Da-Cheng Juan
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
43
Venues
20
Active years
2007–2025
Best venue rank
A*
Where they publish
Papers
43 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | EMNLP | Neuron-Level Differentiation of Memorization and Generalization in Large Language Models. | Ko-Wei Huang, Yi-Fu Fu, Ching-Yu Tsai, Yu-Chieh Tu, Tzu-ling Cheng, Cheng-Yu Lin, Yi-Ting Yang, Heng-Yi Liu, Keng-Te Liao, Da-Cheng Juan, Shou-De Lin |
| 2025 | ICLR | Sufficient Context: A New Lens on Retrieval Augmented Generation Systems. | Hailey Joren, Jianyi Zhang, Chun-Sung Ferng, Da-Cheng Juan, Ankur Taly, Cyrus Rashtchian |
| 2025 | NAACL | DreamSync: Aligning Text-to-Image Generation with Image Understanding Feedback. | Jiao Sun, Deqing Fu, Yushi Hu, Su Wang, Royi Rassin, Da-Cheng Juan, Dana Alon, Charles Herrmann, Sjoerd van Steenkiste, Ranjay Krishna, Cyrus Rashtchian |
| 2023 | ACL | RARR: Researching and Revising What Language Models Say, Using Language Models. | Luyu Gao, Zhuyun Dai, Panupong Pasupat, Anthony Chen, Arun Tejasvi Chaganty, Yicheng Fan, Vincent Y. Zhao, Ni Lao, Hongrae Lee, Da-Cheng Juan, Kelvin Guu |
| 2021 | ACL | "Does it Matter When I Think You Are Lying?" Improving Deception Detection by Integrating Interlocutor's Judgements in Conversations. | Huang-Cheng Chou, Woan-Shiuan Chien, Da-Cheng Juan, Chi-Chun Lee |
| 2021 | ASPDAC | Uncertainty Modeling of Emerging Device based Computing-in-Memory Neural Accelerators with Application to Neural Architecture Search. | Zheyu Yan, Da-Cheng Juan, Xiaobo Sharon Hu, Yiyu Shi |
| 2021 | CVPR | Adversarial Robustness Across Representation Spaces. | Pranjal Awasthi, George Yu, Chun-Sung Ferng, Andrew Tomkins, Da-Cheng Juan |
| 2021 | ICLR | HyperGrid Transformers: Towards A Single Model for Multiple Tasks. | Yi Tay, Zhe Zhao, Dara Bahri, Donald Metzler, Da-Cheng Juan |
| 2021 | ICML | OmniNet: Omnidirectional Representations from Transformers. | Yi Tay, Mostafa Dehghani, Vamsi Aribandi, Jai Prakash Gupta, Philip Pham, Zhen Qin, Dara Bahri, Da-Cheng Juan, Donald Metzler |
| 2021 | ICML | Synthesizer: Rethinking Self-Attention for Transformer Models. | Yi Tay, Dara Bahri, Donald Metzler, Da-Cheng Juan, Zhe Zhao, Che Zheng |
| 2021 | WSDM | Neural Structured Learning: Training Neural Networks with Structured Signals. | Arjun Gopalan, Da-Cheng Juan, Cesar Ilharco Magalhaes, Chun-Sung Ferng, Allan Heydon, Chun-Ta Lu, Philip Pham, George Yu, Yicheng Fan, Yueqi Wang |
| 2020 | AAAI | InstaNAS: Instance-Aware Neural Architecture Search. | An-Chieh Cheng, Chieh Hubert Lin, Da-Cheng Juan, Wei Wei, Min Sun |
| 2020 | ACL | Low-Dimensional Hyperbolic Knowledge Graph Embeddings. | Ines Chami, Adva Wolf, Da-Cheng Juan, Frederic Sala, Sujith Ravi, Christopher R |
| 2020 | ECCV | Remix: Rebalanced Mixup. | Hsin-Ping Chou, Shih-Chieh Chang, Jia-Yu Pan, Wei Wei, Da-Cheng Juan |
| 2020 | EMNLP | AirConcierge: Generating Task-Oriented Dialogue via Efficient Large-Scale Knowledge Retrieval. | Chieh-Yang Chen, Pei-Hsin Wang, Shih-Chieh Chang, Da-Cheng Juan, Wei Wei, Jia-Yu Pan |
| 2020 | EMNLP | Question Answering with Long Multiple-Span Answers. | Ming Zhu, Aman Ahuja, Da-Cheng Juan, Wei Wei, Chandan K. Reddy |
| 2020 | ICML | Sparse Sinkhorn Attention. | Yi Tay, Dara Bahri, Liu Yang, Donald Metzler, Da-Cheng Juan |
| 2020 | KDD | Neural Structured Learning: Training Neural Networks with Structured Signals. | Arjun Gopalan, Da-Cheng Juan, Cesar Ilharco Magalhaes, Chun-Sung Ferng, Allan Heydon, Chun-Ta Lu, Philip Pham, George Yu |
| 2020 | WSDM | Ultra Fine-Grained Image Semantic Embedding. | Da-Cheng Juan, Chun-Ta Lu, Zhen Li, Futang Peng, Aleksei Timofeev, Yi-Ting Chen, Yaxi Gao, Tom Duerig, Andrew Tomkins, Sujith Ravi |
| 2019 | ACL | A2N: Attending to Neighbors for Knowledge Graph Inference. | Trapit Bansal, Da-Cheng Juan, Sujith Ravi, Andrew McCallum |
| 2019 | ACL | On the Robustness of Self-Attentive Models. | Yu-Lun Hsieh, Minhao Cheng, Da-Cheng Juan, Wei Wei, Wen-Lian Hsu, Cho-Jui Hsieh |
| 2019 | ICCV | Improving Adversarial Robustness via Guided Complement Entropy. | Hao-Yun Chen, Jhao-Hong Liang, Shih-Chieh Chang, Jia-Yu Pan, Yu-Ting Chen, Wei Wei, Da-Cheng Juan |
| 2019 | ICCV | COCO-GAN: Generation by Parts via Conditional Coordinating. | Chieh Hubert Lin, Chia-Che Chang, Yu-Sheng Chen, Da-Cheng Juan, Wei Wei, Hwann-Tzong Chen |
| 2019 | ICLR | Complement Objective Training. | Hao-Yun Chen, Pei-Hsin Wang, Chun-Hao Liu, Shih-Chieh Chang, Jia-Yu Pan, Yu-Ting Chen, Wei Wei, Da-Cheng Juan |
| 2019 | PAKDD | Hierarchical LSTM: Modeling Temporal Dynamics and Taxonomy in Location-Based Mobile Check-Ins. | Chun-Hao Liu, Da-Cheng Juan, Xuan-An Tseng, Wei Wei, Yu-Ting Chen, Jia-Yu Pan, Shih-Chieh Chang |
| 2018 | DATE | HyperPower: Power- and memory-constrained hyper-parameter optimization for neural networks. | Dimitrios Stamoulis, Ermao Cai, Da-Cheng Juan, Diana Marculescu |
| 2018 | ECCV | Escaping from Collapsing Modes in a Constrained Space. | Chia-Che Chang, Chieh Hubert Lin, Che-Rung Lee, Da-Cheng Juan, Wei Wei, Hwann-Tzong Chen |
| 2018 | ECCV | DPP-Net: Device-Aware Progressive Search for Pareto-Optimal Neural Architectures. | Jin-Dong Dong, An-Chieh Cheng, Da-Cheng Juan, Wei Wei, Min Sun |
| 2018 | ICCAD | Searching toward pareto-optimal device-aware neural architectures. | An-Chieh Cheng, Jin-Dong Dong, Chi-Hung Hsu, Shu-Huan Chang, Min Sun, Shih-Chieh Chang, Jia-Yu Pan, Yu-Ting Chen, Wei Wei, Da-Cheng Juan |
| 2018 | ICLR | PPP-Net: Platform-aware Progressive Search for Pareto-optimal Neural Architectures. | Jin-Dong Dong, An-Chieh Cheng, Da-Cheng Juan, Wei Wei, Min Sun |
| 2017 | ACML | \emphNeuralPower: Predict and Deploy Energy-Efficient Convolutional Neural Networks. | Ermao Cai, Da-Cheng Juan, Dimitrios Stamoulis, Diana Marculescu |
| 2017 | DSAA | M3A: Model, MetaModel and Anomaly Detection for Inter-arrivals of Web Searches and Postings. | Da-Cheng Juan, Neil Shah, Mingyu Tang, Zhiliang Qian, Diana Marculescu, Christos Faloutsos |
| 2015 | ICCAD | Effective CAD Research in the Sea of Papers. | Jinglan Liu, Da-Cheng Juan, Yiyu Shi |
| 2014 | ASPDAC | A comprehensive and accurate latency model for Network-on-Chip performance analysis. | Zhiliang Qian, Da-Cheng Juan, Paul Bogdan, Chi-Ying Tsui, Diana Marculescu, Radu Marculescu |
| 2014 | PAKDD | Beyond Poisson: Modeling Inter-Arrival Time of Requests in a Datacenter. | Da-Cheng Juan, Lei Li, Huan-Kai Peng, Diana Marculescu, Christos Faloutsos |
| 2013 | DATE | SVR-NoC: a performance analysis tool for network-on-chips using learning-based support vector regression model. | Zhiliang Qian, Da-Cheng Juan, Paul Bogdan, Chi-Ying Tsui, Diana Marculescu, Radu Marculescu |
| 2013 | ISCAS | Impact of manufacturing process variations on performance and thermal characteristics of 3D ICs: Emerging challenges and new solutions. | Da-Cheng Juan, Siddharth Garg, Diana Marculescu |
| 2012 | ASPDAC | A learning-based autoregressive model for fast transient thermal analysis of chip-multiprocessors. | Da-Cheng Juan, Huapeng Zhou, Diana Marculescu, Xin Li |
| 2012 | DATE | Statistical thermal modeling and optimization considering leakage power variations. | Da-Cheng Juan, Yi-Lin Chuang, Diana Marculescu, Yao-Wen Chang |
| 2012 | ISLPED | Power-aware performance increase via core/uncore reinforcement control for chip-multiprocessors. | Da-Cheng Juan, Diana Marculescu |
| 2011 | DATE | Statistical thermal evaluation and mitigation techniques for 3D Chip-Multiprocessors in the presence of process variations. | Da-Cheng Juan, Siddharth Garg, Diana Marculescu |
| 2007 | DAC | Fine-Grained Sleep Transistor Sizing Algorithm for Leakage Power Minimization. | De-Shiuan Chiou, Da-Cheng Juan, Yu-Ting Chen, Shih-Chieh Chang |
| 2007 | ICCAD | An efficient wake-up schedule during power mode transition considering spurious glitches phenomenon. | Yu-Ting Chen, Da-Cheng Juan, Ming-Chao Lee, Shih-Chieh Chang |