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Books and Theses
- 2015
[b1]Tomas Pfister:
Advancing human pose and gesture recognition. University of Oxford, UK, 2015
Journal Articles
- 2024
- [j15]Jiefeng Chen, Jinsung Yoon, Sayna Ebrahimi, Sercan Ö. Arik, Somesh Jha, Tomas Pfister:
ASPEST: Bridging the Gap Between Active Learning and Selective Prediction. Trans. Mach. Learn. Res. 2024 (2024) - 2023
- [j14]Jinsung Yoon
, Michel J. Mizrahi, Nahid Farhady Ghalaty, Thomas Jarvinen, Ashwin S. Ravi, Peter Brune, Fanyu Kong, Dave Anderson, George Lee, Arie Meir, Farhana Bandukwala, Elli Kanal, Sercan Ö. Arik, Tomas Pfister:
EHR-Safe: generating high-fidelity and privacy-preserving synthetic electronic health records. npj Digit. Medicine 6 (2023) - [j13]Si-An Chen, Chun-Liang Li, Sercan Ö. Arik, Nathanael C. Yoder, Tomas Pfister:
TSMixer: An All-MLP Architecture for Time Series Forecast-ing. Trans. Mach. Learn. Res. 2023 (2023) - [j12]Sayna Ebrahimi, Sercan Ö. Arik, Tomas Pfister:
Test-Time Adaptation for Visual Document Understanding. Trans. Mach. Learn. Res. 2023 (2023) - [j11]Yunhao Ge, Sercan Ö. Arik, Jinsung Yoon, Ao Xu, Laurent Itti, Tomas Pfister:
Invariant Structure Learning for Better Generalization and Causal Explainability. Trans. Mach. Learn. Res. 2023 (2023) - [j10]Aya Abdelsalam Ismail, Sercan Ö. Arik, Jinsung Yoon, Ankur Taly, Soheil Feizi, Tomas Pfister:
Interpretable Mixture of Experts. Trans. Mach. Learn. Res. 2023 (2023) - [j9]Jinsung Yoon, Kihyuk Sohn, Chun-Liang Li, Sercan Ö. Arik, Tomas Pfister:
SPADE: Semi-supervised Anomaly Detection under Distribution Mismatch. Trans. Mach. Learn. Res. 2023 (2023) - 2022
- [j8]Thomas C. Tsai, Sercan Ö. Arik, Benjamin H. Jacobson, Jinsung Yoon, Nate Yoder, Dario Sava, Margaret Mitchell, Garth Graham, Tomas Pfister:
Algorithmic fairness in pandemic forecasting: lessons from COVID-19. npj Digit. Medicine 5 (2022) - [j7]Jinsung Yoon, Sercan Ö. Arik, Tomas Pfister:
LIMIS: Locally Interpretable Modeling using Instance-wise Subsampling. Trans. Mach. Learn. Res. 2022 (2022) - [j6]Jinsung Yoon, Kihyuk Sohn, Chun-Liang Li, Sercan Ö. Arik, Chen-Yu Lee, Tomas Pfister:
Self-supervise, Refine, Repeat: Improving Unsupervised Anomaly Detection. Trans. Mach. Learn. Res. 2022 (2022) - 2021
- [j5]Sercan Ö. Arik, Joel Shor, Rajarishi Sinha, Jinsung Yoon, Joseph R. Ledsam, Long T. Le, Michael W. Dusenberry, Nathanael C. Yoder, Kris Popendorf, Arkady Epshteyn, Johan Euphrosine, Elli Kanal, Isaac Jones, Chun-Liang Li, Beth Luan, Joe Mckenna, Vikas Menon, Shashank Singh, Mimi Sun, Ashwin Sura Ravi, Leyou Zhang, Dario Sava, Kane Cunningham, Hiroki Kayama, Thomas C. Tsai, Daisuke Yoneoka, Shuhei Nomura, Hiroaki Miyata, Tomas Pfister:
A prospective evaluation of AI-augmented epidemiology to forecast COVID-19 in the USA and Japan. npj Digit. Medicine 4 (2021) - 2020
- [j4]Sercan Ömer Arik, Tomas Pfister:
ProtoAttend: Attention-Based Prototypical Learning. J. Mach. Learn. Res. 21: 210:1-210:35 (2020) - 2018
- [j3]Xiaobai Li, Xiaopeng Hong, Antti Moilanen, Xiaohua Huang, Tomas Pfister, Guoying Zhao, Matti Pietikäinen:
Towards Reading Hidden Emotions: A Comparative Study of Spontaneous Micro-Expression Spotting and Recognition Methods. IEEE Trans. Affect. Comput. 9(4): 563-577 (2018) - 2014
- [j2]James Charles, Tomas Pfister, Mark Everingham, Andrew Zisserman:
Automatic and Efficient Human Pose Estimation for Sign Language Videos. Int. J. Comput. Vis. 110(1): 70-90 (2014) - 2011
- [j1]Tomas Pfister, Peter Robinson:
Real-Time Recognition of Affective States from Nonverbal Features of Speech and Its Application for Public Speaking Skill Analysis. IEEE Trans. Affect. Comput. 2(2): 66-78 (2011)
Conference and Workshop Papers
- 2024
- [c60]Jinsung Yoon, Yanfei Chen, Sercan Ö. Arik, Tomas Pfister:
Search-Adaptor: Embedding Customization for Information Retrieval. ACL (1) 2024: 12230-12247 - [c59]I-Hung Hsu, Zifeng Wang, Long T. Le, Lesly Miculicich, Nanyun Peng, Chen-Yu Lee, Tomas Pfister:
CaLM: Contrasting Large and Small Language Models to Verify Grounded Generation. ACL (Findings) 2024: 12782-12803 - [c58]James Enouen, Hootan Nakhost, Sayna Ebrahimi, Sercan Ö. Arik, Yan Liu, Tomas Pfister:
TextGenSHAP: Scalable Post-Hoc Explanations in Text Generation with Long Documents. ACL (Findings) 2024: 13984-14011 - [c57]Cheng-Yu Hsieh, Yung-Sung Chuang, Chun-Liang Li, Zifeng Wang, Long T. Le, Abhishek Kumar, James R. Glass, Alexander Ratner, Chen-Yu Lee, Ranjay Krishna, Tomas Pfister:
Found in the middle: Calibrating Positional Attention Bias Improves Long Context Utilization. ACL (Findings) 2024: 14982-14995 - [c56]Zilong Wang, Hao Zhang, Chun-Liang Li, Julian Martin Eisenschlos, Vincent Perot, Zifeng Wang, Lesly Miculicich, Yasuhisa Fujii, Jingbo Shang, Chen-Yu Lee, Tomas Pfister:
Chain-of-Table: Evolving Tables in the Reasoning Chain for Table Understanding. ICLR 2024 - [c55]Defu Cao, Furong Jia, Sercan Ö. Arik, Tomas Pfister, Yixiang Zheng, Wen Ye, Yan Liu:
TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting. ICLR 2024 - [c54]Sungwon Han, Jinsung Yoon, Sercan Ö. Arik, Tomas Pfister:
Large Language Models Can Automatically Engineer Features for Few-Shot Tabular Learning. ICML 2024 - [c53]Zifeng Wang, Chun-Liang Li, Vincent Perot, Long T. Le, Jin Miao, Zizhao Zhang, Chen-Yu Lee, Tomas Pfister:
CodecLM: Aligning Language Models with Tailored Synthetic Data. NAACL-HLT (Findings) 2024: 3712-3729 - [c52]Xi Ye, Ruoxi Sun, Sercan Ö. Arik, Tomas Pfister:
Effective Large Language Model Adaptation for Improved Grounding and Citation Generation. NAACL-HLT 2024: 6237-6251 - 2023
- [c51]Ruoxi Sun, Chun-Liang Li, Sercan Ö. Arik, Michael W. Dusenberry, Chen-Yu Lee, Tomas Pfister:
Neural Spline Search for Quantile Probabilistic Modeling. AAAI 2023: 9927-9934 - [c50]Xingchen Wan, Ruoxi Sun, Hanjun Dai, Sercan Ö. Arik, Tomas Pfister:
Better Zero-Shot Reasoning with Self-Adaptive Prompting. ACL (Findings) 2023: 3493-3514 - [c49]Zifeng Wang, Zizhao Zhang, Jacob Devlin, Chen-Yu Lee, Guolong Su, Hao Zhang, Jennifer G. Dy, Vincent Perot, Tomas Pfister:
QueryForm: A Simple Zero-shot Form Entity Query Framework. ACL (Findings) 2023: 4146-4159 - [c48]Cheng-Yu Hsieh, Chun-Liang Li, Chih-Kuan Yeh, Hootan Nakhost, Yasuhisa Fujii, Alex Ratner, Ranjay Krishna, Chen-Yu Lee, Tomas Pfister:
Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model Sizes. ACL (Findings) 2023: 8003-8017 - [c47]Chen-Yu Lee, Chun-Liang Li, Hao Zhang, Timothy Dozat, Vincent Perot, Guolong Su, Xiang Zhang, Kihyuk Sohn, Nikolay Glushnev, Renshen Wang, Joshua Ainslie, Shangbang Long, Siyang Qin, Yasuhisa Fujii, Nan Hua, Tomas Pfister:
FormNetV2: Multimodal Graph Contrastive Learning for Form Document Information Extraction. ACL (1) 2023: 9011-9026 - [c46]Kuniaki Saito, Kihyuk Sohn, Xiang Zhang, Chun-Liang Li, Chen-Yu Lee, Kate Saenko, Tomas Pfister:
Prefix Conditioning Unifies Language and Label Supervision. CVPR 2023: 2861-2870 - [c45]Kuniaki Saito, Kihyuk Sohn, Xiang Zhang, Chun-Liang Li, Chen-Yu Lee, Kate Saenko, Tomas Pfister:
Pic2Word: Mapping Pictures to Words for Zero-shot Composed Image Retrieval. CVPR 2023: 19305-19314 - [c44]Ruoxi Sun, Sercan Ö. Arik, Rajarishi Sinha, Hootan Nakhost, Hanjun Dai, Pengcheng Yin, Tomas Pfister:
SQLPrompt: In-Context Text-to-SQL with Minimal Labeled Data. EMNLP (Findings) 2023: 542-550 - [c43]Jiefeng Chen, Jinsung Yoon, Sayna Ebrahimi, Sercan Ö. Arik, Tomas Pfister, Somesh Jha:
Adaptation with Self-Evaluation to Improve Selective Prediction in LLMs. EMNLP (Findings) 2023: 5190-5213 - [c42]Xingchen Wan, Ruoxi Sun, Hootan Nakhost, Hanjun Dai, Julian Eisenschlos, Sercan Ö. Arik, Tomas Pfister:
Universal Self-Adaptive Prompting. EMNLP 2023: 7437-7462 - [c41]Chun-Hao Chang, Jinsung Yoon, Sercan Ö. Arik, Madeleine Udell, Tomas Pfister:
Data-Efficient and Interpretable Tabular Anomaly Detection. KDD 2023: 190-201 - [c40]Kihyuk Sohn, Jinsung Yoon, Chun-Liang Li, Chen-Yu Lee, Tomas Pfister:
Anomaly Clustering: Grouping Images into Coherent Clusters of Anomaly Types. WACV 2023: 5468-5479 - [c39]Justin Lazarow, Kihyuk Sohn, Chen-Yu Lee, Chun-Liang Li, Zizhao Zhang, Tomas Pfister:
Unifying Distribution Alignment as a Loss for Imbalanced Semi-supervised Learning. WACV 2023: 5633-5642 - 2022
- [c38]Kunpeng Li, Zizhao Zhang, Guanhang Wu, Xuehan Xiong, Chen-Yu Lee, Zhichao Lu, Yun Fu, Tomas Pfister:
Learning from Weakly-Labeled Web Videos via Exploring Sub-concepts. AAAI 2022: 1341-1349 - [c37]Zizhao Zhang, Han Zhang, Long Zhao, Ting Chen, Sercan Ö. Arik, Tomas Pfister:
Nested Hierarchical Transformer: Towards Accurate, Data-Efficient and Interpretable Visual Understanding. AAAI 2022: 3417-3425 - [c36]Chen-Yu Lee, Chun-Liang Li, Timothy Dozat, Vincent Perot, Guolong Su, Nan Hua, Joshua Ainslie, Renshen Wang, Yasuhisa Fujii, Tomas Pfister:
FormNet: Structural Encoding beyond Sequential Modeling in Form Document Information Extraction. ACL (1) 2022: 3735-3754 - [c35]Sana Tonekaboni, Chun-Liang Li, Sercan Ö. Arik, Anna Goldenberg, Tomas Pfister:
Decoupling Local and Global Representations of Time Series. AISTATS 2022: 8700-8714 - [c34]Zifeng Wang, Zizhao Zhang, Chen-Yu Lee, Han Zhang, Ruoxi Sun, Xiaoqi Ren, Guolong Su, Vincent Perot, Jennifer G. Dy, Tomas Pfister:
Learning to Prompt for Continual Learning. CVPR 2022: 139-149 - [c33]Yuliang Zou, Zizhao Zhang, Chun-Liang Li, Han Zhang, Tomas Pfister, Jia-Bin Huang:
Learning Instance-Specific Adaptation for Cross-Domain Segmentation. ECCV (33) 2022: 459-476 - [c32]Zifeng Wang, Zizhao Zhang, Sayna Ebrahimi, Ruoxi Sun, Han Zhang, Chen-Yu Lee, Xiaoqi Ren, Guolong Su, Vincent Perot, Jennifer G. Dy, Tomas Pfister:
DualPrompt: Complementary Prompting for Rehearsal-Free Continual Learning. ECCV (26) 2022: 631-648 - 2021
- [c31]Sercan Ö. Arik, Tomas Pfister:
TabNet: Attentive Interpretable Tabular Learning. AAAI 2021: 6679-6687 - [c30]Chen-Yu Lee, Chun-Liang Li, Chu Wang, Renshen Wang, Yasuhisa Fujii, Siyang Qin, Ashok C. Popat, Tomas Pfister:
ROPE: Reading Order Equivariant Positional Encoding for Graph-based Document Information Extraction. ACL/IJCNLP (2) 2021: 314-321 - [c29]Chun-Liang Li, Kihyuk Sohn, Jinsung Yoon, Tomas Pfister:
CutPaste: Self-Supervised Learning for Anomaly Detection and Localization. CVPR 2021: 9664-9674 - [c28]Zizhao Zhang, Tomas Pfister:
Learning Fast Sample Re-weighting Without Reward Data. ICCV 2021: 705-714 - [c27]Kihyuk Sohn, Chun-Liang Li, Jinsung Yoon, Minho Jin, Tomas Pfister:
Learning and Evaluating Representations for Deep One-Class Classification. ICLR 2021 - [c26]Yuliang Zou, Zizhao Zhang, Han Zhang, Chun-Liang Li, Xiao Bian, Jia-Bin Huang, Tomas Pfister:
PseudoSeg: Designing Pseudo Labels for Semantic Segmentation. ICLR 2021 - [c25]Sungyong Seo, Sercan Ö. Arik, Jinsung Yoon, Xiang Zhang, Kihyuk Sohn, Tomas Pfister:
Controlling Neural Networks with Rule Representations. NeurIPS 2021: 11196-11207 - 2020
- [c24]Zizhao Zhang, Han Zhang, Sercan Ömer Arik, Honglak Lee, Tomas Pfister:
Distilling Effective Supervision From Severe Label Noise. CVPR 2020: 9291-9300 - [c23]Linchao Zhu, Sercan Ömer Arik, Yi Yang, Tomas Pfister:
Learning to Transfer Learn: Reinforcement Learning-Based Selection for Adaptive Transfer Learning. ECCV (27) 2020: 342-358 - [c22]Mingfei Gao, Zizhao Zhang, Guo Yu, Sercan Ömer Arik, Larry S. Davis, Tomas Pfister:
Consistency-Based Semi-supervised Active Learning: Towards Minimizing Labeling Cost. ECCV (10) 2020: 510-526 - [c21]Chen Xing, Sercan Ömer Arik, Zizhao Zhang, Tomas Pfister:
Distance-Based Learning from Errors for Confidence Calibration. ICLR 2020 - [c20]Jinsung Yoon, Sercan Ömer Arik, Tomas Pfister:
Data Valuation using Reinforcement Learning. ICML 2020: 10842-10851 - [c19]Sercan Ömer Arik, Chun-Liang Li, Jinsung Yoon, Rajarishi Sinha, Arkady Epshteyn, Long T. Le, Vikas Menon, Shashank Singh, Leyou Zhang, Martin Nikoltchev, Yash Sonthalia, Hootan Nakhost, Elli Kanal, Tomas Pfister:
Interpretable Sequence Learning for Covid-19 Forecasting. NeurIPS 2020 - [c18]Yujia Xie, Hanjun Dai, Minshuo Chen, Bo Dai, Tuo Zhao, Hongyuan Zha, Wei Wei, Tomas Pfister:
Differentiable Top-k with Optimal Transport. NeurIPS 2020 - [c17]Chih-Kuan Yeh, Been Kim, Sercan Ömer Arik, Chun-Liang Li, Tomas Pfister, Pradeep Ravikumar:
On Completeness-aware Concept-Based Explanations in Deep Neural Networks. NeurIPS 2020 - 2019
- [c16]Donghoon Lee, Tomas Pfister, Ming-Hsuan Yang:
Inserting Videos Into Videos. CVPR 2019: 10061-10070 - [c15]Lanlan Liu, Michael Muelly, Jia Deng, Tomas Pfister, Li-Jia Li:
Generative Modeling for Small-Data Object Detection. ICCV 2019: 6072-6080 - [c14]Rui Zhang, Tomas Pfister, Jia Li:
Harmonic Unpaired Image-to-image Translation. ICLR (Poster) 2019 - 2017
- [c13]Ashish Shrivastava, Tomas Pfister, Oncel Tuzel, Joshua Susskind, Wenda Wang, Russell Webb:
Learning from Simulated and Unsupervised Images through Adversarial Training. CVPR 2017: 2242-2251 - 2016
- [c12]James Charles, Tomas Pfister, Derek R. Magee, David C. Hogg, Andrew Zisserman:
Personalizing Human Video Pose Estimation. CVPR 2016: 3063-3072 - 2015
- [c11]Tomas Pfister, James Charles, Andrew Zisserman:
Flowing ConvNets for Human Pose Estimation in Videos. ICCV 2015: 1913-1921 - 2014
- [c10]Tomas Pfister, Karen Simonyan, James Charles, Andrew Zisserman:
Deep Convolutional Neural Networks for Efficient Pose Estimation in Gesture Videos. ACCV (1) 2014: 538-552 - [c9]James Charles, Tomas Pfister, Derek R. Magee, David C. Hogg, Andrew Zisserman:
Upper Body Pose Estimation with Temporal Sequential Forests. BMVC 2014 - [c8]Tomas Pfister, James Charles, Andrew Zisserman:
Domain-Adaptive Discriminative One-Shot Learning of Gestures. ECCV (6) 2014: 814-829 - 2013
- [c7]James Charles, Tomas Pfister, Derek R. Magee, David C. Hogg, Andrew Zisserman:
Domain Adaptation for Upper Body Pose Tracking in Signed TV Broadcasts. BMVC 2013 - [c6]Tomas Pfister, James Charles, Andrew Zisserman:
Large-scale Learning of Sign Language by Watching TV (Using Co-occurrences). BMVC 2013 - [c5]Xiaobai Li, Tomas Pfister, Xiaohua Huang, Guoying Zhao, Matti Pietikäinen:
A Spontaneous Micro-expression Database: Inducement, collection and baseline. FG 2013: 1-6 - 2012
- [c4]Tomas Pfister, James Charles, Mark Everingham, Andrew Zisserman:
Automatic and Efficient Long Term Arm and Hand Tracking for Continuous Sign Language TV Broadcasts. BMVC 2012: 1-11 - 2011
- [c3]Tomas Pfister, Xiaobai Li, Guoying Zhao, Matti Pietikäinen:
Recognising spontaneous facial micro-expressions. ICCV 2011: 1449-1456 - [c2]Tomas Pfister, Xiaobai Li, Guoying Zhao, Matti Pietikäinen:
Differentiating spontaneous from posed facial expressions within a generic facial expression recognition framework. ICCV Workshops 2011: 868-875 - 2010
- [c1]Tomas Pfister, Peter Robinson:
Speech Emotion Classification and Public Speaking Skill Assessment. HBU 2010: 151-162
Informal and Other Publications
- 2024
- [i78]Zilong Wang, Hao Zhang, Chun-Liang Li, Julian Martin Eisenschlos, Vincent Perot, Zifeng Wang, Lesly Miculicich, Yasuhisa Fujii, Jingbo Shang, Chen-Yu Lee, Tomas Pfister:
Chain-of-Table: Evolving Tables in the Reasoning Chain for Table Understanding. CoRR abs/2401.04398 (2024) - [i77]Zifeng Wang, Chun-Liang Li, Vincent Perot, Long T. Le, Jin Miao, Zizhao Zhang, Chen-Yu Lee, Tomas Pfister:
CodecLM: Aligning Language Models with Tailored Synthetic Data. CoRR abs/2404.05875 (2024) - [i76]Sungwon Han, Jinsung Yoon, Sercan Ö. Arik, Tomas Pfister:
Large Language Models Can Automatically Engineer Features for Few-Shot Tabular Learning. CoRR abs/2404.09491 (2024) - [i75]Pritam Sarkar, Sayna Ebrahimi, Ali Etemad, Ahmad Beirami, Sercan Ö. Arik, Tomas Pfister:
Mitigating Object Hallucination via Data Augmented Contrastive Tuning. CoRR abs/2405.18654 (2024) - [i74]Maximillian Chen, Ruoxi Sun, Sercan Ö. Arik, Tomas Pfister:
Learning to Clarify: Multi-turn Conversations with Action-Based Contrastive Self-Training. CoRR abs/2406.00222 (2024) - [i73]Yusen Zhang, Ruoxi Sun, Yanfei Chen, Tomas Pfister, Rui Zhang, Sercan Ö. Arik:
Chain of Agents: Large Language Models Collaborating on Long-Context Tasks. CoRR abs/2406.02818 (2024) - [i72]Yihe Dong, Sercan Ö. Arik, Nathanael C. Yoder, Tomas Pfister:
Learned Feature Importance Scores for Automated Feature Engineering. CoRR abs/2406.04153 (2024) - [i71]I-Hung Hsu, Zifeng Wang, Long T. Le, Lesly Miculicich, Nanyun Peng, Chen-Yu Lee, Tomas Pfister:
CaLM: Contrasting Large and Small Language Models to Verify Grounded Generation. CoRR abs/2406.05365 (2024) - [i70]Cheng-Yu Hsieh, Yung-Sung Chuang, Chun-Liang Li, Zifeng Wang, Long T. Le, Abhishek Kumar, James R. Glass, Alexander Ratner, Chen-Yu Lee, Ranjay Krishna, Tomas Pfister:
Found in the Middle: Calibrating Positional Attention Bias Improves Long Context Utilization. CoRR abs/2406.16008 (2024) - [i69]Zilong Wang, Zifeng Wang, Long T. Le, Huaixiu Steven Zheng, Swaroop Mishra, Vincent Perot, Yuwei Zhang, Anush Mattapalli, Ankur Taly, Jingbo Shang, Chen-Yu Lee, Tomas Pfister:
Speculative RAG: Enhancing Retrieval Augmented Generation through Drafting. CoRR abs/2407.08223 (2024) - [i68]Jinsung Yoon, Rajarishi Sinha, Sercan Ö. Arik, Tomas Pfister:
Matryoshka-Adaptor: Unsupervised and Supervised Tuning for Smaller Embedding Dimensions. CoRR abs/2407.20243 (2024) - [i67]Yanfei Chen, Jinsung Yoon, Devendra Singh Sachan, Qingze Wang, Vincent Cohen-Addad, MohammadHossein Bateni, Chen-Yu Lee, Tomas Pfister:
Re-Invoke: Tool Invocation Rewriting for Zero-Shot Tool Retrieval. CoRR abs/2408.01875 (2024) - [i66]Sayna Ebrahimi, Sercan Ö. Arik, Tejas Nama, Tomas Pfister:
CROME: Cross-Modal Adapters for Efficient Multimodal LLM. CoRR abs/2408.06610 (2024) - [i65]Mohammadreza Pourreza, Ruoxi Sun, Hailong Li, Lesly Miculicich, Tomas Pfister, Sercan Ö. Arik:
SQL-GEN: Bridging the Dialect Gap for Text-to-SQL Via Synthetic Data And Model Merging. CoRR abs/2408.12733 (2024) - 2023
- [i64]Ruoxi Sun, Chun-Liang Li, Sercan Ö. Arik, Michael W. Dusenberry, Chen-Yu Lee, Tomas Pfister:
Neural Spline Search for Quantile Probabilistic Modeling. CoRR abs/2301.04857 (2023) - [i63]Kuniaki Saito, Kihyuk Sohn, Xiang Zhang, Chun-Liang Li, Chen-Yu Lee, Kate Saenko, Tomas Pfister:
Pic2Word: Mapping Pictures to Words for Zero-shot Composed Image Retrieval. CoRR abs/2302.03084 (2023) - [i62]Si-An Chen, Chun-Liang Li, Nate Yoder, Sercan Ö. Arik, Tomas Pfister:
TSMixer: An all-MLP Architecture for Time Series Forecasting. CoRR abs/2303.06053 (2023) - [i61]Jiefeng Chen, Jinsung Yoon, Sayna Ebrahimi, Sercan Ö. Arik, Somesh Jha, Tomas Pfister:
ASPEST: Bridging the Gap Between Active Learning and Selective Prediction. CoRR abs/2304.03870 (2023) - [i60]Cheng-Yu Hsieh, Chun-Liang Li, Chih-Kuan Yeh, Hootan Nakhost, Yasuhisa Fujii, Alexander Ratner, Ranjay Krishna, Chen-Yu Lee, Tomas Pfister:
Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model Sizes. CoRR abs/2305.02301 (2023) - [i59]Chen-Yu Lee, Chun-Liang Li, Hao Zhang, Timothy Dozat, Vincent Perot, Guolong Su, Xiang Zhang, Kihyuk Sohn, Nikolai Glushnev, Renshen Wang, Joshua Ainslie, Shangbang Long, Siyang Qin, Yasuhisa Fujii, Nan Hua, Tomas Pfister:
FormNetV2: Multimodal Graph Contrastive Learning for Form Document Information Extraction. CoRR abs/2305.02549 (2023) - [i58]Xingchen Wan, Ruoxi Sun, Hanjun Dai, Sercan Ö. Arik, Tomas Pfister:
Better Zero-Shot Reasoning with Self-Adaptive Prompting. CoRR abs/2305.14106 (2023) - [i57]Xingchen Wan, Ruoxi Sun, Hootan Nakhost, Hanjun Dai, Julian Martin Eisenschlos, Sercan Ö. Arik, Tomas Pfister:
Universal Self-adaptive Prompting. CoRR abs/2305.14926 (2023) - [i56]Sayna Ebrahimi, Sercan Ö. Arik, Yihe Dong, Tomas Pfister:
LANISTR: Multimodal Learning from Structured and Unstructured Data. CoRR abs/2305.16556 (2023) - [i55]Ruoxi Sun, Sercan Ö. Arik, Hootan Nakhost, Hanjun Dai, Rajarishi Sinha, Pengcheng Yin, Tomas Pfister:
SQL-PaLM: Improved Large Language Model Adaptation for Text-to-SQL. CoRR abs/2306.00739 (2023) - [i54]Cheng-Yu Hsieh, Si-An Chen, Chun-Liang Li, Yasuhisa Fujii, Alexander Ratner, Chen-Yu Lee, Ranjay Krishna, Tomas Pfister:
Tool Documentation Enables Zero-Shot Tool-Usage with Large Language Models. CoRR abs/2308.00675 (2023) - [i53]Nicasia Beebe-Wang, Sayna Ebrahimi, Jinsung Yoon, Sercan Ö. Arik, Tomas Pfister:
PAITS: Pretraining and Augmentation for Irregularly-Sampled Time Series. CoRR abs/2308.13703 (2023) - [i52]Defu Cao, Furong Jia, Sercan Ö. Arik, Tomas Pfister, Yixiang Zheng, Wen Ye, Yan Liu:
TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting. CoRR abs/2310.04948 (2023) - [i51]Jinsung Yoon, Sercan Ö. Arik, Yanfei Chen, Tomas Pfister:
Search-Adaptor: Text Embedding Customization for Information Retrieval. CoRR abs/2310.08750 (2023) - [i50]Jiefeng Chen, Jinsung Yoon, Sayna Ebrahimi, Sercan Ö. Arik, Tomas Pfister, Somesh Jha:
Adaptation with Self-Evaluation to Improve Selective Prediction in LLMs. CoRR abs/2310.11689 (2023) - [i49]Chuizheng Meng, Yihe Dong, Sercan Ö. Arik, Yan Liu, Tomas Pfister:
COSTAR: Improved Temporal Counterfactual Estimation with Self-Supervised Learning. CoRR abs/2311.00886 (2023) - [i48]Ruoxi Sun, Sercan Ö. Arik, Rajarishi Sinha, Hootan Nakhost, Hanjun Dai, Pengcheng Yin, Tomas Pfister:
SQLPrompt: In-Context Text-to-SQL with Minimal Labeled Data. CoRR abs/2311.02883 (2023) - [i47]Xi Ye, Ruoxi Sun, Sercan Ö. Arik, Tomas Pfister:
Effective Large Language Model Adaptation for Improved Grounding. CoRR abs/2311.09533 (2023) - [i46]James Enouen, Hootan Nakhost, Sayna Ebrahimi, Sercan Ö. Arik, Yan Liu, Tomas Pfister:
TextGenSHAP: Scalable Post-hoc Explanations in Text Generation with Long Documents. CoRR abs/2312.01279 (2023) - 2022
- [i45]Vishnu Suresh Lokhande, Kihyuk Sohn, Jinsung Yoon, Madeleine Udell, Chen-Yu Lee, Tomas Pfister:
Towards Group Robustness in the presence of Partial Group Labels. CoRR abs/2201.03668 (2022) - [i44]Sana Tonekaboni, Chun-Liang Li, Sercan Ö. Arik, Anna Goldenberg, Tomas Pfister:
Decoupling Local and Global Representations of Time Series. CoRR abs/2202.02262 (2022) - [i43]Sercan Ö. Arik, Nathanael C. Yoder, Tomas Pfister:
Self-Adaptive Forecasting for Improved Deep Learning on Non-Stationary Time-Series. CoRR abs/2202.02403 (2022) - [i42]Chun-Hao Chang, Jinsung Yoon, Sercan Ö. Arik, Madeleine Udell, Tomas Pfister:
Data-Efficient and Interpretable Tabular Anomaly Detection. CoRR abs/2203.02034 (2022) - [i41]Chen-Yu Lee, Chun-Liang Li, Timothy Dozat, Vincent Perot, Guolong Su, Nan Hua, Joshua Ainslie, Renshen Wang, Yasuhisa Fujii, Tomas Pfister:
FormNet: Structural Encoding beyond Sequential Modeling in Form Document Information Extraction. CoRR abs/2203.08411 (2022) - [i40]Yuliang Zou, Zizhao Zhang, Chun-Liang Li, Han Zhang, Tomas Pfister, Jia-Bin Huang:
Learning Instance-Specific Adaptation for Cross-Domain Segmentation. CoRR abs/2203.16530 (2022) - [i39]Zifeng Wang, Zizhao Zhang, Sayna Ebrahimi, Ruoxi Sun, Han Zhang, Chen-Yu Lee, Xiaoqi Ren, Guolong Su, Vincent Perot, Jennifer G. Dy, Tomas Pfister:
DualPrompt: Complementary Prompting for Rehearsal-free Continual Learning. CoRR abs/2204.04799 (2022) - [i38]Kuniaki Saito, Kihyuk Sohn, Xiang Zhang, Chun-Liang Li, Chen-Yu Lee, Kate Saenko, Tomas Pfister:
Prefix Conditioning Unifies Language and Label Supervision. CoRR abs/2206.01125 (2022) - [i37]Aya Abdelsalam Ismail, Sercan Ö. Arik, Jinsung Yoon, Ankur Taly, Soheil Feizi, Tomas Pfister:
Interpretable Mixture of Experts for Structured Data. CoRR abs/2206.02107 (2022) - [i36]Yunhao Ge, Sercan Ö. Arik, Jinsung Yoon, Ao Xu, Laurent Itti, Tomas Pfister:
Invariant Structure Learning for Better Generalization and Causal Explainability. CoRR abs/2206.06469 (2022) - [i35]Sayna Ebrahimi, Sercan Ö. Arik, Tomas Pfister:
Test-Time Adaptation for Visual Document Understanding. CoRR abs/2206.07240 (2022) - [i34]Zifeng Wang, Zizhao Zhang, Jacob Devlin, Chen-Yu Lee, Guolong Su, Hao Zhang, Jennifer G. Dy, Vincent Perot, Tomas Pfister:
QueryForm: A Simple Zero-shot Form Entity Query Framework. CoRR abs/2211.07730 (2022) - [i33]Jinsung Yoon, Kihyuk Sohn, Chun-Liang Li, Sercan Ö. Arik, Tomas Pfister:
SPADE: Semi-supervised Anomaly Detection under Distribution Mismatch. CoRR abs/2212.00173 (2022) - 2021
- [i32]Kunpeng Li, Zizhao Zhang, Guanhang Wu, Xuehan Xiong, Chen-Yu Lee, Zhichao Lu, Yun Fu, Tomas Pfister:
Learning from Weakly-labeled Web Videos via Exploring Sub-Concepts. CoRR abs/2101.03713 (2021) - [i31]Chun-Liang Li, Kihyuk Sohn, Jinsung Yoon, Tomas Pfister:
CutPaste: Self-Supervised Learning for Anomaly Detection and Localization. CoRR abs/2104.04015 (2021) - [i30]Zizhao Zhang, Han Zhang, Long Zhao, Ting Chen, Tomas Pfister:
Aggregating Nested Transformers. CoRR abs/2105.12723 (2021) - [i29]Jinsung Yoon, Kihyuk Sohn, Chun-Liang Li, Sercan Ö. Arik, Chen-Yu Lee, Tomas Pfister:
Self-Trained One-class Classification for Unsupervised Anomaly Detection. CoRR abs/2106.06115 (2021) - [i28]Sungyong Seo, Sercan Ö. Arik, Jinsung Yoon, Xiang Zhang, Kihyuk Sohn, Tomas Pfister:
Controlling Neural Networks with Rule Representations. CoRR abs/2106.07804 (2021) - [i27]Chen-Yu Lee, Chun-Liang Li, Chu Wang, Renshen Wang, Yasuhisa Fujii, Siyang Qin, Ashok C. Popat, Tomas Pfister:
ROPE: Reading Order Equivariant Positional Encoding for Graph-based Document Information Extraction. CoRR abs/2106.10786 (2021) - [i26]Zizhao Zhang, Tomas Pfister:
Learning Fast Sample Re-weighting Without Reward Data. CoRR abs/2109.03216 (2021) - [i25]Zifeng Wang, Zizhao Zhang, Chen-Yu Lee, Han Zhang, Ruoxi Sun, Xiaoqi Ren, Guolong Su, Vincent Perot, Jennifer G. Dy, Tomas Pfister:
Learning to Prompt for Continual Learning. CoRR abs/2112.08654 (2021) - [i24]Kihyuk Sohn, Jinsung Yoon, Chun-Liang Li, Chen-Yu Lee, Tomas Pfister:
Anomaly Clustering: Grouping Images into Coherent Clusters of Anomaly Types. CoRR abs/2112.11573 (2021) - 2020
- [i23]Yujia Xie, Hanjun Dai, Minshuo Chen, Bo Dai, Tuo Zhao, Hongyuan Zha, Wei Wei, Tomas Pfister:
Differentiable Top-k Operator with Optimal Transport. CoRR abs/2002.06504 (2020) - [i22]Kihyuk Sohn, Zizhao Zhang, Chun-Liang Li, Han Zhang, Chen-Yu Lee, Tomas Pfister:
A Simple Semi-Supervised Learning Framework for Object Detection. CoRR abs/2005.04757 (2020) - [i21]Sercan Ömer Arik, Chun-Liang Li, Jinsung Yoon, Rajarishi Sinha, Arkady Epshteyn, Long T. Le, Vikas Menon, Shashank Singh, Leyou Zhang, Nate Yoder, Martin Nikoltchev, Yash Sonthalia, Hootan Nakhost, Elli Kanal, Tomas Pfister:
Interpretable Sequence Learning for COVID-19 Forecasting. CoRR abs/2008.00646 (2020) - [i20]Yuliang Zou, Zizhao Zhang, Han Zhang, Chun-Liang Li, Xiao Bian, Jia-Bin Huang, Tomas Pfister:
PseudoSeg: Designing Pseudo Labels for Semantic Segmentation. CoRR abs/2010.09713 (2020) - [i19]Kihyuk Sohn, Chun-Liang Li, Jinsung Yoon, Minho Jin, Tomas Pfister:
Learning and Evaluating Representations for Deep One-class Classification. CoRR abs/2011.02578 (2020) - 2019
- [i18]Sercan Ömer Arik, Tomas Pfister:
Attention-Based Prototypical Learning Towards Interpretable, Confident and Robust Deep Neural Networks. CoRR abs/1902.06292 (2019) - [i17]Rui Zhang, Tomas Pfister, Jia Li:
Harmonic Unpaired Image-to-image Translation. CoRR abs/1902.09727 (2019) - [i16]Donghoon Lee, Tomas Pfister, Ming-Hsuan Yang:
Inserting Videos into Videos. CoRR abs/1903.06571 (2019) - [i15]Sercan Ömer Arik, Tomas Pfister:
TabNet: Attentive Interpretable Tabular Learning. CoRR abs/1908.07442 (2019) - [i14]Linchao Zhu, Sercan Ömer Arik, Yi Yang, Tomas Pfister:
Learning to Transfer Learn. CoRR abs/1908.11406 (2019) - [i13]Yucen Luo, Jun Zhu, Tomas Pfister:
A Simple yet Effective Baseline for Robust Deep Learning with Noisy Labels. CoRR abs/1909.09338 (2019) - [i12]Jinsung Yoon, Sercan Ömer Arik, Tomas Pfister:
Data Valuation using Reinforcement Learning. CoRR abs/1909.11671 (2019) - [i11]Jinsung Yoon, Sercan Ömer Arik, Tomas Pfister:
RL-LIM: Reinforcement Learning-based Locally Interpretable Modeling. CoRR abs/1909.12367 (2019) - [i10]Zizhao Zhang, Han Zhang, Sercan Ömer Arik, Honglak Lee, Tomas Pfister:
IEG: Robust Neural Network Training to Tackle Severe Label Noise. CoRR abs/1910.00701 (2019) - [i9]Mingfei Gao, Zizhao Zhang, Guo Yu, Sercan Ömer Arik, Larry S. Davis, Tomas Pfister:
Consistency-Based Semi-Supervised Active Learning: Towards Minimizing Labeling Cost. CoRR abs/1910.07153 (2019) - [i8]Lanlan Liu, Michael Muelly, Jia Deng, Tomas Pfister, Li-Jia Li:
Generative Modeling for Small-Data Object Detection. CoRR abs/1910.07169 (2019) - [i7]Chih-Kuan Yeh, Been Kim, Sercan Ömer Arik, Chun-Liang Li, Pradeep Ravikumar, Tomas Pfister:
On Concept-Based Explanations in Deep Neural Networks. CoRR abs/1910.07969 (2019) - [i6]Chen Xing, Sercan Ömer Arik, Zizhao Zhang, Tomas Pfister:
Distance-Based Learning from Errors for Confidence Calibration. CoRR abs/1912.01730 (2019) - [i5]Bryan Lim, Sercan Ömer Arik, Nicolas Loeff, Tomas Pfister:
Temporal Fusion Transformers for Interpretable Multi-horizon Time Series Forecasting. CoRR abs/1912.09363 (2019) - 2016
- [i4]Ashish Shrivastava, Tomas Pfister, Oncel Tuzel, Josh Susskind, Wenda Wang, Russell Webb:
Learning from Simulated and Unsupervised Images through Adversarial Training. CoRR abs/1612.07828 (2016) - 2015
- [i3]Tomas Pfister, James Charles, Andrew Zisserman:
Flowing ConvNets for Human Pose Estimation in Videos. CoRR abs/1506.02897 (2015) - [i2]Xiaobai Li, Xiaopeng Hong, Antti Moilanen, Xiaohua Huang, Tomas Pfister, Guoying Zhao, Matti Pietikäinen:
Reading Hidden Emotions: Spontaneous Micro-expression Spotting and Recognition. CoRR abs/1511.00423 (2015) - [i1]James Charles, Tomas Pfister, Derek R. Magee, David C. Hogg, Andrew Zisserman:
Personalizing Human Video Pose Estimation. CoRR abs/1511.06676 (2015)
Coauthor Index
Sercan Ö. Arik
aka: Sercan Ömer Arik
aka: Sercan Ömer Arik
[j15] [j14] [j13] [j12] [j11] [j10] [j9] [j8] [j7] [j6] [j5] [j4] [c60] [c58] [c55] [c54] [c52] [c51] [c50] [c44] [c43] [c42] [c41] [c37] [c35] [c31] [c25] [c24] [c23] [c22] [c21] [c20] [c19] [c17] [i76] [i75] [i74] [i73] [i72] [i68] [i66] [i65] [i64] [i62] [i61] [i58] [i57] [i56] [i55] [i53] [i52] [i51] [i50] [i49] [i48] [i47] [i46] [i44] [i43] [i42] [i37] [i36] [i35] [i33] [i29] [i28] [i21] [i18] [i15] [i14] [i12] [i11] [i10] [i9] [i7] [i6] [i5]
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