Kumar Sricharan

53 papers A* 5A 2B 3C 1Misc 1Journal 29Unranked 12

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Automatic Prompt Optimization via Heuristic Search: A Survey. CoRR Wendi Cui, Jiaxin Zhang, Zhuohang Li, Hao Sun, Damien Lopez, Kamalika Das, Bradley A. Malin, Kumar Sricharan
2025	—	`conf`	Heuristic-based Search Algorithm in Automatic Instruction-focused Prompt Optimization: A Survey. ACL (Findings) Wendi Cui, Jiaxin Zhang, Zhuohang Li, Hao Sun, Damien Lopez, Kamalika Das, Bradley A. Malin, Kumar Sricharan
2025	J	`jnl`	SCE: Scalable Consistency Ensembles Make Blackbox Large Language Model Generation More Reliable. CoRR Jiaxin Zhang, Zhuohang Li, Wendi Cui, Kamalika Das, Bradley A. Malin, Kumar Sricharan
2025	—	`conf`	SEE: Strategic Exploration and Exploitation for Cohesive In-Context Prompt Optimization. ACL (1) Wendi Cui, Jiaxin Zhang, Zhuohang Li, Hao Sun, Damien Lopez, Kamalika Das, Bradley A. Malin, Kumar Sricharan
2025	—	`conf`	XOOD: A Self-supervised Algorithm for Detecting Out-of-Distribution Data for Image Classification. ICANN (1) Frej Berglind, Magesh Rajasekaran, Md Saiful Islam Sajol, Haron Temam, Supratik Mukhopadhyay, Kamalika Das, Kumar Sricharan, Kumar Kallurupalli
2024	J	`jnl`	DCR-Consistency: Divide-Conquer-Reasoning for Consistency Evaluation and Improvement of Large Language Models. CoRR Wendi Cui, Jiaxin Zhang, Zhuohang Li, Damien Lopez, Kamalika Das, Bradley A. Malin, Kumar Sricharan
2024	A	`conf`	DECDM: Document Enhancement using Cycle-Consistent Diffusion Models. WACV Jiaxin Zhang, Joy Rimchala, Lalla Mouatadid, Kamalika Das, Kumar Sricharan
2024	A	`conf`	Discriminant Distance-Aware Representation on Deterministic Uncertainty Quantification Methods. AISTATS Jiaxin Zhang, Kamalika Das, Kumar Sricharan
2024	J	`jnl`	Discriminant Distance-Aware Representation on Deterministic Uncertainty Quantification Methods. CoRR Jiaxin Zhang, Kamalika Das, Kumar Sricharan
2024	—	`conf`	Divide-Conquer-Reasoning for Consistency Evaluation and Automatic Improvement of Large Language Models. EMNLP (Industry Track) Wendi Cui, Zhuohang Li, Damien Lopez, Kamalika Das, Bradley A. Malin, Kumar Sricharan, Jiaxin Zhang
2024	A*	`conf`	Do You Know What You Are Talking About? Characterizing Query-Knowledge Relevance For Reliable Retrieval Augmented Generation. EMNLP Zhuohang Li, Jiaxin Zhang, Chao Yan, Kamalika Das, Kumar Sricharan, Murat Kantarcioglu, Bradley A. Malin
2024	J	`jnl`	Do You Know What You Are Talking About? Characterizing Query-Knowledge Relevance For Reliable Retrieval Augmented Generation. CoRR Zhuohang Li, Jiaxin Zhang, Chao Yan, Kamalika Das, Kumar Sricharan, Murat Kantarcioglu, Bradley A. Malin
2024	J	`jnl`	PhaseEvo: Towards Unified In-Context Prompt Optimization for Large Language Models. CoRR Wendi Cui, Jiaxin Zhang, Zhuohang Li, Hao Sun, Damien Lopez, Kamalika Das, Bradley A. Malin, Kumar Sricharan
2024	A*	`conf`	Synthetic Knowledge Ingestion: Towards Knowledge Refinement and Injection for Enhancing Large Language Models. EMNLP Jiaxin Zhang, Wendi Cui, Yiran Huang, Kamalika Das, Kumar Sricharan
2024	J	`jnl`	Synthetic Knowledge Ingestion: Towards Knowledge Refinement and Injection for Enhancing Large Language Models. CoRR Jiaxin Zhang, Wendi Cui, Yiran Huang, Kamalika Das, Kumar Sricharan
2023	J	`jnl`	DECDM: Document Enhancement using Cycle-Consistent Diffusion Models. CoRR Jiaxin Zhang, Joy Rimchala, Lalla Mouatadid, Kamalika Das, Kumar Sricharan
2023	A*	`conf`	Interactive Multi-fidelity Learning for Cost-effective Adaptation of Language Model with Sparse Human Supervision. NeurIPS Jiaxin Zhang, Zhuohang Li, Kamalika Das, Kumar Sricharan
2023	J	`jnl`	Interactive Multi-fidelity Learning for Cost-effective Adaptation of Language Model with Sparse Human Supervision. CoRR Jiaxin Zhang, Zhuohang Li, Kamalika Das, Kumar Sricharan
2023	J	`jnl`	SAC CoRR Jiaxin Zhang, Zhuohang Li, Kamalika Das, Bradley A. Malin, Kumar Sricharan
2023	—	`conf`	SAC³: Reliable Hallucination Detection in Black-Box Language Models via Semantic-aware Cross-check Consistency. EMNLP (Findings) Jiaxin Zhang, Zhuohang Li, Kamalika Das, Bradley A. Malin, Kumar Sricharan
2022	J	`jnl`	XOOD: Extreme Value Based Out-Of-Distribution Detection For Image Classification. CoRR Frej Berglind, Haron Temam, Supratik Mukhopadhyay, Kamalika Das, Md Saiful Islam Sajol, Kumar Sricharan, Kumar Kallurupalli
2021	J	`jnl`	Ensemble Estimation of Generalized Mutual Information With Applications to Genomics. IEEE Trans. Inf. Theory Kevin R. Moon, Kumar Sricharan, Alfred O. Hero III
2018	J	`jnl`	Building robust classifiers through generation of confident out of distribution examples. CoRR Kumar Sricharan, Ashok Srivastava
2018	J	`jnl`	Ensemble Estimation of Information Divergence Entropy Kevin R. Moon, Kumar Sricharan, Kristjan H. Greenewald, Alfred O. Hero III
2018	A*	`conf`	ExprGAN: Facial Expression Editing With Controllable Expression Intensity. AAAI Hui Ding, Kumar Sricharan, Rama Chellappa
2018	J	`jnl`	Improving robustness of classifiers by training against live traffic. CoRR Kumar Sricharan, Kumar Kallurupalli, Ashok Srivastava
2018	J	`jnl`	Latent Laplacian Maximum Entropy Discrimination for Detection of High-Utility Anomalies. IEEE Trans. Inf. Forensics Secur. Elizabeth Hou, Kumar Sricharan, Alfred O. Hero III
2017	J	`jnl`	Ensemble Estimation of Distributional Functionals via $k$-Nearest Neighbors. CoRR Kevin R. Moon, Kumar Sricharan, Alfred O. Hero III
2017	J	`jnl`	Ensemble Estimation of Mutual Information. CoRR Kevin R. Moon, Kumar Sricharan, Alfred O. Hero III
2017	B	`conf`	Ensemble estimation of mutual information. ISIT Kevin R. Moon, Kumar Sricharan, Alfred O. Hero III
2017	J	`jnl`	ExprGAN: Facial Expression Editing with Controllable Expression Intensity. CoRR Hui Ding, Kumar Sricharan, Rama Chellappa
2017	J	`jnl`	Latent Laplacian Maximum Entropy Discrimination for Detection of High-Utility Anomalies. CoRR Elizabeth Hou, Kumar Sricharan, Alfred O. Hero III
2017	—	`conf`	Recognizing Abnormal Heart Sounds Using Deep Learning. KDH@IJCAI Jonathan Rubin, Rui Abreu, Anurag Ganguli, Saigopal Nelaturi, Ion Matei, Kumar Sricharan
2017	J	`jnl`	Recognizing Abnormal Heart Sounds Using Deep Learning. CoRR Jonathan Rubin, Rui Abreu, Anurag Ganguli, Saigopal Nelaturi, Ion Matei, Kumar Sricharan
2017	J	`jnl`	Reports of the Workshops of the Thirty-First AAAI Conference on Artificial Intelligence. AI Mag. Monica Anderson, Roman Barták, John S. Brownstein, David L. Buckeridge, Hoda Eldardiry, Christopher W. Geib, Maria L. Gini, Aaron Isaksen, Sarah Keren, Robert Laddaga, Viliam Lisý, Rodney Martin, David R. Martinez, Martin Michalowski, Loizos Michael, Reuth Mirsky, Thanh Hai Nguyen, Michael J. Paul, Enrico Pontelli, Scott Sanner, Arash Shaban-Nejad, Arunesh Sinha, Shirin Sohrabi, Kumar Sricharan, Biplav Srivastava, Mark Stefik, William W. Streilein, Nathan R. Sturtevant, Kartik Talamadupula, Michael Thielscher, Julian Togelius, Tran Cao Son, Long Tran-Thanh, Neal Wagner, Byron C. Wallace, Szymon Wilk, Jichen Zhu
2017	J	`jnl`	Semi-supervised Conditional GANs. CoRR Kumar Sricharan, Raja Bala, Matthew Shreve, Hui Ding, Kumar Saketh, Jin Sun
2016	—	`conf`	Classifying Heart Sound Recordings using Deep Convolutional Neural Networks and Mel-Frequency Cepstral Coefficients. CinC Jonathan Rubin, Rui Abreu, Anurag Ganguli, Saigopal Nelaturi, Ion Matei, Kumar Sricharan
2016	J	`jnl`	Graph Analysis for Detecting Fraud, Waste, and Abuse in Healthcare Data. AI Mag. Juan Liu, Eric Bier, Aaron Wilson, John Alexis Guerra Gómez, Tomonori Honda, Kumar Sricharan, Leilani Gilpin, Daniel Davies
2016	J	`jnl`	Improving Convergence of Divergence Functional Ensemble Estimators. CoRR Kevin R. Moon, Kumar Sricharan, Kristjan H. Greenewald, Alfred O. Hero III
2016	B	`conf`	Improving convergence of divergence functional ensemble estimators. ISIT Kevin R. Moon, Kumar Sricharan, Kristjan H. Greenewald, Alfred O. Hero III
2015	—	`conf`	Detecting Insider Threat from Enterprise Social and Online Activity Data. MIST@CCS Gaurang Gavai, Kumar Sricharan, Dave Gunning, Rob Rolleston, John Hanley, Mudita Singhal
2015	A*	`conf`	Graph Analysis for Detecting Fraud, Waste, and Abuse in Healthcare Data. AAAI Juan Liu, Eric Bier, Aaron Wilson, Tomonori Honda, Kumar Sricharan, Leilani Gilpin, John Alexis Guerra Gómez, Daniel Davies
2015	J	`jnl`	Supervised and Unsupervised methods to detect Insider Threat from Enterprise Social and Online Activity Data. J. Wirel. Mob. Networks Ubiquitous Comput. Dependable Appl. Gaurang Gavai, Kumar Sricharan, Dave Gunning, John Hanley, Mudita Singhal, Rob Rolleston
2014	—	`conf`	Localizing anomalous changes in time-evolving graphs. SIGMOD Conference Kumar Sricharan, Kamalika Das
2014	J	`jnl`	Multi-source fusion for anomaly detection: using across-domain and across-time peer-group consistency checks. J. Wirel. Mob. Networks Ubiquitous Comput. Dependable Appl. Hoda Eldardiry, Kumar Sricharan, Juan Liu, John Hanley, Bob Price, Oliver Brdiczka, Eugene Bart
2014	—	`conf`	Predicting Company Quitting From Online Social Enterprise Activity. SNAKDD Gaurang Gavai, Kumar Sricharan, Juan Liu, Oliver Brdiczka, John Hanley
2013	J	`jnl`	Ensemble Estimators for Multivariate Entropy Estimation. IEEE Trans. Inf. Theory Kumar Sricharan, Dennis L. Wei, Alfred O. Hero III
2012	—	`conf`	Ensemble weighted kernel estimators for multivariate entropy estimation. NIPS Kumar Sricharan, Alfred O. Hero III
2012	J	`jnl`	Estimation of Nonlinear Functionals of Densities With Confidence. IEEE Trans. Inf. Theory Kumar Sricharan, Raviv Raich, Alfred O. Hero III
2011	C	`conf`	A local dependence measure and its application to screening for high correlations in large data sets. FUSION Kumar Sricharan, Alfred O. Hero III, Bala Rajaratnam
2011	—	`conf`	Efficient anomaly detection using bipartite k-NN graphs. NIPS Kumar Sricharan, Alfred O. Hero III
2011	B	`conf`	k-nearest neighbor estimation of entropies with confidence. ISIT Kumar Sricharan, Raviv Raich, Alfred O. Hero III
2010	Misc	`conf`	Optimized intrinsic dimension estimator using nearest neighbor graphs. ICASSP Kumar Sricharan, Raviv Raich, Alfred O. Hero III