Kumar Shridhar

According to our database, Kumar Shridhar authored at least 24 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Calibrating Large Language Models with Sample Consistency.

Qing Lyu, Kumar Shridhar, Chaitanya Malaviya, Li Zhang, Yanai Elazar, Niket Tandon, Marianna Apidianaki, Mrinmaya Sachan, Chris Callison-Burch

CoRR, 2024

Distilling LLMs' Decomposition Abilities into Compact Language Models.

Denis Tarasov, Kumar Shridhar

CoRR, 2024

2023

The ART of LLM Refinement: Ask, Refine, and Trust.

Kumar Shridhar, Koustuv Sinha, Andrew Cohen, Tianlu Wang, Ping Yu, Ram Pasunuru, Mrinmaya Sachan, Jason Weston, Asli Celikyilmaz

CoRR, 2023

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

Kushal Jain, Kumar Shridhar

CoRR, 2023

SCREWS: A Modular Framework for Reasoning with Revisions.

Kumar Shridhar, Harsh Jhamtani, Hao Fang, Benjamin Van Durme, Jason Eisner, Patrick Xia

CoRR, 2023

Longtonotes: OntoNotes with Longer Coreference Chains.

Kumar Shridhar, Nicholas Monath, Raghuveer Thirukovalluru, Alessandro Stolfo, Manzil Zaheer, Andrew McCallum, Mrinmaya Sachan

Proceedings of the Findings of the Association for Computational Linguistics: EACL 2023, 2023

Automatic Educational Question Generation with Difficulty Level Controls.

Ying Jiao, Kumar Shridhar, Peng Cui, Wangchunshu Zhou, Mrinmaya Sachan

Proceedings of the Artificial Intelligence in Education - 24th International Conference, 2023

A Causal Framework to Quantify the Robustness of Mathematical Reasoning with Language Models.

Alessandro Stolfo, Zhijing Jin, Kumar Shridhar, Bernhard Schölkopf, Mrinmaya Sachan

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

Distilling Reasoning Capabilities into Smaller Language Models.

Kumar Shridhar, Alessandro Stolfo, Mrinmaya Sachan

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.

Kumar Shridhar, Alessandro Stolfo, Mrinmaya Sachan

CoRR, 2022

Learning to Drop Out: An Adversarial Approach to Training Sequence VAEs.

Djordje Miladinovic, Kumar Shridhar, Kushal Jain, Max B. Paulus, Joachim M. Buhmann, Carl Allen

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.

Kumar Shridhar, Jakub Macina, Mennatallah El-Assady, Tanmay Sinha, Manu Kapur, Mrinmaya Sachan

Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

2021

Translational Equivariance in Kernelizable Attention.

Max Horn, Kumar Shridhar, Elrich Groenewald, Philipp F. M. Baumann

CoRR, 2021

HyperEmbed: Tradeoffs Between Resources and Performance in NLP Tasks with Hyperdimensional Computing Enabled Embedding of n-gram Statistics.

Pedro Alonso, Kumar Shridhar, Denis Kleyko, Evgeny Osipov, Marcus Liwicki

Proceedings of the International Joint Conference on Neural Networks, 2021

One to Rule Them All: Towards Joint Indic Language Hate Speech Detection.

Mehar Bhatia, Tenzin Singhay Bhotia, Akshat Agarwal, Prakash Ramesh, Shubham Gupta, Kumar Shridhar, Felix Laumann, Ayushman Dash

Proceedings of the Working Notes of FIRE 2021, 2021

Scaling Within Document Coreference to Long Texts.

Raghuveer Thirukovalluru, Nicholas Monath, Kumar Shridhar, Manzil Zaheer, Mrinmaya Sachan, Andrew McCallum

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.

Kushal Jain, Adwait P. Deshpande, Kumar Shridhar, Felix Laumann, Ayushman Dash

CoRR, 2020

End to End Binarized Neural Networks for Text Classification.

Kumar Shridhar, Harshil Jain, Akshat Agarwal, Denis Kleyko

Proceedings of SustaiNLP: Workshop on Simple and Efficient Natural Language Processing, 2020

2019

ProbAct: A Probabilistic Activation Function for Deep Neural Networks.

Joonho Lee, Kumar Shridhar, Hideaki Hayashi, Brian Kenji Iwana, Seokjun Kang, Seiichi Uchida

CoRR, 2019

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

Kumar Shridhar, Felix Laumann, Marcus Liwicki

CoRR, 2019

Subword Semantic Hashing for Intent Classification on Small Datasets.

Kumar Shridhar, Ayushman Dash, Amit Sahu, Gustav Grund Pihlgren, Pedro Alonso, Vinaychandran Pondenkandath, György Kovács, Foteini Simistira, Marcus Liwicki

Proceedings of the International Joint Conference on Neural Networks, 2019

Author Profiling using Semantic and Syntactic Features.

György Kovács, Vanda Balogh, Purvanshi Mehta, Kumar Shridhar, Pedro Alonso, Marcus Liwicki

Proceedings of the Working Notes of CLEF 2019, 2019

2018

Subword Semantic Hashing for Intent Classification on Small Datasets.

Kumar Shridhar, Amit Sahu, Ayushman Dash, Pedro Alonso, Gustav Pihlgren, Vinay Pondeknath, Fotini Simistira, Marcus Liwicki

CoRR, 2018

Bayesian Convolutional Neural Networks.

Felix Laumann, Kumar Shridhar, Adrian Llopart Maurin

CoRR, 2018