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Chandan Singh
Chandan Singh
Senior researcher, Microsoft research
Verified email at microsoft.com - Homepage
Title
Cited by
Cited by
Year
Definitions, methods, and applications in interpretable machine learning
WJ Murdoch*, C Singh*, K Kumbier, R Abbasi-Asl, B Yu
PNAS 🔍🌳, 2019
2112*2019
Beyond the imitation game: Quantifying and extrapolating the capabilities of language models
A Srivastava, A Rastogi, A Rao, AAM Shoeb, A Abid, A Fisch, AR Brown, ...
TMLR 🤖, 2022
1371*2022
Interpretations are useful: penalizing explanations to align neural networks with prior knowledge
L Rieger, C Singh, W Murdoch, B Yu
ICML 🔍, 2020
2532020
Large scale image segmentation with structured loss based deep learning for connectome reconstruction
J Funke*, F Tschopp*, W Grisaitis, A Sheridan, C Singh, S Saalfeld, ...
IEEE TPAMI 🧠, 2018
253*2018
Hierarchical interpretations for neural network predictions
C Singh*, WJ Murdoch*, B Yu
ICLR 🔍, 2018
1822018
Curating a covid-19 data repository and forecasting county-level death counts in the united states
N Altieri, RL Barter, J Duncan, R Dwivedi, K Kumbier, X Li, R Netzorg, ...
HDSR 🌳💊, 2021
89*2021
Rethinking interpretability in the era of large language models
C Singh, JP Inala, M Galley, R Caruana, J Gao
arXiv 🔍🤖🌳, 2024
882024
NL-augmenter: a framework for task-sensitive natural language augmentation
KD Dhole, V Gangal, S Gehrmann, A Gupta, Z Li, S Mahamood, ...
NEJLT 🤖, 2021
772021
Hierarchical shrinkage: Improving the accuracy and interpretability of tree-based models.
A Agarwal*, YS Tan*, O Ronen, C Singh, B Yu
ICML 🔍🌳, 2022
542022
Adaptive wavelet distillation from neural networks through interpretations
W Ha, C Singh, F Lanusse, S Upadhyayula, B Yu
NeurIPS 🔍🌳, 2021
482021
Self-verification improves few-shot clinical information extraction
Z Gero*, C Singh*, H Cheng, T Naumann, M Galley, J Gao, H Poon
ICML workshop 🔍🤖💊, 2023
432023
Augmenting interpretable models with large language models during training
C Singh, A Askari, R Caruana, J Gao
Nature communications 🔍🤖🌳, 2023
40*2023
Fast interpretable greedy-tree sums (figs)
YS Tan*, C Singh*, K Nasseri*, A Agarwal*, J Duncan, O Ronen, ...
PNAS 🔍🌳💊, 2023
40*2023
Explaining data patterns in natural language with language models
C Singh*, JX Morris*, J Aneja, AM Rush, J Gao
EMNLP workshop 🔍🤖, 2022
38*2022
Explaining black box text modules in natural language with language models
C Singh*, AR Hsu*, R Antonello, S Jain, AG Huth, B Yu, J Gao
NeurIPS workshop 🔍🤖🧠, 2023
332023
imodels: a python package for fitting interpretable models
C Singh*, K Nasseri*, YS Tan, T Tang, B Yu
JOSS 🔍🌳, 2021
282021
Tell your model where to attend: Post-hoc attention steering for llms
Q Zhang, C Singh, L Liu, X Liu, B Yu, J Gao, T Zhao
ICLR 🤖, 2024
272024
Revisiting minimum description length complexity in overparameterized models
R Dwivedi*, C Singh*, B Yu, M Wainwright
JMLR, 2023
25*2023
A consensus layer V pyramidal neuron can sustain interpulse-interval coding
C Singh, WB Levy
PLOS one 🧠, 2017
212017
Tree prompting: Efficient task adaptation without fine-tuning
C Singh*, J Morris*, AM Rush, J Gao, Y Deng
EMNLP 🔍🤖🌳, 2023
18*2023
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