Krishnateja Killamsetty

35 papers A* 12A 1Journal 19Unranked 3

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	A Library of LLM Intrinsics for Retrieval-Augmented Generation. CoRR Marina Danilevsky, Kristjan H. Greenewald, R. Chulaka Gunasekara, Maeda F. Hanafi, Lihong He, Yannis Katsis, Krishnateja Killamsetty, Yatin Nandwani, Lucian Popa, Dinesh Raghu, Frederick Reiss, Vraj Shah, Khoi-Nguyen Tran, Huaiyu Zhu, Luis A. Lastras
2025	A*	`conf`	DELIFT: Data Efficient Language model Instruction Fine-Tuning. ICLR Ishika Agarwal, Krishnateja Killamsetty, Lucian Popa, Marina Danilevsky
2025	J	`jnl`	Learning What Matters: Probabilistic Task Selection via Mutual Information for Model Finetuning. CoRR Prateek Chanda, Saral Sureka, Parth Pratim Chatterjee, Krishnateja Killamsetty, Nikhil Shivakumar Nayak, Ganesh Ramakrishnan
2025	J	`jnl`	Sculpting Subspaces: Constrained Full Fine-Tuning in LLMs for Continual Learning. CoRR Nikhil Shivakumar Nayak, Krishnateja Killamsetty, Ligong Han, Abhishek Bhandwaldar, Prateek Chanda, Kai Xu, Hao Wang, Aldo Pareja, Oleg Silkin, Mustafa Eyceoz, Akash Srivastava
2025	A*	`conf`	Unveiling the Secret Recipe: A Guide For Supervised Fine-Tuning Small LLMs. ICLR Aldo Pareja, Nikhil Shivakumar Nayak, Hao Wang, Krishnateja Killamsetty, Shivchander Sudalairaj, Wenlong Zhao, Seungwook Han, Abhishek Bhandwaldar, Guangxuan Xu, Kai Xu, Ligong Han, Luke Inglis, Akash Srivastava
2024	A	`conf`	Beyond Active Learning: Leveraging the Full Potential of Human Interaction via Auto-Labeling, Human Correction, and Human Verification. WACV Nathan Beck, Krishnateja Killamsetty, Suraj Kothawade, Rishabh K. Iyer
2024	J	`jnl`	DELIFT: Data Efficient Language model Instruction Fine Tuning. CoRR Ishika Agarwal, Krishnateja Killamsetty, Lucian Popa, Marina Danilevksy
2024	A*	`conf`	SCoRe: Submodular Combinatorial Representation Learning. ICML Anay Majee, Suraj Kothawade, Krishnateja Killamsetty, Rishabh K. Iyer
2024	J	`jnl`	Unveiling the Secret Recipe: A Guide For Supervised Fine-Tuning Small LLMs. CoRR Aldo Pareja, Nikhil Shivakumar Nayak, Hao Wang, Krishnateja Killamsetty, Shivchander Sudalairaj, Wenlong Zhao, Seungwook Han, Abhishek Bhandwaldar, Guangxuan Xu, Kai Xu, Ligong Han, Luke Inglis, Akash Srivastava
2023	J	`jnl`	Beyond Active Learning: Leveraging the Full Potential of Human Interaction via Auto-Labeling, Human Correction, and Human Verification. CoRR Nathan Beck, Krishnateja Killamsetty, Suraj Kothawade, Rishabh K. Iyer
2023	—	`conf`	INGENIOUS: Using Informative Data Subsets for Efficient Pre-Training of Language Models. EMNLP (Findings) H. S. V. N. S. Kowndinya Renduchintala, Krishnateja Killamsetty, Sumit Bhatia, Milan Aggarwal, Ganesh Ramakrishnan, Rishabh K. Iyer, Balaji Krishnamurthy
2023	J	`jnl`	INGENIOUS: Using Informative Data Subsets for Efficient Pre-Training of Large Language Models. CoRR H. S. V. N. S. Kowndinya Renduchintala, Krishnateja Killamsetty, Sumit Bhatia, Milan Aggarwal, Ganesh Ramakrishnan, Rishabh K. Iyer, Balaji Krishnamurthy
2023	J	`jnl`	MILO: Model-Agnostic Subset Selection Framework for Efficient Model Training and Tuning. CoRR Krishnateja Killamsetty, Alexandre V. Evfimievski, Tejaswini Pedapati, Kiran Kate, Lucian Popa, Rishabh K. Iyer
2023	J	`jnl`	SCoRe: Submodular Combinatorial Representation Learning for Real-World Class-Imbalanced Settings. CoRR Anay Majee, Suraj Kothawade, Krishnateja Killamsetty, Rishabh K. Iyer
2022	A*	`conf`	A Nested Bi-level Optimization Framework for Robust Few Shot Learning. AAAI Krishnateja Killamsetty, Changbin Li, Chen Zhao, Feng Chen, Rishabh K. Iyer
2022	A*	`conf`	AUTOMATA: Gradient Based Data Subset Selection for Compute-Efficient Hyper-parameter Tuning. NeurIPS Krishnateja Killamsetty, Guttu Sai Abhishek, Aakriti, Ganesh Ramakrishnan, Alexandre V. Evfimievski, Lucian Popa, Rishabh K. Iyer
2022	J	`jnl`	AUTOMATA: Gradient Based Data Subset Selection for Compute-Efficient Hyper-parameter Tuning. CoRR Krishnateja Killamsetty, Guttu Sai Abhishek, Aakriti, Alexandre V. Evfimievski, Lucian Popa, Ganesh Ramakrishnan, Rishabh K. Iyer
2022	A*	`conf`	GCR: Gradient Coreset based Replay Buffer Selection for Continual Learning. CVPR Rishabh Tiwari, Krishnateja Killamsetty, Rishabh K. Iyer, Pradeep Shenoy
2022	A*	`conf`	How Out-of-Distribution Data Hurts Semi-Supervised Learning. ICDM Xujiang Zhao, Krishnateja Killamsetty, Rishabh K. Iyer, Feng Chen
2022	—	`conf`	Learning to Robustly Aggregate Labeling Functions for Semi-supervised Data Programming. ACL (Findings) Ayush Maheshwari, Krishnateja Killamsetty, Ganesh Ramakrishnan, Rishabh K. Iyer, Marina Danilevsky, Lucian Popa
2022	A*	`conf`	ORIENT: Submodular Mutual Information Measures for Data Subset Selection under Distribution Shift. NeurIPS Athresh Karanam, Krishnateja Killamsetty, Harsha Kokel, Rishabh K. Iyer
2021	J	`jnl`	GCR: Gradient Coreset Based Replay Buffer Selection For Continual Learning. CoRR Rishabh Tiwari, Krishnateja Killamsetty, Rishabh K. Iyer, Pradeep Shenoy
2021	A*	`conf`	GLISTER: Generalization based Data Subset Selection for Efficient and Robust Learning. AAAI Krishnateja Killamsetty, Durga Sivasubramanian, Ganesh Ramakrishnan, Rishabh K. Iyer
2021	J	`jnl`	GRAD-MATCH: A Gradient Matching Based Data Subset Selection for Efficient Learning. CoRR Krishnateja Killamsetty, Durga Sivasubramanian, Baharan Mirzasoleiman, Ganesh Ramakrishnan, Abir De, Rishabh K. Iyer
2021	A*	`conf`	GRAD-MATCH: Gradient Matching based Data Subset Selection for Efficient Deep Model Training. ICML Krishnateja Killamsetty, Durga Sivasubramanian, Ganesh Ramakrishnan, Abir De, Rishabh K. Iyer
2021	J	`jnl`	Learning to Robustly Aggregate Labeling Functions for Semi-supervised Data Programming. CoRR Ayush Maheshwari, Krishnateja Killamsetty, Ganesh Ramakrishnan, Rishabh K. Iyer, Marina Danilevsky, Lucian Popa
2021	A*	`conf`	RETRIEVE: Coreset Selection for Efficient and Robust Semi-Supervised Learning. NeurIPS Krishnateja Killamsetty, Xujiang Zhao, Feng Chen, Rishabh K. Iyer
2021	J	`jnl`	RETRIEVE: Coreset Selection for Efficient and Robust Semi-Supervised Learning. CoRR Krishnateja Killamsetty, Xujiang Zhao, Feng Chen, Rishabh K. Iyer
2021	A*	`conf`	SIMILAR: Submodular Information Measures Based Active Learning In Realistic Scenarios. NeurIPS Suraj Kothawade, Nathan Beck, Krishnateja Killamsetty, Rishabh K. Iyer
2021	J	`jnl`	SIMILAR: Submodular Information Measures Based Active Learning In Realistic Scenarios. CoRR Suraj Kothawade, Nathan Beck, Krishnateja Killamsetty, Rishabh K. Iyer
2021	—	`conf`	Semi-Supervised Data Programming with Subset Selection. ACL/IJCNLP (Findings) Ayush Maheshwari, Oishik Chatterjee, Krishnateja Killamsetty, Ganesh Ramakrishnan, Rishabh K. Iyer
2020	J	`jnl`	A Reweighted Meta Learning Framework for Robust Few Shot Learning. CoRR Krishnateja Killamsetty, Changbin Li, Chen Zhao, Rishabh K. Iyer, Feng Chen
2020	J	`jnl`	Data Programming using Semi-Supervision and Subset Selection. CoRR Ayush Maheshwari, Oishik Chatterjee, Krishnateja Killamsetty, Rishabh K. Iyer, Ganesh Ramakrishnan
2020	J	`jnl`	GLISTER: Generalization based Data Subset Selection for Efficient and Robust Learning. CoRR Krishnateja Killamsetty, Durga Sivasubramanian, Ganesh Ramakrishnan, Rishabh K. Iyer
2020	J	`jnl`	Robust Semi-Supervised Learning with Out of Distribution Data. CoRR Xujiang Zhao, Krishnateja Killamsetty, Rishabh K. Iyer, Feng Chen