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ORCIDArshdeep Sekhon
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2020 – today
- 2024
[i15]Jia He, Mukund Rungta, David Koleczek, Arshdeep Sekhon, Franklin X. Wang, Sadid Hasan:
Does Prompt Formatting Have Any Impact on LLM Performance? CoRR abs/2411.10541 (2024)- 2023
- [c12]Arshdeep Sekhon, Hanjie Chen, Aman Shrivastava, Zhe Wang, Yangfeng Ji, Yanjun Qi:
Improving Interpretability via Explicit Word Interaction Graph Layer. AAAI 2023: 13528-13537 - [i14]Arshdeep Sekhon, Hanjie Chen, Aman Shrivastava, Zhe Wang, Yangfeng Ji, Yanjun Qi:
Improving Interpretability via Explicit Word Interaction Graph Layer. CoRR abs/2302.02016 (2023) - 2022
- [c11]Arshdeep Sekhon, Zhe Wang, Yanjun Qi:
Beyond Data Samples: Aligning Differential Networks Estimation with Scientific Knowledge. AISTATS 2022: 10881-10923 - [c10]Arshdeep Sekhon, Yangfeng Ji, Matthew B. Dwyer
, Yanjun Qi:
White-box Testing of NLP models with Mask Neuron Coverage. NAACL-HLT (Findings) 2022: 1547-1558 - [c9]Zhe Wang, Jake Grigsby, Arshdeep Sekhon, Yanjun Qi:
ST-MAML : A stochastic-task based method for task-heterogeneous meta-learning. UAI 2022: 2066-2074 - [i13]Arshdeep Sekhon, Yangfeng Ji, Matthew B. Dwyer, Yanjun Qi:
White-box Testing of NLP models with Mask Neuron Coverage. CoRR abs/2205.05050 (2022) - 2021
- [c8]Jack Lanchantin, Tom Weingarten, Arshdeep Sekhon, Clint Miller, Yanjun Qi:
Transfer learning for predicting virus-host protein interactions for novel virus sequences. BCB 2021: 36:1-36:10 - [c7]Sanchit Sinha, Hanjie Chen, Arshdeep Sekhon, Yangfeng Ji, Yanjun Qi:
Perturbing Inputs for Fragile Interpretations in Deep Natural Language Processing. BlackboxNLP@EMNLP 2021: 420-434 - [c6]Paola Cascante-Bonilla, Arshdeep Sekhon, Yanjun Qi, Vicente Ordonez:
Evolving Image Compositions for Feature Representation Learning. BMVC 2021: 199 - [i12]Arshdeep Sekhon, Zhe Wang, Yanjun Qi:
Relate and Predict: Structure-Aware Prediction with Jointly Optimized Neural DAG. CoRR abs/2103.02405 (2021) - [i11]Paola Cascante-Bonilla, Arshdeep Sekhon, Yanjun Qi, Vicente Ordonez:
Evolving Image Compositions for Feature Representation Learning. CoRR abs/2106.09011 (2021) - [i10]Sanchit Sinha, Hanjie Chen, Arshdeep Sekhon, Yangfeng Ji, Yanjun Qi:
Perturbing Inputs for Fragile Interpretations in Deep Natural Language Processing. CoRR abs/2108.04990 (2021) - [i9]Zhe Wang, Jake Grigsby, Arshdeep Sekhon, Yanjun Qi:
ST-MAML: A Stochastic-Task based Method for Task-Heterogeneous Meta-Learning. CoRR abs/2109.13305 (2021) - 2020
- [i8]Arshdeep Sekhon, Beilun Wang, Zhe Wang, Yanjun Qi:
Differential Network Learning Beyond Data Samples. CoRR abs/2004.11494 (2020)
2010 – 2019
- 2019
- [c5]Jack Lanchantin, Arshdeep Sekhon, Yanjun Qi:
Neural Message Passing for Multi-label Classification. ECML/PKDD (2) 2019: 138-163 - [i7]Jack Lanchantin, Arshdeep Sekhon, Yanjun Qi:
Neural Message Passing for Multi-Label Classification. CoRR abs/1904.08049 (2019) - 2018
- [j1]Arshdeep Sekhon, Ritambhara Singh, Yanjun Qi:
DeepDiff: DEEP-learning for predicting DIFFerential gene expression from histone modifications. Bioinform. 34(17): i891-i900 (2018) - [c4]Beilun Wang, Arshdeep Sekhon, Yanjun Qi:
Fast and Scalable Learning of Sparse Changes in High-Dimensional Gaussian Graphical Model Structure. AISTATS 2018: 1691-1700 - [c3]Beilun Wang, Arshdeep Sekhon, Yanjun Qi:
A Fast and Scalable Joint Estimator for Integrating Additional Knowledge in Learning Multiple Related Sparse Gaussian Graphical Models. ICML 2018: 5148-5157 - [i6]Beilun Wang, Arshdeep Sekhon, Yanjun Qi:
A Fast and Scalable Joint Estimator for Integrating Additional Knowledge in Learning Multiple Related Sparse Gaussian Graphical Models. CoRR abs/1806.00548 (2018) - [i5]Arshdeep Sekhon, Ritambhara Singh, Yanjun Qi:
DeepDiff: Deep-learning for predicting Differential gene expression from histone modifications. CoRR abs/1807.03878 (2018) - 2017
- [c2]Ritambhara Singh, Jack Lanchantin, Arshdeep Sekhon, Yanjun Qi:
Attend and Predict: Understanding Gene Regulation by Selective Attention on Chromatin. NIPS 2017: 6785-6795 - [c1]Ritambhara Singh, Arshdeep Sekhon, Kamran Kowsari, Jack Lanchantin, Beilun Wang, Yanjun Qi:
GaKCo: A Fast Gapped k-mer String Kernel Using Counting. ECML/PKDD (1) 2017: 356-373 - [i4]Ritambhara Singh, Arshdeep Sekhon, Kamran Kowsari, Jack Lanchantin, Beilun Wang, Yanjun Qi:
GaKCo: a Fast GApped k-mer string Kernel using COunting. CoRR abs/1704.07468 (2017) - [i3]Ritambhara Singh, Jack Lanchantin, Arshdeep Sekhon, Yanjun Qi:
Attend and Predict: Understanding Gene Regulation by Selective Attention on Chromatin. CoRR abs/1708.00339 (2017) - [i2]Beilun Wang, Arshdeep Sekhon, Yanjun Qi:
Fast and Scalable Learning of Sparse Changes in High-Dimensional Gaussian Graphical Model Structure. CoRR abs/1710.11223 (2017) - [i1]Jack Lanchantin, Arshdeep Sekhon, Ritambhara Singh, Yanjun Qi:
Prototype Matching Networks for Large-Scale Multi-label Genomic Sequence Classification. CoRR abs/1710.11238 (2017)
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