Tejaswini Pedapati

Orcid: 0000-0002-5260-0951

According to our database1, Tejaswini Pedapati authored at least 44 papers between 2017 and 2025.

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Bibliography

2025
TOPJoin: A Context-Aware Multi-Criteria Approach for Joinable Column Search.
CoRR, July, 2025

EvalAssist: A Human-Centered Tool for LLM-as-a-Judge.
CoRR, July, 2025

CoFrNets: Interpretable Neural Architecture Inspired by Continued Fractions.
CoRR, June, 2025

LongFuncEval: Measuring the effectiveness of long context models for function calling.
CoRR, May, 2025

Sparse Gradient Compression for Fine-Tuning Large Language Models.
CoRR, February, 2025

Differentiable Prompt Learning for Vision Language Models.
CoRR, January, 2025

Large Language Model Confidence Estimation via Black-Box Access.
Trans. Mach. Learn. Res., 2025

Granite Guardian: Comprehensive LLM Safeguarding.
Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies, 2025

STAR: Spectral Truncation and Rescale for Model Merging.
Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies, 2025

Large Language Models can Become Strong Self-Detoxifiers.
Proceedings of the Thirteenth International Conference on Learning Representations, 2025

TabSketchFM: Sketch-Based Tabular Representation Learning for Data Discovery Over Data Lakes.
Proceedings of the 41st IEEE International Conference on Data Engineering, 2025

Modular Prompt Learning Improves Vision-Language Models.
Proceedings of the 2025 IEEE International Conference on Acoustics, 2025

EpMAN: Episodic Memory AttentioN for Generalizing to Longer Contexts.
Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

From PEFT to DEFT: Parameter Efficient Finetuning for Reducing Activation Density in Transformers.
Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025

EvalAssist: LLM-as-a-Judge Simplified.
Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025

2024
Model Agnostic Contrastive Explanations for Classification Models.
IEEE J. Emerg. Sel. Topics Circuits Syst., December, 2024

Granite Guardian.
CoRR, 2024

Large Language Models can be Strong Self-Detoxifiers.
CoRR, 2024

Aligning Human and LLM Judgments: Insights from EvalAssist on Task-Specific Evaluations and AI-assisted Assessment Strategy Preferences.
CoRR, 2024

Graph is all you need? Lightweight data-agnostic neural architecture search without training.
CoRR, 2024

NeuroPrune: A Neuro-inspired Topological Sparse Training Algorithm for Large Language Models.
Proceedings of the Findings of the Association for Computational Linguistics, 2024

2023
LakeBench: Benchmarks for Data Discovery over Data Lakes.
CoRR, 2023

MILO: Model-Agnostic Subset Selection Framework for Efficient Model Training and Tuning.
CoRR, 2023

2022
Neural Capacitance: A New Perspective of Neural Network Selection via Edge Dynamics.
CoRR, 2022

Multihop: Leveraging Complex Models to Learn Accurate Simple Models.
Proceedings of the IEEE International Conference on Knowledge Graph, 2022

2021
Contrastive Explanations for Comparing Preferences of Reinforcement Learning Agents.
CoRR, 2021

Building Accurate Simple Models with Multihop.
CoRR, 2021

CoFrNets: Interpretable Neural Architecture Inspired by Continued Fractions.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

AutoText: An End-to-End AutoAI Framework for Text.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Learning Global Transparent Models from Local Contrastive Explanations.
CoRR, 2020

Learning Global Transparent Models consistent with Local Contrastive Explanations.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Automation of Deep Learning - Theory and Practice.
Proceedings of the 2020 on International Conference on Multimedia Retrieval, 2020

Survey on Automated End-to-End Data Science?
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Learning to Rank Learning Curves.
Proceedings of the 37th International Conference on Machine Learning, 2020

2019
How can AI Automate End-to-End Data Science?
CoRR, 2019

Model Agnostic Contrastive Explanations for Structured Data.
CoRR, 2019

A Survey on Neural Architecture Search.
CoRR, 2019

Inductive Transfer for Neural Architecture Optimization.
CoRR, 2019

NeuNetS: An Automated Synthesis Engine for Neural Network Design.
CoRR, 2019

2018
Understanding Unequal Gender Classification Accuracy from Face Images.
CoRR, 2018

Dataset Evolver: An Interactive Feature Engineering Notebook.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Foresight: Recommending Visual Insights.
Proc. VLDB Endow., 2017

Neurology-as-a-Service for the Developing World.
CoRR, 2017

Foresight: Rapid Data Exploration Through Guideposts.
CoRR, 2017


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