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2020 – today
- 2024
[c11]Sanchit Sinha, Guangzhi Xiong, Aidong Zhang:
A Self-explaining Neural Architecture for Generalizable Concept Learning. IJCAI 2024: 503-511- [c10]Sanchit Sinha
, Guangzhi Xiong, Aidong Zhang:
CoLiDR: Concept Learning using Aggregated Disentangled Representations. KDD 2024: 2699-2710 - [c9]Sanchit Sinha, Yuguang Yue, Victor Soto, Mayank Kulkarni, Jianhua Lu, Aidong Zhang:
MAML-en-LLM: Model Agnostic Meta-Training of LLMs for Improved In-Context Learning. KDD 2024: 2711-2720 - [i7]Sanchit Sinha, Guangzhi Xiong, Aidong Zhang:
A Self-explaining Neural Architecture for Generalizable Concept Learning. CoRR abs/2405.00349 (2024) - [i6]Sanchit Sinha, Yuguang Yue, Victor Soto, Mayank Kulkarni, Jianhua Lu, Aidong Zhang:
MAML-en-LLM: Model Agnostic Meta-Training of LLMs for Improved In-Context Learning. CoRR abs/2405.11446 (2024) - [i5]Sanchit Sinha, Guangzhi Xiong, Aidong Zhang:
CoLiDR: Concept Learning using Aggregated Disentangled Representations. CoRR abs/2407.19300 (2024) - 2023
- [c8]Sanchit Sinha, Mengdi Huai, Jianhui Sun, Aidong Zhang:
Understanding and Enhancing Robustness of Concept-Based Models. AAAI 2023: 15127-15135 - [c7]Anshu Bhatia, Sanchit Sinha, Saket Dingliwal, Karthik Gopalakrishnan, Sravan Bodapati, Katrin Kirchhoff:
Don't Stop Self-Supervision: Accent Adaptation of Speech Representations via Residual Adapters. INTERSPEECH 2023: 3362-3366 - [c6]Jianhui Sun, Sanchit Sinha, Aidong Zhang:
Enhance Diffusion to Improve Robust Generalization. KDD 2023: 2083-2095 - [i4]Jianhui Sun, Sanchit Sinha, Aidong Zhang:
Enhance Diffusion to Improve Robust Generalization. CoRR abs/2306.02618 (2023) - [i3]Anshu Bhatia, Sanchit Sinha, Saket Dingliwal, Karthik Gopalakrishnan, Sravan Bodapati, Katrin Kirchhoff:
Don't Stop Self-Supervision: Accent Adaptation of Speech Representations via Residual Adapters. CoRR abs/2307.00453 (2023) - 2022
- [i2]Sanchit Sinha, Mengdi Huai, Jianhui Sun, Aidong Zhang:
Understanding and Enhancing Robustness of Concept-based Models. CoRR abs/2211.16080 (2022) - 2021
- [c5]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 - [c4]Abhijin Adiga, Nicholas Palmer, Sanchit Sinha, Penina Waghalter, Aniruddha Dave, Daniel Perez Lazarte, Thierry Brévault, Andrea Apolloni, Henning S. Mortveit, Young Yun Baek, Madhav V. Marathe:
Realistic Commodity Flow Networks to Assess Vulnerability of Food Systems. COMPLEX NETWORKS 2021: 168-179 - [i1]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)
2010 – 2019
- 2019
- [c3]Dhruva Sahrawat, Mohit Agarwal, Sanchit Sinha, Aditya Adhikary, Mansi Agarwal, Rajiv Ratn Shah, Roger Zimmermann:
Video Summarization using Global Attention with Memory Network and LSTM. BigMM 2019: 231-236 - [c2]Mohit Agarwal, Sanchit Sinha, Maneet Singh, Shruti Nagpal, Richa Singh, Mayank Vatsa:
Triplet Transform Learning for Automated Primate Face Recognition. ICIP 2019: 3462-3466 - 2018
- [c1]Sanchit Sinha, Mohit Agarwal, Mayank Vatsa, Richa Singh, Saket Anand:
Exploring Bias in Primate Face Detection and Recognition. ECCV Workshops (1) 2018: 541-555
Coauthor Index
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