Segui
Danish Pruthi
Danish Pruthi
Indian Institute of Science, Bangalore
Email verificata su iisc.ac.in - Home page
Titolo
Citata da
Citata da
Anno
Combating Adversarial Misspellings with Robust Word Recognition
D Pruthi, B Dhingra, ZC Lipton
ACL 2019, 2019
3572019
Learning to Deceive with Attention-Based Explanations
D Pruthi, M Gupta, B Dhingra, G Neubig, ZC Lipton
ACL 2020, 2020
2362020
SPINE: SParse Interpretable Neural Embeddings
A Subramanian, D Pruthi, H Jhamtani, T Berg-Kirkpatrick, E Hovy
AAAI 2018, 2017
1652017
compare-mt: A Tool for Holistic Comparison of Language Generation Systems
G Neubig, ZY Dou, J Hu, P Michel, D Pruthi, X Wang
NAACL 2019 (System Demonstrations), 2019
1342019
Evaluating Explanations: How much do explanations from the teacher aid students?
D Pruthi, R Bansal, B Dhingra, LB Soares, M Collins, ZC Lipton, G Neubig, ...
TACL 2021, 2020
1172020
NeuSpell: A Neural Spelling Correction Toolkit
SM Jayanthi, D Pruthi, G Neubig
EMNLP 2020 (System Demonstrations), 2020
842020
Simple and Effective Semi-Supervised Question Answering
B Dhingra, D Pruthi, D Rajagopal
NAACL 2018, 2018
832018
Explain, Edit, and Understand: Rethinking User Study Design for Evaluating Model Explanations
S Arora, D Pruthi, N Sadeh, WW Cohen, ZC Lipton, G Neubig
AAAI 2022, 2021
442021
Do Context-Aware Translation Models Pay the Right Attention?
K Yin, P Fernandes, D Pruthi, A Chaudhary, AFT Martins, G Neubig
ACL 2021, 2021
362021
Weakly-and Semi-supervised Evidence Extraction
D Pruthi, B Dhingra, G Neubig, ZC Lipton
Findings of EMNLP 2020, 2020
282020
Inspecting the Geographical Representativeness of Images from Text-to-Image Models
A Basu, RV Babu, D Pruthi
International Conference on Computer Vision (ICCV 2023), 2023
272023
Learning to Scaffold: Optimizing Model Explanations for Teaching
P Fernandes, M Treviso, D Pruthi, AFT Martins, G Neubig
NeurIPS 2022, 2022
232022
Maxxyt: An autonomous wearable device for real-time tracking of a wide range of exercises
D Pruthi, A Jain, KM Jatavallabhula, R Nalwaya, P Teja
UKSim 2015, 137-141, 2015
132015
Model-tuning Via Prompts Makes NLP Models Adversarially Robust
M Raman, P Maini, JZ Kolter, ZC Lipton, D Pruthi
EMNLP 2023, 2023
122023
Discovering response-eliciting factors in social question answering: A reddit inspired study
D Pruthi, Y Dahiya, P Talukdar
ICWSM 2016, 2016
12*2016
What Can Natural Language Processing Do for Peer Review?
I Kuznetsov, OM Afzal, K Dercksen, N Dycke, A Goldberg, T Hope, D Hovy, ...
arXiv preprint arXiv:2405.06563, 2024
112024
Geographical Erasure in Language Generation
P Schwöbel, J Golebiowski, M Donini, C Archambeau, D Pruthi
Findings of EMNLP 2023, 2023
102023
Downstream Trade-offs of a Family of Text Watermarks
A Ajith, S Singh, D Pruthi
Findings of the Association for Computational Linguistics: EMNLP 2024, 14039 …, 2024
9*2024
Evaluating Large Language Models for Health-related Queries with Presuppositions
N Kaur, M Choudhury, D Pruthi
arXiv preprint arXiv:2312.08800, 2023
82023
Goodhart's Law Applies to NLP's Explanation Benchmarks
J Hsia, D Pruthi, A Singh, ZC Lipton
arXiv preprint arXiv:2308.14272, 2023
62023
Il sistema al momento non può eseguire l'operazione. Riprova più tardi.
Articoli 1–20