Tejaswini Pedapati

59 papers A* 11B 2Misc 1Journal 40Unranked 5

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	AI Steerability 360: A Toolkit for Steering Large Language Models. CoRR Erik Miehling, Karthikeyan Natesan Ramamurthy, Praveen Venkateswaran, Irene Ko, Pierre L. Dognin, Moninder Singh, Tejaswini Pedapati, Avinash Balakrishnan, Matthew Riemer, Dennis Wei, Inge Vejsbjerg, Elizabeth M. Daly, Kush R. Varshney
2026	J	`jnl`	CoFrGeNet: Continued Fraction Architectures for Language Generation. CoRR Amit Dhurandhar, Vijil Chenthamarakshan, Dennis Wei, Tejaswini Pedapati, Karthikeyan Natesan Ramamurthy, Rahul Nair
2025	J	`jnl`	CoFrNets: Interpretable Neural Architecture Inspired by Continued Fractions. CoRR Isha Puri, Amit Dhurandhar, Tejaswini Pedapati, Kartikeyan Shanmugam, Dennis Wei, Kush R. Varshney
2025	A*	`conf`	Differentiable Prompt Learning for Vision Language Models. IJCAI Zhenhan Huang, Tejaswini Pedapati, Pin-Yu Chen, Jianxi Gao
2025	J	`jnl`	Differentiable Prompt Learning for Vision Language Models. CoRR Zhenhan Huang, Tejaswini Pedapati, Pin-Yu Chen, Jianxi Gao
2025	—	`conf`	EpMAN: Episodic Memory AttentioN for Generalizing to Longer Contexts. ACL (1) Subhajit Chaudhury, Payel Das, Sarathkrishna Swaminathan, Georgios Kollias, Elliot Nelson, Khushbu Pahwa, Tejaswini Pedapati, Igor Melnyk, Matthew Riemer
2025	J	`jnl`	EpMAN: Episodic Memory AttentioN for Generalizing to Longer Contexts. CoRR Subhajit Chaudhury, Payel Das, Sarathkrishna Swaminathan, Georgios Kollias, Elliot Nelson, Khushbu Pahwa, Tejaswini Pedapati, Igor Melnyk, Matthew Riemer
2025	J	`jnl`	EvalAssist: A Human-Centered Tool for LLM-as-a-Judge. CoRR Zahra Ashktorab, Elizabeth M. Daly, Erik Miehling, Werner Geyer, Martin Santillan Cooper, Tejaswini Pedapati, Michael Desmond, Qian Pan, Hyo Jin Do
2025	A*	`conf`	EvalAssist: Insights on Task-Specific Evaluations and AI-Assisted Judgment Strategy Preferences. UIST Zahra Ashktorab, Michael Desmond, Qian Pan, James M. Johnson, Martín Santillán Cooper, Elizabeth M. Daly, Rahul Nair, Tejaswini Pedapati, Hyo Jin Do, Werner Geyer
2025	A*	`conf`	EvalAssist: LLM-as-a-Judge Simplified. AAAI Michael Desmond, Zahra Ashktorab, Werner Geyer, Elizabeth M. Daly, Martín Santillán Cooper, Qian Pan, Rahul Nair, Nico Wagner, Tejaswini Pedapati
2025	J	`jnl`	Evaluating Joinable Column Discovery Approaches for Context-Aware Search. CoRR Harsha Kokel, Aamod Khatiwada, Tejaswini Pedapati, Haritha Ananthakrishnan, Oktie Hassanzadeh, Horst Samulowitz, Kavitha Srinivas
2025	A*	`conf`	From PEFT to DEFT: Parameter Efficient Finetuning for Reducing Activation Density in Transformers. AAAI Bharat Runwal, Tejaswini Pedapati, Pin-Yu Chen
2025	—	`conf`	Granite Guardian: Comprehensive LLM Safeguarding. NAACL (Industry Track) Inkit Padhi, Manish Nagireddy, Giandomenico Cornacchia, Subhajit Chaudhury, Tejaswini Pedapati, Pierre L. Dognin, Keerthiram Murugesan, Erik Miehling, Martín Santillán Cooper, Kieran Fraser, Giulio Zizzo, Muhammad Zaid Hameed, Mark Purcell, Michael Desmond, Qian Pan, Inge Vejsbjerg, Elizabeth M. Daly, Michael Hind, Werner Geyer, Ambrish Rawat, Kush R. Varshney, Prasanna Sattigeri
2025	J	`jnl`	Large Language Model Confidence Estimation via Black-Box Access. Trans. Mach. Learn. Res. Tejaswini Pedapati, Amit Dhurandhar, Soumya Ghosh, Soham Dan, Prasanna Sattigeri
2025	A*	`conf`	Large Language Models can Become Strong Self-Detoxifiers. ICLR Ching-Yun Ko, Pin-Yu Chen, Payel Das, Youssef Mroueh, Soham Dan, Georgios Kollias, Subhajit Chaudhury, Tejaswini Pedapati, Luca Daniel
2025	J	`jnl`	LongFuncEval: Measuring the effectiveness of long context models for function calling. CoRR Kiran Kate, Tejaswini Pedapati, Kinjal Basu, Yara Rizk, Vijil Chenthamarakshan, Subhajit Chaudhury, Mayank Agarwal, Ibrahim Abdelaziz
2025	Misc	`conf`	Modular Prompt Learning Improves Vision-Language Models. ICASSP Zhenhan Huang, Tejaswini Pedapati, Pin-Yu Chen, Jianxi Gao
2025	J	`jnl`	Modular Prompt Learning Improves Vision-Language Models. CoRR Zhenhan Huang, Tejaswini Pedapati, Pin-Yu Chen, Jianxi Gao
2025	J	`jnl`	OjaKV: Context-Aware Online Low-Rank KV Cache Compression with Oja's Rule. CoRR Yuxuan Zhu, David H. Yang, Mohammad Mohammadi Amiri, Keerthiram Murugesan, Tejaswini Pedapati, Pin-Yu Chen
2025	—	`conf`	STAR: Spectral Truncation and Rescale for Model Merging. NAACL (Short Papers) Yu-Ang Lee, Ching-Yun Ko, Tejaswini Pedapati, I-Hsin Chung, Mi-Yen Yeh, Pin-Yu Chen
2025	J	`jnl`	STAR: Spectral Truncation and Rescale for Model Merging. CoRR Yu-Ang Lee, Ching-Yun Ko, Tejaswini Pedapati, I-Hsin Chung, Mi-Yen Yeh, Pin-Yu Chen
2025	J	`jnl`	Sparse Gradient Compression for Fine-Tuning Large Language Models. CoRR David H. Yang, Mohammad Mohammadi Amiri, Tejaswini Pedapati, Subhajit Chaudhury, Pin-Yu Chen
2025	J	`jnl`	TOPJoin: A Context-Aware Multi-Criteria Approach for Joinable Column Search. CoRR Harsha Kokel, Aamod Khatiwada, Tejaswini Pedapati, Haritha Ananthakrishnan, Oktie Hassanzadeh, Horst Samulowitz, Kavitha Srinivas
2025	A*	`conf`	TabSketchFM: Sketch-Based Tabular Representation Learning for Data Discovery Over Data Lakes. ICDE Aamod Khatiwada, Harsha Kokel, Ibrahim Abdelaziz, Subhajit Chaudhury, Julian Dolby, Oktie Hassanzadeh, Zhenhan Huang, Tejaswini Pedapati, Horst Samulowitz, Kavitha Srinivas
2024	J	`jnl`	Aligning Human and LLM Judgments: Insights from EvalAssist on Task-Specific Evaluations and AI-assisted Assessment Strategy Preferences. CoRR Zahra Ashktorab, Michael Desmond, Qian Pan, James M. Johnson, Martin Santillan Cooper, Elizabeth M. Daly, Rahul Nair, Tejaswini Pedapati, Swapnaja Achintalwar, Werner Geyer
2024	J	`jnl`	From PEFT to DEFT: Parameter Efficient Finetuning for Reducing Activation Density in Transformers. CoRR Bharat Runwal, Tejaswini Pedapati, Pin-Yu Chen
2024	J	`jnl`	Granite Guardian. CoRR Inkit Padhi, Manish Nagireddy, Giandomenico Cornacchia, Subhajit Chaudhury, Tejaswini Pedapati, Pierre L. Dognin, Keerthiram Murugesan, Erik Miehling, Martin Santillan Cooper, Kieran Fraser, Giulio Zizzo, Muhammad Zaid Hameed, Mark Purcell, Michael Desmond, Qian Pan, Zahra Ashktorab, Inge Vejsbjerg, Elizabeth M. Daly, Michael Hind, Werner Geyer, Ambrish Rawat, Kush R. Varshney, Prasanna Sattigeri
2024	J	`jnl`	Graph is all you need? Lightweight data-agnostic neural architecture search without training. CoRR Zhenhan Huang, Tejaswini Pedapati, Pin-Yu Chen, Chunheng Jiang, Jianxi Gao
2024	J	`jnl`	Large Language Model Confidence Estimation via Black-Box Access. CoRR Tejaswini Pedapati, Amit Dhurandhar, Soumya Ghosh, Soham Dan, Prasanna Sattigeri
2024	J	`jnl`	Large Language Models can be Strong Self-Detoxifiers. CoRR Ching-Yun Ko, Pin-Yu Chen, Payel Das, Youssef Mroueh, Soham Dan, Georgios Kollias, Subhajit Chaudhury, Tejaswini Pedapati, Luca Daniel
2024	J	`jnl`	Model Agnostic Contrastive Explanations for Classification Models. IEEE J. Emerg. Sel. Topics Circuits Syst. Amit Dhurandhar, Tejaswini Pedapati, Avinash Balakrishnan, Pin-Yu Chen, Karthikeyan Shanmugam, Ruchir Puri
2024	—	`conf`	NeuroPrune: A Neuro-inspired Topological Sparse Training Algorithm for Large Language Models. ACL (Findings) Amit Dhurandhar, Tejaswini Pedapati, Ronny Luss, Soham Dan, Aurélie C. Lozano, Payel Das, Georgios Kollias
2024	J	`jnl`	NeuroPrune: A Neuro-inspired Topological Sparse Training Algorithm for Large Language Models. CoRR Amit Dhurandhar, Tejaswini Pedapati, Ronny Luss, Soham Dan, Aurélie C. Lozano, Payel Das, Georgios Kollias
2024	J	`jnl`	TabSketchFM: Sketch-based Tabular Representation Learning for Data Discovery over Data Lakes. CoRR Aamod Khatiwada, Harsha Kokel, Ibrahim Abdelaziz, Subhajit Chaudhury, Julian Dolby, Oktie Hassanzadeh, Zhenhan Huang, Tejaswini Pedapati, Horst Samulowitz, Kavitha Srinivas
2023	J	`jnl`	LakeBench: Benchmarks for Data Discovery over Data Lakes. CoRR Kavitha Srinivas, Julian Dolby, Ibrahim Abdelaziz, Oktie Hassanzadeh, Harsha Kokel, Aamod Khatiwada, Tejaswini Pedapati, Subhajit Chaudhury, Horst Samulowitz
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
2022	—	`conf`	Multihop: Leveraging Complex Models to Learn Accurate Simple Models. ICKG Amit Dhurandhar, Tejaswini Pedapati
2022	J	`jnl`	Neural Capacitance: A New Perspective of Neural Network Selection via Edge Dynamics. CoRR Chunheng Jiang, Tejaswini Pedapati, Pin-Yu Chen, Yizhou Sun, Jianxi Gao
2021	A*	`conf`	AutoText: An End-to-End AutoAI Framework for Text. AAAI Arunima Chaudhary, Alayt Issak, Kiran Kate, Yannis Katsis, Abel N. Valente, Dakuo Wang, Alexandre V. Evfimievski, Sairam Gurajada, Ban Kawas, A. Cristiano I. Malossi, Lucian Popa, Tejaswini Pedapati, Horst Samulowitz, Martin Wistuba, Yunyao Li
2021	J	`jnl`	Building Accurate Simple Models with Multihop. CoRR Amit Dhurandhar, Tejaswini Pedapati
2021	A*	`conf`	CoFrNets: Interpretable Neural Architecture Inspired by Continued Fractions. NeurIPS Isha Puri, Amit Dhurandhar, Tejaswini Pedapati, Karthikeyan Shanmugam, Dennis Wei, Kush R. Varshney
2021	J	`jnl`	Contrastive Explanations for Comparing Preferences of Reinforcement Learning Agents. CoRR Jasmina Gajcin, Rahul Nair, Tejaswini Pedapati, Radu Marinescu, Elizabeth Daly, Ivana Dusparic
2020	B	`conf`	Automation of Deep Learning - Theory and Practice. ICMR Martin Wistuba, Ambrish Rawat, Tejaswini Pedapati
2020	A*	`conf`	Learning Global Transparent Models consistent with Local Contrastive Explanations. NeurIPS Tejaswini Pedapati, Avinash Balakrishnan, Karthikeyan Shanmugam, Amit Dhurandhar
2020	J	`jnl`	Learning Global Transparent Models from Local Contrastive Explanations. CoRR Tejaswini Pedapati, Avinash Balakrishnan, Karthikeyan Shanmugam, Amit Dhurandhar
2020	A*	`conf`	Learning to Rank Learning Curves. ICML Martin Wistuba, Tejaswini Pedapati
2020	J	`jnl`	Learning to Rank Learning Curves. CoRR Martin Wistuba, Tejaswini Pedapati
2020	B	`conf`	Survey on Automated End-to-End Data Science? IJCNN Djallel Bouneffouf, Charu C. Aggarwal, Thanh Hoang, Udayan Khurana, Horst Samulowitz, Beat Buesser, Sijia Liu, Tejaswini Pedapati, Parikshit Ram, Ambrish Rawat, Martin Wistuba, Alexander G. Gray
2019	J	`jnl`	A Survey on Neural Architecture Search. CoRR Martin Wistuba, Ambrish Rawat, Tejaswini Pedapati
2019	J	`jnl`	How can AI Automate End-to-End Data Science? CoRR Charu C. Aggarwal, Djallel Bouneffouf, Horst Samulowitz, Beat Buesser, Thanh Hoang, Udayan Khurana, Sijia Liu, Tejaswini Pedapati, Parikshit Ram, Ambrish Rawat, Martin Wistuba, Alexander G. Gray
2019	J	`jnl`	Inductive Transfer for Neural Architecture Optimization. CoRR Martin Wistuba, Tejaswini Pedapati
2019	J	`jnl`	Model Agnostic Contrastive Explanations for Structured Data. CoRR Amit Dhurandhar, Tejaswini Pedapati, Avinash Balakrishnan, Pin-Yu Chen, Karthikeyan Shanmugam, Ruchir Puri
2019	J	`jnl`	NeuNetS: An Automated Synthesis Engine for Neural Network Design. CoRR Atin Sood, Benjamin Elder, Benjamin Herta, Chao Xue, Costas Bekas, A. Cristiano I. Malossi, Debashish Saha, Florian Scheidegger, Ganesh Venkataraman, Gegi Thomas, Giovanni Mariani, Hendrik Strobelt, Horst Samulowitz, Martin Wistuba, Matteo Manica, Mihir R. Choudhury, Rong Yan, Roxana Istrate, Ruchir Puri, Tejaswini Pedapati
2018	A*	`conf`	Dataset Evolver: An Interactive Feature Engineering Notebook. AAAI Fatemeh Nargesian, Udayan Khurana, Tejaswini Pedapati, Horst Samulowitz, Deepak S. Turaga
2018	J	`jnl`	Understanding Unequal Gender Classification Accuracy from Face Images. CoRR Vidya Muthukumar, Tejaswini Pedapati, Nalini K. Ratha, Prasanna Sattigeri, Chai-Wah Wu, Brian Kingsbury, Abhishek Kumar, Samuel Thomas, Aleksandra Mojsilovic, Kush R. Varshney
2017	J	`jnl`	Foresight: Rapid Data Exploration Through Guideposts. CoRR Çagatay Demiralp, Peter J. Haas, Srinivasan Parthasarathy, Tejaswini Pedapati
2017	J	`jnl`	Foresight: Recommending Visual Insights. CoRR Çagatay Demiralp, Peter J. Haas, Srinivasan Parthasarathy, Tejaswini Pedapati
2017	J	`jnl`	Foresight: Recommending Visual Insights. Proc. VLDB Endow. Çagatay Demiralp, Peter J. Haas, Srinivasan Parthasarathy, Tejaswini Pedapati
2017	J	`jnl`	Neurology-as-a-Service for the Developing World. CoRR Tejas Dharamsi, Payel Das, Tejaswini Pedapati, Gregory Bramble, Vinod Muthusamy, Horst Samulowitz, Kush R. Varshney, Yuvaraj Rajamanickam, John Thomas, Justin Dauwels