Erik Nijkamp - RankMe

46 papers A* 13A 1Misc 3Journal 26Unranked 3

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Convomem Benchmark: Why Your First 150 Conversations Don't Need RAG. CoRR Egor Pakhomov, Erik Nijkamp, Caiming Xiong
2025	J	`jnl`	xGen-small Technical Report. CoRR Erik Nijkamp, Bo Pang, Egor Pakhomov, Akash Gokul, Jin Qu, Silvio Savarese, Yingbo Zhou, Caiming Xiong
2023	J	`jnl`	CodeGen2: Lessons for Training LLMs on Programming and Natural Languages. CoRR Erik Nijkamp, Hiroaki Hayashi, Caiming Xiong, Silvio Savarese, Yingbo Zhou
2023	A*	`conf`	CodeGen: An Open Large Language Model for Code with Multi-Turn Program Synthesis. ICLR Erik Nijkamp, Bo Pang, Hiroaki Hayashi, Lifu Tu, Huan Wang, Yingbo Zhou, Silvio Savarese, Caiming Xiong
2023	J	`jnl`	Generating High Fidelity Synthetic Data via Coreset selection and Entropic Regularization. CoRR Omead Pooladzandi, Pasha Khosravi, Erik Nijkamp, Baharan Mirzasoleiman
2023	—	`conf`	Long Document Summarization with Top-down and Bottom-up Inference. EACL (Findings) Bo Pang, Erik Nijkamp, Wojciech Kryscinski, Silvio Savarese, Yingbo Zhou, Caiming Xiong
2023	J	`jnl`	XGen-7B Technical Report. CoRR Erik Nijkamp, Tian Xie, Hiroaki Hayashi, Bo Pang, Congying Xia, Chen Xing, Jesse Vig, Semih Yavuz, Philippe Laban, Ben Krause, Senthil Purushwalkam, Tong Niu, Wojciech Kryscinski, Lidiya Murakhovs'ka, Prafulla Kumar Choubey, Alexander R. Fabbri, Ye Liu, Rui Meng, Lifu Tu, Meghana Bhat, Chien-Sheng Wu, Silvio Savarese, Yingbo Zhou, Shafiq Joty, Caiming Xiong
2022	J	`jnl`	A Conversational Paradigm for Program Synthesis. CoRR Erik Nijkamp, Bo Pang, Hiroaki Hayashi, Lifu Tu, Huan Wang, Yingbo Zhou, Silvio Savarese, Caiming Xiong
2022	J	`jnl`	BigIssue: A Realistic Bug Localization Benchmark. CoRR Paul Kassianik, Erik Nijkamp, Bo Pang, Yingbo Zhou, Caiming Xiong
2022	A*	`conf`	Learning Probabilistic Models from Generator Latent Spaces with Hat EBM. NeurIPS Mitch Hill, Erik Nijkamp, Jonathan Mitchell, Bo Pang, Song-Chun Zhu
2022	J	`jnl`	Learning Probabilistic Models from Generator Latent Spaces with Hat EBM. CoRR Mitch Hill, Erik Nijkamp, Jonathan Mitchell, Bo Pang, Song-Chun Zhu
2022	J	`jnl`	Long Document Summarization with Top-down and Bottom-up Inference. CoRR Bo Pang, Erik Nijkamp, Wojciech Kryscinski, Silvio Savarese, Yingbo Zhou, Caiming Xiong
2022	A*	`conf`	MCMC Should Mix: Learning Energy-Based Model with Neural Transport Latent Space MCMC. ICLR Erik Nijkamp, Ruiqi Gao, Pavel Sountsov, Srinivas Vasudevan, Bo Pang, Song-Chun Zhu, Ying Nian Wu
2022	J	`jnl`	ProGen2: Exploring the Boundaries of Protein Language Models. CoRR Erik Nijkamp, Jeffrey A. Ruffolo, Eli N. Weinstein, Nikhil Naik, Ali Madani
2021	A	`conf`	Generative Text Modeling through Short Run Inference. EACL Bo Pang, Erik Nijkamp, Tian Han, Ying Nian Wu
2021	J	`jnl`	Generative Text Modeling through Short Run Inference. CoRR Bo Pang, Erik Nijkamp, Tian Han, Ying Nian Wu
2021	—	`conf`	SCRIPT: Self-Critic PreTraining of Transformers. NAACL-HLT Erik Nijkamp, Bo Pang, Ying Nian Wu, Caiming Xiong
2020	A*	`conf`	Flow Contrastive Estimation of Energy-Based Models. CVPR Ruiqi Gao, Erik Nijkamp, Diederik P. Kingma, Zhen Xu, Andrew M. Dai, Ying Nian Wu
2020	A*	`conf`	Joint Training of Variational Auto-Encoder and Latent Energy-Based Model. CVPR Tian Han, Erik Nijkamp, Linqi Zhou, Bo Pang, Song-Chun Zhu, Ying Nian Wu
2020	J	`jnl`	Joint Training of Variational Auto-Encoder and Latent Energy-Based Model. CoRR Tian Han, Erik Nijkamp, Linqi Zhou, Bo Pang, Song-Chun Zhu, Ying Nian Wu
2020	J	`jnl`	Learning Energy-based Model with Flow-based Backbone by Neural Transport MCMC. CoRR Erik Nijkamp, Ruiqi Gao, Pavel Sountsov, Srinivas Vasudevan, Bo Pang, Song-Chun Zhu, Ying Nian Wu
2020	A*	`conf`	Learning Latent Space Energy-Based Prior Model. NeurIPS Bo Pang, Tian Han, Erik Nijkamp, Song-Chun Zhu, Ying Nian Wu
2020	J	`jnl`	Learning Latent Space Energy-Based Prior Model. CoRR Bo Pang, Tian Han, Erik Nijkamp, Song-Chun Zhu, Ying Nian Wu
2020	—	`conf`	Learning Multi-layer Latent Variable Model via Variational Optimization of Short Run MCMC for Approximate Inference. ECCV (6) Erik Nijkamp, Bo Pang, Tian Han, Linqi Zhou, Song-Chun Zhu, Ying Nian Wu
2020	A*	`conf`	On the Anatomy of MCMC-Based Maximum Likelihood Learning of Energy-Based Models. AAAI Erik Nijkamp, Mitch Hill, Tian Han, Song-Chun Zhu, Ying Nian Wu
2020	J	`jnl`	Semi-supervised Learning by Latent Space Energy-Based Model of Symbol-Vector Coupling. CoRR Bo Pang, Erik Nijkamp, Jiali Cui, Tian Han, Ying Nian Wu
2020	A*	`conf`	Towards Holistic and Automatic Evaluation of Open-Domain Dialogue Generation. ACL Bo Pang, Erik Nijkamp, Wenjuan Han, Linqi Zhou, Yixian Liu, Kewei Tu
2019	J	`jnl`	A Generative Model for Sampling High-Performance and Diverse Weights for Neural Networks. CoRR Lior Deutsch, Erik Nijkamp, Yu Yang
2019	A*	`conf`	Divergence Triangle for Joint Training of Generator Model, Energy-Based Model, and Inferential Model. CVPR Tian Han, Erik Nijkamp, Xiaolin Fang, Mitch Hill, Song-Chun Zhu, Ying Nian Wu
2019	J	`jnl`	Flow Contrastive Estimation of Energy-Based Models. CoRR Ruiqi Gao, Erik Nijkamp, Diederik P. Kingma, Zhen Xu, Andrew M. Dai, Ying Nian Wu
2019	J	`jnl`	Learning Deep Generative Models with Short Run Inference Dynamics. CoRR Erik Nijkamp, Bo Pang, Tian Han, Linqi Zhou, Song-Chun Zhu, Ying Nian Wu
2019	A*	`conf`	Learning Non-Convergent Non-Persistent Short-Run MCMC Toward Energy-Based Model. NeurIPS Erik Nijkamp, Mitch Hill, Song-Chun Zhu, Ying Nian Wu
2019	J	`jnl`	On Learning Non-Convergent Short-Run MCMC Toward Energy-Based Model. CoRR Erik Nijkamp, Song-Chun Zhu, Ying Nian Wu
2019	J	`jnl`	On the Anatomy of MCMC-based Maximum Likelihood Learning of Energy-Based Models. CoRR Erik Nijkamp, Mitch Hill, Tian Han, Song-Chun Zhu, Ying Nian Wu
2019	J	`jnl`	Representation Learning: A Statistical Perspective. CoRR Jianwen Xie, Ruiqi Gao, Erik Nijkamp, Song-Chun Zhu, Ying Nian Wu
2018	J	`jnl`	Building a Telescope to Look Into High-Dimensional Image Spaces. CoRR Mitch Hill, Erik Nijkamp, Song-Chun Zhu
2018	J	`jnl`	Divergence Triangle for Joint Training of Generator Model, Energy-based Model, and Inference Model. CoRR Tian Han, Erik Nijkamp, Xiaolin Fang, Mitch Hill, Song-Chun Zhu, Ying Nian Wu
2017	A*	`conf`	Generative Hierarchical Learning of Sparse FRAME Models. CVPR Jianwen Xie, Yifei Xu, Erik Nijkamp, Ying Nian Wu, Song-Chun Zhu
2011	A*	`conf`	Large-scale matrix factorization with distributed stochastic gradient descent. KDD Rainer Gemulla, Erik Nijkamp, Peter J. Haas, Yannis Sismanis
2011	Misc	`conf`	MapReduce and PACT - Comparing Data Parallel Programming Models. BTW Alexander Alexandrov, Stephan Ewen, Max Heimel, Fabian Hueske, Odej Kao, Volker Markl, Erik Nijkamp, Daniel Warneke
2010	J	`jnl`	BinRank: Scaling Dynamic Authority-Based Search Using Materialized Subgraphs. IEEE Trans. Knowl. Data Eng. Heasoo Hwang, Andrey Balmin, Berthold Reinwald, Erik Nijkamp
2010	J	`jnl`	Massively Parallel Data Analysis with PACTs on Nephele. Proc. VLDB Endow. Alexander Alexandrov, Dominic Battré, Stephan Ewen, Max Heimel, Fabian Hueske, Odej Kao, Volker Markl, Erik Nijkamp, Daniel Warneke
2009	A*	`conf`	BinRank: Scaling Dynamic Authority-Based Search Using Materialized SubGraphs. ICDE Heasoo Hwang, Andrey Balmin, Berthold Reinwald, Erik Nijkamp
2009	Misc	`conf`	Embedded Analytics in Front Office Applications. BTW Martin A. Oberhofer, Erik Nijkamp
2009	Misc	`conf`	Value Demonstration of Embedded Analytics for Front Office Applications. BTW Erik Nijkamp, Martin A. Oberhofer, Albert Maier
2008	J	`jnl`	DBPubs: multidimensional exploration of database publications. Proc. VLDB Endow. Akanksha Baid, Andrey Balmin, Heasoo Hwang, Erik Nijkamp, Jun Rao, Berthold Reinwald, Alkis Simitsis, Yannis Sismanis, Frank van Ham