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Ananth Balashankar
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2020 – today
- 2024
- [j1]Aradhana Sinha, Ananth Balashankar, Ahmad Beirami, Thi Avrahami, Jilin Chen, Alex Beutel:
Break it, Imitate it, Fix it: Robustness by Generating Human-Like Attacks. Trans. Mach. Learn. Res. 2024 (2024) - [c15]Zhaofeng Wu, Ananth Balashankar, Yoon Kim, Jacob Eisenstein, Ahmad Beirami:
Reuse Your Rewards: Reward Model Transfer for Zero-Shot Cross-Lingual Alignment. EMNLP 2024: 1332-1353 - [i12]Zhaofeng Wu, Ananth Balashankar, Yoon Kim, Jacob Eisenstein, Ahmad Beirami:
Reuse Your Rewards: Reward Model Transfer for Zero-Shot Cross-Lingual Alignment. CoRR abs/2404.12318 (2024) - [i11]James Atwood, Preethi Lahoti, Ananth Balashankar, Flavien Prost, Ahmad Beirami:
Inducing Group Fairness in LLM-Based Decisions. CoRR abs/2406.16738 (2024) - [i10]Yash Kumar Lal, Preethi Lahoti, Aradhana Sinha, Yao Qin, Ananth Balashankar:
Automated Adversarial Discovery for Safety Classifiers. CoRR abs/2406.17104 (2024) - [i9]Ankit Bhardwaj, Ananth Balashankar, Shiva R. Iyer, Nita Soans, Anant Sudarshan, Rohini Pande, Lakshminarayanan Subramanian:
Discovering Hidden Pollution Hotspots Using Sparse Sensor Measurements. CoRR abs/2410.04309 (2024) - 2023
- [c14]Ananth Balashankar, Srikanth Jagabathula, Lakshmi Subramanian:
Learning Conditional Granger Causal Temporal Networks. CLeaR 2023: 692-706 - [c13]Ananth Balashankar, Xuezhi Wang, Yao Qin, Ben Packer, Nithum Thain, Ed H. Chi, Jilin Chen, Alex Beutel:
Improving Classifier Robustness through Active Generative Counterfactual Data Augmentation. EMNLP (Findings) 2023: 127-139 - [c12]Zhouxing Shi, Nicholas Carlini, Ananth Balashankar, Ludwig Schmidt, Cho-Jui Hsieh, Alex Beutel, Yao Qin:
Effective Robustness against Natural Distribution Shifts for Models with Different Training Data. NeurIPS 2023 - [i8]Zhouxing Shi, Nicholas Carlini, Ananth Balashankar, Ludwig Schmidt, Cho-Jui Hsieh, Alex Beutel, Yao Qin:
Effective Robustness against Natural Distribution Shifts for Models with Different Training Data. CoRR abs/2302.01381 (2023) - [i7]Ananth Balashankar, Xuezhi Wang, Yao Qin, Ben Packer, Nithum Thain, Jilin Chen, Ed H. Chi, Alex Beutel:
Improving Classifier Robustness through Active Generation of Pairwise Counterfactuals. CoRR abs/2305.13535 (2023) - [i6]Aradhana Sinha, Ananth Balashankar, Ahmad Beirami, Thi Avrahami, Jilin Chen, Alex Beutel:
Break it, Imitate it, Fix it: Robustness by Generating Human-Like Attacks. CoRR abs/2310.16955 (2023) - [i5]Ananth Balashankar, Xiao Ma, Aradhana Sinha, Ahmad Beirami, Yao Qin, Jilin Chen, Alex Beutel:
Improving Few-shot Generalization of Safety Classifiers via Data Augmented Parameter-Efficient Fine-Tuning. CoRR abs/2310.16959 (2023) - 2022
- [c11]Ananth Balashankar, Samuel Fraiberger, Eric Deregt, Marelize Gorgens, Lakshminarayanan Subramanian:
Targeted Policy Recommendations using Outcome-aware Clustering. COMPASS 2022: 300-312 - [c10]Ananth Balashankar, Alyssa Lees:
The Need for Transparent Demographic Group Trade-Offs in Credit Risk and Income Classification. iConference (1) 2022: 344-354 - 2021
- [c9]Ananth Balashankar, Lakshminarayanan Subramanian:
Learning Faithful Representations of Causal Graphs. ACL/IJCNLP (1) 2021: 839-850 - [c8]Ananth Balashankar, Xuezhi Wang, Ben Packer, Nithum Thain, Ed H. Chi, Alex Beutel:
Can We Improve Model Robustness through Secondary Attribute Counterfactuals? EMNLP (1) 2021: 4701-4712 - [c7]Ananth Balashankar, Alex Beutel, Lakshminarayanan Subramanian:
Enhancing Neural Recommender Models through Domain-Specific Concordance. WSDM 2021: 1002-1010 - [i4]Ananth Balashankar, Lakshminarayanan Subramanian, Samuel P. Fraiberger:
Fine-grained prediction of food insecurity using news streams. CoRR abs/2111.15602 (2021) - 2020
- [i3]Yan Shvartzshnaider, Ananth Balashankar, Vikas Patidar, Thomas Wies, Lakshminarayanan Subramanian:
Beyond The Text: Analysis of Privacy Statements through Syntactic and Semantic Role Labeling. CoRR abs/2010.00678 (2020)
2010 – 2019
- 2019
- [c6]Ananth Balashankar, Aashish Dugar, Lakshminarayanan Subramanian, Samuel Fraiberger:
Reconstructing the MERS disease outbreak from news. COMPASS 2019: 272-280 - [c5]Ananth Balashankar, Sunandan Chakraborty, Samuel Fraiberger, Lakshminarayanan Subramanian:
Identifying Predictive Causal Factors from News Streams. EMNLP/IJCNLP (1) 2019: 2338-2348 - [c4]Yan Shvartzshnaider, Zvonimir Pavlinovic, Ananth Balashankar, Thomas Wies
, Lakshminarayanan Subramanian, Helen Nissenbaum, Prateek Mittal:
VACCINE: Using Contextual Integrity For Data Leakage Detection. WWW 2019: 1702-1712 - [i2]Ananth Balashankar, Alyssa Lees:
Fairness Sample Complexity and the Case for Human Intervention. CoRR abs/1910.11452 (2019) - [i1]Ananth Balashankar, Alyssa Lees, Chris Welty, Lakshminarayanan Subramanian:
What is Fair? Exploring Pareto-Efficiency for Fairness Constrained Classifiers. CoRR abs/1910.14120 (2019) - 2018
- [c3]Ananth Balashankar, Sunandan Chakraborty, Lakshminarayanan Subramanian:
Unsupervised Word Influencer Networks from News Streams. ECONLP@ACL 2018: 62-68 - [c2]Yan Shvartzshanider, Ananth Balashankar, Thomas Wies
RECIPE: Applying Open Domain Question Answering to Privacy Policies. QA@ACL 2018: 71-77 - 2014
- [c1]Swadhin Pradhan
(Stable) virtual landmarks: Spatial dropbox to enhance retail experience. COMSNETS 2014: 1-8
Coauthor Index
aka: Lakshmi Subramanian
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