Kamalika Das - RankMe

73 papers A* 6A 7Misc 1Journal 32Unranked 24

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	COMBOOD: A Semiparametric Approach for Detecting Out-of-distribution Data for Image Classification. CoRR Magesh Rajasekaran, Md Saiful Islam Sajol, Frej Berglind, Supratik Mukhopadhyay, Kamalika Das
2026	J	`jnl`	Learning to Rewrite Tool Descriptions for Reliable LLM-Agent Tool Use. CoRR Ruocheng Guo, Kaiwen Dong, Xiang Gao, Kamalika Das
2026	J	`jnl`	REMem: Reasoning with Episodic Memory in Language Agent. CoRR Yiheng Shu, Saisri Padmaja Jonnalagedda, Xiang Gao, Bernal Jiménez Gutiérrez, Weijian Qi, Kamalika Das, Huan Sun, Yu Su
2026	J	`jnl`	RIMRULE: Improving Tool-Using Language Agents via MDL-Guided Rule Learning. CoRR Xiang Gao, Yuguang Yao, Qi Zhang, Kaiwen Dong, Avinash Baidya, Ruocheng Guo, Hilaf Hasson, Kamalika Das
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`	Gradient-guided Attention Map Editing: Towards Efficient Contextual Hallucination Mitigation. NAACL (Findings) Yu Wang, Jiaxin Zhang, Xiang Gao, Wendi Cui, Peng Li, Kamalika Das
2025	J	`jnl`	Gradient-guided Attention Map Editing: Towards Efficient Contextual Hallucination Mitigation. CoRR Yu Wang, Jiaxin Zhang, Xiang Gao, Wendi Cui, Peng Li, Kamalika Das
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	—	`conf`	Learning to Search Effective Example Sequences for In-Context Learning. NAACL (Findings) Xiang Gao, Ankita Sinha, Kamalika Das
2025	J	`jnl`	Learning to Search Effective Example Sequences for In-Context Learning. CoRR Xiang Gao, Ankita Sinha, Kamalika Das
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`	The Behavior Gap: Evaluating Zero-shot LLM Agents in Complex Task-Oriented Dialogs. ACL (Findings) Avinash Baidya, Kamalika Das, Xiang Gao
2025	J	`jnl`	The Behavior Gap: Evaluating Zero-shot LLM Agents in Complex Task-Oriented Dialogs. CoRR Avinash Baidya, Kamalika Das, Xiang Gao
2025	—	`conf`	Transaction Categorization with Relational Deep Learning in QuickBooks. ECML/PKDD (9) Kaiwen Dong, Padmaja Jonnalagedda, Xiang Gao, Ayan Acharya, Maria Kissa, Mauricio Flores, Nitesh V. Chawla, Kamalika Das
2025	J	`jnl`	Transaction Categorization with Relational Deep Learning in QuickBooks. CoRR Kaiwen Dong, Padmaja Jonnalagedda, Xiang Gao, Ayan Acharya, Maria Kissa, Mauricio Flores, Nitesh V. Chawla, Kamalika Das
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	A	`conf`	COMBOOD: A Semiparametric Approach for Detecting Out-of-distribution Data for Image Classification. SDM Magesh Rajasekaran, Md Saiful Islam Sajol, Frej Berglind, Supratik Mukhopadhyay, Kamalika Das
2024	A*	`conf`	Customizing Language Model Responses with Contrastive In-Context Learning. AAAI Xiang Gao, Kamalika Das
2024	J	`jnl`	Customizing Language Model Responses with Contrastive In-Context Learning. CoRR Xiang Gao, Kamalika Das
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	—	`conf`	SPUQ: Perturbation-Based Uncertainty Quantification for Large Language Models. EACL (1) Xiang Gao, Jiaxin Zhang, Lalla Mouatadid, Kamalika Das
2024	J	`jnl`	SPUQ: Perturbation-Based Uncertainty Quantification for Large Language Models. CoRR Xiang Gao, Jiaxin Zhang, Lalla Mouatadid, Kamalika Das
2024	—	`conf`	Survival of the Safest: Towards Secure Prompt Optimization through Interleaved Multi-Objective Evolution. EMNLP (Industry Track) Ankita Sinha, Wendi Cui, Kamalika Das, Jiaxin Zhang
2024	J	`jnl`	Survival of the Safest: Towards Secure Prompt Optimization through Interleaved Multi-Objective Evolution. CoRR Ankita Sinha, Wendi Cui, Kamalika Das, Jiaxin Zhang
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
2020	A*	`conf`	Learning Instrument Invariant Characteristics for Generating High-resolution Global Coral Reef Maps. KDD Ata Akbari Asanjan, Kamalika Das, Alan S. Li, Ved Chirayath, Juan Torres-Perez, Soroosh Sorooshian
2018	J	`jnl`	CADDeLaG: Framework for distributed anomaly detection in large dense graph sequences. CoRR Aniruddha Basak, Kamalika Das, Ole J. Mengshoel
2018	—	`conf`	Understanding Climate-Vegetation Interactions in Global Rainforests Through a GP-Tree Analysis. PPSN (1) Anuradha Kodali, Marcin Szubert, Kamalika Das, Sangram Ganguly, Joshua Clifford Bongard
2017	—	`conf`	ASK-the-Expert: Active Learning Based Knowledge Discovery Using the Expert. ECML/PKDD (3) Kamalika Das, Ilya Avrekh, Bryan L. Matthews, Manali Sharma, Nikunj C. Oza
2017	—	`ed.`	Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2017, Skopje, Macedonia, September 18-22, 2017, Proceedings, Part III ECML/PKDD (3) Yasemin Altun, Kamalika Das, Taneli Mielikäinen, Donato Malerba, Jerzy Stefanowski, Jesse Read, Marinka Zitnik, Michelangelo Ceci, Saso Dzeroski
2016	—	`conf`	Active Learning with Rationales for Identifying Operationally Significant Anomalies in Aviation. ECML/PKDD (3) Manali Sharma, Kamalika Das, Mustafa Bilgic, Bryan L. Matthews, David Nielsen, Nikunj C. Oza
2016	—	`conf`	Distributed Support Vector Machines: An Overview. Solving Large Scale Learning Tasks Marco Stolpe, Kanishka Bhaduri, Kamalika Das
2016	A	`conf`	Reducing Antagonism between Behavioral Diversity and Fitness in Semantic Genetic Programming. GECCO Marcin Szubert, Anuradha Kodali, Sangram Ganguly, Kamalika Das, Josh C. Bongard
2016	A	`conf`	Semantic Forward Propagation for Symbolic Regression. PPSN Marcin Szubert, Anuradha Kodali, Sangram Ganguly, Kamalika Das, Josh C. Bongard
2015	—	`conf`	Large scale support vector regression for aviation safety. IEEE BigData Kamalika Das, Kanishka Bhaduri, Bryan L. Matthews, Nikunj C. Oza
2015	Misc	`conf`	PerCCS: person-count from carbon dioxide using sparse non-negative matrix factorization. UbiComp Chandrayee Basu, Christian Koehler, Kamalika Das, Anind K. Dey
2014	J	`jnl`	Discovering Anomalous Aviation Safety Events Using Scalable Data Mining Algorithms. J. Aerosp. Inf. Syst. Bryan L. Matthews, Santanu Das, Kanishka Bhaduri, Kamalika Das, Rodney Martin, Nikunj C. Oza
2014	—	`conf`	Localizing anomalous changes in time-evolving graphs. SIGMOD Conference Kumar Sricharan, Kamalika Das
2013	—	`conf`	Anomaly Detection in Vertically Partitioned Data by Distributed Core Vector Machines. ECML/PKDD (3) Marco Stolpe, Kanishka Bhaduri, Kamalika Das, Katharina Morik
2013	J	`jnl`	Discovering Anomalous Aviation Safety Events Using Scalable Data Mining Algorithms. J. Aerosp. Inf. Syst. Bryan L. Matthews, Santanu Das, Kanishka Bhaduri, Kamalika Das, Rodney Martin, Nikunj C. Oza
2013	J	`jnl`	Sparse inverse kernel Gaussian Process regression. Stat. Anal. Data Min. Kamalika Das, Ashok N. Srivastava
2011	—	`conf`	Detecting Abnormal Machine Characteristics in Cloud Infrastructures. ICDM Workshops Kanishka Bhaduri, Kamalika Das, Bryan L. Matthews
2011	A	`conf`	Distributed Monitoring of the R2 Statistic for Linear Regression. SDM Kanishka Bhaduri, Kamalika Das, Chris Giannella
2011	J	`jnl`	Distributed anomaly detection using 1-class SVM for vertically partitioned data. Stat. Anal. Data Min. Kamalika Das, Kanishka Bhaduri, Petr Votava
2011	J	`jnl`	Multi-objective optimization based privacy preserving distributed data mining in Peer-to-Peer networks. Peer-to-Peer Netw. Appl. Kamalika Das, Kanishka Bhaduri, Hillol Kargupta
2011	J	`jnl`	Scalable, asynchronous, distributed eigen monitoring of astronomy data streams. Stat. Anal. Data Min. Kanishka Bhaduri, Kamalika Das, Kirk D. Borne, Chris Giannella, Tushar Mahule, Hillol Kargupta
2011	—	`conf`	Sparse Inverse Gaussian Process Regression with Application to Climate Network Discovery. CIDU Kamalika Das, Ashok N. Srivastava
2010	J	`jnl`	A local asynchronous distributed privacy preserving feature selection algorithm for large peer-to-peer networks. Knowl. Inf. Syst. Kamalika Das, Kanishka Bhaduri, Hillol Kargupta
2010	A*	`conf`	Block-GP: Scalable Gaussian Process Regression for Multimodal Data. ICDM Kamalika Das, Ashok N. Srivastava
2010	—	`conf`	Distributed Anomaly Detection using Satellite Data From Multiple Modalitie. CIDU Kanishka Bhaduri, Kamalika Das, Petr Votava
2009	—	`conf`	A Local Distributed Peer-to-Peer Algorithm Using Multi-Party Optimization Based Privacy Preservation for Data Mining Primitive Computation. Peer-to-Peer Computing Kamalika Das, Kanishka Bhaduri, Hillol Kargupta
2009	A	`conf`	Scalable Distributed Change Detection from Astronomy Data Streams Using Local, Asynchronous Eigen Monitoring Algorithms. SDM Kamalika Das, Kanishka Bhaduri, Sugandha Arora, Wesley Griffin, Kirk D. Borne, Chris Giannella, Hillol Kargupta
2008	J	`jnl`	Distributed Identification of Top-l Inner Product Elements and its Application in a Peer-to-Peer Network. IEEE Trans. Knowl. Data Eng. Kamalika Das, Kanishka Bhaduri, Kun Liu, Hillol Kargupta
2008	—	`ch.`	Privacy-Preserving Data Analysis on Graphs and Social Networks. Next Generation of Data Mining Kun Liu, Kamalika Das, Tyrone Grandison, Hillol Kargupta
2007	—	`ch.`	Algorithms for Distributed Data Stream Mining. Data Streams - Models and Algorithms Kanishka Bhaduri, Kamalika Das, Krishnamoorthy Sivakumar, Hillol Kargupta, Ran Wolff, Rong Chen
2007	—	`conf`	Multi-party, Privacy-Preserving Distributed Data Mining Using a Game Theoretic Framework. PKDD Hillol Kargupta, Kamalika Das, Kun Liu
2007	—	`conf`	Peer-to-Peer Data Mining, Privacy Issues, and Games. AIS-ADM Kanishka Bhaduri, Kamalika Das, Hillol Kargupta
2006	J	`jnl`	Client-side web mining for community formation in peer-to-peer environments. SIGKDD Explor. Kun Liu, Kanishka Bhaduri, Kamalika Das, Phuong Nguyen, Hillol Kargupta