Open-Domain Chatbot with Knowledge Graph-based Persona. arXiv preprint arXiv:2109.08875, https://arxiv.org/abs/2109.08875.
T. Han, C. Huang, W. Peng. 2021. Coreference Augmentation for Multi-Domain Task-Oriented Dialogue State Tracking. In Proceedings of Interspeech 2021, pages 1259-1263. doi: 10.21437/Interspeech.2021-1463.
L. Bai, H. Lu, H. Hu, K. Smith, K. Harripersaud, V. Lipkova, Y. Wen, X. Guo, W. Peng, C. Liu, M. Shen, A. Shen, L. Zhang, Evaluation of Work Resumption Strategies after COVID-19 Reopening in the Chinese City of Shenzhen: A mathematical modeling study, Public Health, Volume 193, pages 17-22. ELSEVIER.
J. Liu, R. Takanobu, J. Wen, D. Wan, H. Li, W. Nie, C. Li, W. Peng, M. Huang. 2021. Robustness Testing of Language Understanding in Dialog Systems. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing(ACL-IJCNLP 2021, Long Paper), pages 2467–2480, Online. Association for Computational Linguistics.
S. Gao, R. Takanobu, W. Peng, Q. Liu, M. Huang. 2021. HyKnow: End-to-End Task-Oriented Dialog Modeling with Hybrid Knowledge Management. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing(ACL-IJCNLP 2021, Findings), pages 1591–1602, Online. Association for Computational Linguistics.
X. Liu, W. Xue, Q. Su, W. Nie, W. Peng. 2021. metaCAT: A Metadata-based Task-oriented Chatbot Annotation Tool. In Proceedings of the 1st Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 10th International Joint Conference on Natural Language Processing (AACL 2021), pages 20-25, Suzhou, China. Association for Computational Linguistics.
H. Açarçiçek, T. Çolakoğlu, P.E. Aktan, C.H. Huang, W. Peng. 2020. Filtering Noisy Parallel Corpus using Transformers with Proxy Task Learning. In Proceedings of the Fifth Conference on Machine Translation(WMT20): Shared Task Papers, pages 940-946, Online. Association for Computational Linguistics.
W. Peng, J. Liu, M. Wang, L. Li, X. Meng, H. Yang, Q. Liu. 2020. Huawei’s Submissions to the WMT20 Biomedical Translation Task. In Proceedings of the Fifth Conference on Machine Translation (WMT20): Shared Task Papers, pages 857-861, Online. Association for Computational Linguistics.
X. Shang, W. Peng, J. Wu, M. He, L. Zhang, Leading determinants for multimorbidity in middle-aged Australian men and women: A nine-year follow-up cohort study, Preventive Medicine , Volume 141, 2020, 106260, https://doi.org/10.1016/j.ypmed.2020.106260.
X. Shang, A.M. Hodge, W. Peng, M. He, L. Zhang, Are leading risk factors for cancer and mental disorders multimorbidity shared by these two individual conditions in community-dwelling middle-aged adults?, Cancers, Volume 12, 2020, 1700, https://doi.org/10.3390/cancers12061700.
X. Shang, W. Peng, E. Hill, C. Szoeke, M. He, L. Zhang, Incidence, progression, and patterns of multimorbidity in community-dwelling middle-aged men and women, Frontiers in Public Health, Volume 8, 2020, 404, doi: 10.3389/fpubh.2020.00404.
W. Peng, C.H. Huang, T. Li, Y. Chen, Q. Liu. 2020. Dictionary-based Data Augmentation for Cross-domain Neural Machine Translation. arXiv preprint arXiv:2004.02577, https://arxiv.org/abs/2004.02577.
C.M. Lee, J. Liu, W. Peng. 2020. Applying Cyclical Learning Rate to Neural Machine Translation. arXive preprint arXiv:2004.02401, https://arxiv.org/abs/2004.02401.
W. Peng, J. Liu, L. Li, Q. Liu. 2019. Huawei’s NMT System for the WMT 2019 Biomedical Translation Task. In Proceedings of the Fourth Conference on Machine Translation: Shared Task Papers, pages 164-168, Italy, Florence. Association for Computational Linguistics.
Zhang L, Shang X, Sreedharan S, Yan X, Liu J, Keel S, Wu J, Peng W, He M, Predicting the Development of Type 2 Diabetes in a Large Australian Cohort Using Machine Learning Techniques:Longitudinal Survey Study, JMIR Med Inform 2020;8(7):e16850, URL: https://medinform.jmir.org/2020/7/e16850, DOI: 10.2196/16850.
Peng W., Adikari A, Alahakoon D, Gero J., Discovering the influence of sarcasm in social media responses. WIREs Data Mining Knowl Discov. 2019; 9:e1331. https://doi.org/10.1002/widm.1331
Shang, X., Peng, W., Hill, E., Szoeke, C., M. He, Zhang, L., Incidence of Medication-treated Depression and Anxiety associated with Long-term Cancer, Cardiovascular Disease, Diabetes and Osteoarthritis in Community Dwelling Women and Men, EClinicalMedicine – The Lancet, Volume 15, 2019, 23-32, ELSEVIER, https://doi.org/10.1016/j.eclinm.2019.08.010.
S. Nguyen, W. Peng, P. Sokolowski, D. Alahakoon, X. Yu, Optimizing rooftop photovoltaic distributed generation with battery storage for peer-to-peer energy trading, Applied Energy, Volume 228, 2018, pages 2567-2580, ELSEVIER. https://doi.org/10.1016/j.apenergy.2018.07.042.
Sultana, N., Chilamkurti, N., Peng, W.，Alhadad, R. Survey on SDN based network intrusion detection system using machine learning approaches. Peer-to-Peer Netw. Appl. 12, 493–501 (2019). https://doi.org/10.1007/s12083-017-0630-0
P. Sokolowski, W. Peng, R. Patel and X. Yu, “Roles of policy settings in distributed generation with battery storage,” IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society, Beijing, China, 2017, pp. 4802-4807, doi: 10.1109/IECON.2017.8216828.
W. Peng, D. Alahakoon and X. Li (eds). 2017. AI 2017: Advances in Artificial Intelligence, Springer, ISBN 978-3 319-63003-8.
W. Peng, P. Sokolowski, R. Patel, X. Yu and D. Alahakoon, “A multi-agent simulation framework for distributed generation with battery storage,” 2017 IEEE 26th International Symposium on Industrial Electronics (ISIE), Edinburgh, UK, 2017, pp. 37-42, doi: 10.1109/ISIE.2017.8001220.
W. Peng and J.S. Gero. 2015. Situated concept formation from interactions: An implementable constructive memory model. In Proceedings of the Third Annual Conference on Advances in Cognitive Systems, ACS-2015 (Article 10), pages 1-17, Atlanta, Georgia.
Q. Wang, W. Peng and X. Yu, “Building an explanation generation mechanism in probabilistic knowledge-based systems,” 2010 8th IEEE International Conference on Industrial Informatics, Osaka, Japan, 2010, pp. 229-233, doi: 10.1109/INDIN.2010.5549426.
Qingmai Wang, Wei Peng and X. Yu, “Ontology based geometry recognition for STEP,” 2010 IEEE International Symposium on Industrial Electronics, Bari, Italy, 2010, pp. 1686-1691, doi: 10.1109/ISIE.2010.5637530.
J.S. Gero and W. Peng, Understanding the behaviors of a constructive memory agent: A markov chain analysis, Knowledge-Based Systems, Volume 22, Issue 8, 2009, pages 610-621, https://doi.org/10.1016/j.knosys.2009.05.006.
W. Peng, Q. Wang, B. Wang and X. Yu, “Putting Simple Hierarchy into Ant Foraging: Cluster-based Soft-bots,” 2009 Third International Conference on Network and System Security, Gold Coast, QLD, Australia, 2009, pp. 484-488, doi: 10.1109/NSS.2009.89.
D. Smith and W. Peng, “Machine learning approaches for soil classification in a multi-agent deficit irrigation control system,” 2009 IEEE International Conference on Industrial Technology, Churchill, VIC, Australia, 2009, pp. 1-6, doi: 10.1109/ICIT.2009.4939641.
G. James, W. Peng and K. Deng, Managing Household Wind-Energy Generation, IEEE Intelligent Systems, vol. 23, no. 5, pp. 9-12, Sept.-Oct. 2008, doi: 10.1109/MIS.2008.87.
Peng, W., Gero, J.S. (2009). Concept formation in scientific knowledge discovery from a constructivist view. In: Gaber, M. (eds) Scientific Data Mining and Knowledge Discovery. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02788-8_5.
W. Peng and J.S. Gero. 2009. A Design Interaction Tool that Adapts, VDM Verlag.
M. Holloway-Phillips, W. Peng, D. Smith and A. Terhorst, Adaptive scheduling in deficit irrigation – a model-data synthesis approach, WIT Transactions on Ecology and the Environment, Volume 112, pages 187-200, WIT Press. DOI: 10.2495/SI080191
J. McCulloch, P. McCarthy, S. M. Guru, W. Peng, D. Hugo, and A. Terhorst. 2008. Wireless sensor network deployment for water use efficiency in irrigation. In Proceedings of the workshop on Real-world wireless sensor networks (REALWSN ‘08). Association for Computing Machinery, New York, NY, USA, 46–50. https://doi.org/10.1145/1435473.1435487.
W. Peng and J.S. Gero. 2007. Learning First-person Knowledge through Interactions: Towards effective design tools. In Proceedings of 16th International Conference on Engineering Design, pages 47:1-12, Ecole Centrale de Paris.
W. Peng and J.S. Gero. 2007. Computer-aided Design Tools that Adapt. In Proceedings of 12th International Conference on Computer-aided Architectural Design, pages 417-430. Springer, 2007.
W. Peng and J.S. Gero. 2006. Concept formation in a design optimization tool. In J van Leeuwen and H Timmermans (eds), Innovation in Design Decision Support Systems in Architecture and Urban Planning, pages 292-308. Springer. https://doi.org/10.1007/978-1-4020-5060-2_19.
W. Peng and J.S. Gero. 2006. Using a Constructive Interactive Activation and Competition Neural Network to Construct a Situated Agent’s Experience. In PRICAI 2006: Trends in Artificial Intelligence, Y. Qiang and G. Webb, Eds., pages 21-30. Springer.
W. Peng and J.S. Gero. 2006. Towards a ‘Loosely-wired’ Design Optimization Tool. In Clients Driving Construction Innovation: Moving Ideas into Practice, K. Brown, K. Hampson and P. Brandon, Eds., pages 143-148, Brisbane, Australia (Best Paper Award).
J.S. Gero and W. Peng. 2005. Assisting interactions in a dynamic design process: A new role for an adaptive design tool. In Clients Driving Construction Innovation: Mapping the Terrain, K. Hampson, K. Brown and P. Scuderi, Eds., pages 201-210. Pearson.
R. Reffat, J.S. Gero and W. Peng. 2004. Using Data Mining on Building Maintenance during the Building Life Cycle. In Proceedings of the 38th Australian & New Zealand Architectural Science Association (ANZASCA) Conference, pages 91-97, Tasmania, Australia.
J.S. Gero and W. Peng. 2004. A Situated Agent-based Design Assistant. In Proceedings of CAADRIA04, pages 145-157, Seoul, Korea.