Kumar Shridhar

According to our database1, Kumar Shridhar authored at least 27 papers between 2018 and 2024.

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Bibliography

2024
SIKeD: Self-guided Iterative Knowledge Distillation for mathematical reasoning.
CoRR, 2024

SMART: Self-learning Meta-strategy Agent for Reasoning Tasks.
CoRR, 2024

Calibrating Large Language Models with Sample Consistency.
CoRR, 2024

Distilling LLMs' Decomposition Abilities into Compact Language Models.
CoRR, 2024

The ART of LLM Refinement: Ask, Refine, and Trust.
Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), 2024

2023
Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models.
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Trans. Mach. Learn. Res., 2023

First Step Advantage: Importance of Starting Right in Multi-Step Reasoning.
CoRR, 2023

SCREWS: A Modular Framework for Reasoning with Revisions.
CoRR, 2023

Longtonotes: OntoNotes with Longer Coreference Chains.
Proceedings of the Findings of the Association for Computational Linguistics: EACL 2023, 2023

Automatic Educational Question Generation with Difficulty Level Controls.
Proceedings of the Artificial Intelligence in Education - 24th International Conference, 2023

A Causal Framework to Quantify the Robustness of Mathematical Reasoning with Language Models.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

Distilling Reasoning Capabilities into Smaller Language Models.
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

2022
Distilling Multi-Step Reasoning Capabilities of Large Language Models into Smaller Models via Semantic Decompositions.
CoRR, 2022

Learning to Drop Out: An Adversarial Approach to Training Sequence VAEs.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Automatic Generation of Socratic Subquestions for Teaching Math Word Problems.
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

2021
Translational Equivariance in Kernelizable Attention.
CoRR, 2021

HyperEmbed: Tradeoffs Between Resources and Performance in NLP Tasks with Hyperdimensional Computing Enabled Embedding of n-gram Statistics.
Proceedings of the International Joint Conference on Neural Networks, 2021

One to Rule Them All: Towards Joint Indic Language Hate Speech Detection.
Proceedings of the Working Notes of FIRE 2021, 2021

Scaling Within Document Coreference to Long Texts.
Proceedings of the Findings of the Association for Computational Linguistics: ACL/IJCNLP 2021, 2021

2020
Indic-Transformers: An Analysis of Transformer Language Models for Indian Languages.
CoRR, 2020

End to End Binarized Neural Networks for Text Classification.
Proceedings of SustaiNLP: Workshop on Simple and Efficient Natural Language Processing, 2020

2019
ProbAct: A Probabilistic Activation Function for Deep Neural Networks.
CoRR, 2019

A Comprehensive guide to Bayesian Convolutional Neural Network with Variational Inference.
CoRR, 2019

Subword Semantic Hashing for Intent Classification on Small Datasets.
Proceedings of the International Joint Conference on Neural Networks, 2019

Author Profiling using Semantic and Syntactic Features.
Proceedings of the Working Notes of CLEF 2019, 2019

2018
Subword Semantic Hashing for Intent Classification on Small Datasets.
CoRR, 2018

Bayesian Convolutional Neural Networks.
CoRR, 2018


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