Kumar Shridhar
13 papers · 2020–2026 · 6 venues · across top CS/AI venues
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Research topics
Artificial Intelligence
(9)
Natural Language Processing
(8)
Core AI
(8)
Machine Learning
(7)
Deep Learning
(5)
Application Areas
(4)
Generation
(4)
Learning Types Β· Machine Learning
(4)
Models
(3)
Resources & Methods
(3)
Architectures
(2)
Bayesian & Probabilistic
(2)
Learning Paradigms
(2)
Learning Types Β· Deep Learning
(2)
Optimization & Theory
(2)
Keywords
large language model
(7)
mathematical reasoning
(3)
knowledge distillation
(2)
language model
(2)
model compression
(2)
chain of thought
(2)
multi-step reasoning
(2)
chain-of-thought reasoning
(2)
transfer learning
(1)
model selection
(1)
sequence generation
(1)
question decomposition
(1)
self-supervised learning
(1)
coreference resolution
(1)
few-shot learning
(1)
variational autoencoder
(1)
question generation
(1)
model calibration
(1)
intent classification
(1)
adversarial training
(1)
Papers
Apertus: Democratizing Open and Compliant LLMs for Global Language Environments
ACL 2026
Calibrating Large Language Models with Sample Consistency
AAAI 2025
First-Step Advantage: Importance of Starting Right in Multi-Step Math Reasoning
ACL 2025
Select-then-Route : Taxonomy guided Routing for LLMs
EMNLP 2025
SIKeD: Self-guided Iterative Knowledge Distillation for Mathematical Reasoning
ACL 2025
The ART of LLM Refinement: Ask, Refine, and Trust
NAACL 2024
A Causal Framework to Quantify the Robustness of Mathematical Reasoning with Language Models
ACL 2023
Distilling Reasoning Capabilities into Smaller Language Models
ACL 2023
Longtonotes: OntoNotes with Longer Coreference Chains
EACL 2023
Automatic Generation of Socratic Subquestions for Teaching Math Word Problems
EMNLP 2022
Learning to Drop Out: An Adversarial Approach to Training Sequence VAEs
NeurIPS 2022
Scaling Within Document Coreference to Long Texts
ACL 2021
End to End Binarized Neural Networks for Text Classification
EMNLP 2020