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Varun Kumar
Varun Kumar
AWS AI Labs
Verified email at umd.edu - Homepage
Title
Cited by
Cited by
Year
Data augmentation using pre-trained transformer models
V Kumar, A Choudhary, E Cho
AACL, 2020
4442020
BOLD: Dataset and Metrics for Measuring Biases in Open-Ended Language Generation
J Dhamala, T Sun, V Kumar, S Krishna, Y Pruksachatkun, KW Chang, ...
FAccT, 2021
2842021
Multi-lingual Evaluation of Code Generation Models
B Athiwaratkun, SK Gouda, Z Wang, X Li, Y Tian, M Tan, WU Ahmad, ...
ICLR, 2022
113*2022
Closing the loop: User-centered design and evaluation of a human-in-the-loop topic modeling system
A Smith, V Kumar, J Boyd-Graber, K Seppi, L Findlater
IUI, 2018
1072018
A Closer Look At Feature Space Data Augmentation For Few-Shot Intent Classification
V Kumar, H Glaude, C de Lichy, W Campbell
EMNLP, 2019
932019
On the Intrinsic and Extrinsic Fairness Evaluation Metrics for Contextualized Language Representations
YT Cao, Y Pruksachatkun, KW Chang, R Gupta, V Kumar, J Dhamala, ...
ACL, 2022
782022
Industry Scale Semi-Supervised Learning for Natural Language Understanding
L Chen, F Garcia, V Kumar, H Xie, J Lu
NAACL, 2021
582021
ReCode: Robustness Evaluation of Code Generation Models
S Wang, Z Li, H Qian, C Yang, Z Wang, M Shang, V Kumar, S Tan, B Ray, ...
ACL, 2022
47*2022
Mitigating Gender Bias in Distilled Language Models via Counterfactual Role Reversal
U Gupta, J Dhamala, V Kumar, A Verma, Y Pruksachatkun, S Krishna, ...
ACL Findings, 2022
402022
Why Didn't You Listen to Me? Comparing User Control of Human-in-the-Loop Topic Models
V Kumar, A Smith-Renner, L Findlater, K Seppi, J Boyd-Graber
ACL, 2019
292019
Mining shapes of expertise in online social Q&A communities
V Kumar, N Pedanekar
CSCW, 2016
252016
Digging into user control: perceptions of adherence and instability in transparent models
A Smith-Renner, V Kumar, J Boyd-Graber, K Seppi, L Findlater
IUI, 2020
202020
Efficient Semi-Supervised Learning for Natural Language Understanding by Optimizing Diversity
E Cho, H Xie, JP Lalor, V Kumar, WM Campbell
ASRU, 2019
202019
ProtoDA: Efficient Transfer Learning for Few-Shot Intent Classification
M Kumar, V Kumar, H Glaude, A Alok, R Gupta
SLT, 2021
19*2021
Resolving Ambiguities in Text-to-Image Generative Models
N Mehrabi, P Goyal, A Verma, J Dhamala, V Kumar, Q Hu, KW Chang, ...
ACL, 2022
12*2022
A Static Evaluation of Code Completion by Large Language Models
H Ding, V Kumar, Y Tian, Z Wang, R Kwiatkowski, X Li, MK Ramanathan, ...
ACL, 2023
10*2023
The GW/UMD CLPsych 2016 shared task system
A Zirikly, V Kumar, P Resnik
CLPsych @ NAACL 2016, 2016
92016
System and method for providing augmentation based learning content
N Pedanekar, VM Banahatti, SS Karande, V Kumar, AT Doke
92015
Fewer Truncations Improve Language Modeling
H Ding, Z Wang, G Paolini, V Kumar, A Deoras, D Roth, S Soatto
ICML, 2024
62024
Towards greener yet powerful code generation via quantization: An empirical study
X Wei, SK Gonugondla, S Wang, W Ahmad, B Ray, H Qian, X Li, V Kumar, ...
FSE, 2023
6*2023
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