Does String-Based Neural MT Learn Source Syntax? - Xing Shi; Inkit Padhi; Kevin Knight (EMNLP, 2016)

Improved Neural Text Attribute Transfer with Non-parallel Data. - Igor Melnyk; Cícero Nogueira dos Santos; Kahini Wadhawan; Inkit Padhi; Abhishek Kumar (CoRR, 2017)

Fighting Offensive Language on Social Media with Unsupervised Text Style Transfer. - Cícero Nogueira dos Santos; Igor Melnyk; Inkit Padhi (ACL (2), 2018)

Data Driven Techniques for Organizing Scientific Articles Relevant to Biomimicry. - Yuanshuo Zhao; Ioana Baldini; Prasanna Sattigeri; Inkit Padhi; Yoong Keok Lee; Ethan Smith (AIES, 2018)

PepCVAE: Semi-Supervised Targeted Design of Antimicrobial Peptide Sequences. - Payel Das; Kahini Wadhawan; Oscar Chang; Tom Sercu; Cícero Nogueira dos Santos; Matthew Riemer; Inkit Padhi; Vijil Chenthamarakshan; Aleksandra Mojsilovic (CoRR, 2018)

Learning Implicit Generative Models by Matching Perceptual Features. - Cícero Nogueira dos Santos; Youssef Mroueh; Inkit Padhi; Pierre L. Dognin (ICCV, 2019)

Interactive Visual Exploration of Latent Space (IVELS) for peptide auto-encoder model selection. - Tom Sercu; Sebastian Gehrmann; Hendrik Strobelt; Payel Das; Inkit Padhi; Cícero Nogueira dos Santos; Kahini Wadhawan; Vijil Chenthamarakshan (DGS@ICLR, 2019)

Sobolev Independence Criterion. - Youssef Mroueh; Tom Sercu; Mattia Rigotti; Inkit Padhi; Cícero Nogueira dos Santos (NeurIPS, 2019)

Learning Implicit Text Generation via Feature Matching. - Inkit Padhi; Pierre L. Dognin; Ke Bai; Cícero Nogueira dos Santos; Vijil Chenthamarakshan; Youssef Mroueh; Payel Das (ACL, 2020)

DualTKB: A Dual Learning Bridge between Text and Knowledge Base. - Pierre L. Dognin; Igor Melnyk; Inkit Padhi; Cícero Nogueira dos Santos; Payel Das (EMNLP (1), 2020)

CogMol: Target-Specific and Selective Drug Design for COVID-19 Using Deep Generative Models. - Vijil Chenthamarakshan; Payel Das; Samuel C. Hoffman; Hendrik Strobelt; Inkit Padhi; Kar Wai Lim; Benjamin Hoover; Matteo Manica; Jannis Born; Teodoro Laino; Aleksandra Mojsilovic (NeurIPS, 2020)

Target-Specific and Selective Drug Design for COVID-19 Using Deep Generative Models. - Vijil Chenthamarakshan; Payel Das; Inkit Padhi; Hendrik Strobelt; Kar Wai Lim; Benjamin Hoover; Samuel C. Hoffman; Aleksandra Mojsilovic (CoRR, 2020)

Accelerating Antimicrobial Discovery with Controllable Deep Generative Models and Molecular Dynamics. - Payel Das; Tom Sercu; Kahini Wadhawan; Inkit Padhi; Sebastian Gehrmann; Flaviu S. Cipcigan; Vijil Chenthamarakshan; Hendrik Strobelt; Cícero Nogueira dos Santos; Pin-Yu Chen; Yi Yan Yang; Jeremy Tan; et al. (CoRR, 2020)

Alleviating Noisy Data in Image Captioning with Cooperative Distillation. - Pierre L. Dognin; Igor Melnyk; Youssef Mroueh; Inkit Padhi; Mattia Rigotti; Jarret Ross; Yair Schiff (CoRR, 2020)

Generate Your Counterfactuals: Towards Controlled Counterfactual Generation for Text. - Nishtha Madaan; Inkit Padhi; Naveen Panwar; Diptikalyan Saha (AAAI, 2021)

ReGen: Reinforcement Learning for Text and Knowledge Base Generation using Pretrained Language Models. - Pierre L. Dognin; Inkit Padhi; Igor Melnyk; Payel Das (EMNLP (1), 2021)

Tabular Transformers for Modeling Multivariate Time Series. - Inkit Padhi; Yair Schiff; Igor Melnyk; Mattia Rigotti; Youssef Mroueh; Pierre L. Dognin; Jerret Ross; Ravi Nair; Erik R. Altman (ICASSP, 2021)

Do Large Scale Molecular Language Representations Capture Important Structural Information? - Jerret Ross; Brian Belgodere; Vijil Chenthamarakshan; Inkit Padhi; Youssef Mroueh; Payel Das (CoRR, 2021)

Fair Infinitesimal Jackknife: Mitigating the Influence of Biased Training Data Points Without Refitting. - Prasanna Sattigeri; Soumya Ghosh; Inkit Padhi; Pierre L. Dognin; Kush R. Varshney (NeurIPS, 2022)

Cloud-Based Real-Time Molecular Screening Platform with MolFormer. - Brian Belgodere; Vijil Chenthamarakshan; Payel Das; Pierre L. Dognin; Toby Kurien; Igor Melnyk; Youssef Mroueh; Inkit Padhi; Mattia Rigotti; Jarret Ross; Yair Schiff; Richard A. Young (ECML/PKDD (6), 2022)

GT4SD: Generative Toolkit for Scientific Discovery. - Matteo Manica; Joris Cadow; Dimitrios Christofidellis; Ashish Dave; Jannis Born; Dean Clarke; Yves Gaetan Nana Teukam; Samuel C. Hoffman; Matthew Buchan; Vijil Chenthamarakshan; Timothy Donovan; Hsiang-Han Hsu; et al. (CoRR, 2022)

Reprogramming Large Pretrained Language Models for Antibody Sequence Infilling. - Igor Melnyk; Vijil Chenthamarakshan; Pin-Yu Chen; Payel Das; Amit Dhurandhar; Inkit Padhi; Devleena Das (CoRR, 2022)

Image Captioning as an Assistive Technology: Lessons Learned from VizWiz 2020 Challenge. - Pierre L. Dognin; Igor Melnyk; Youssef Mroueh; Inkit Padhi; Mattia Rigotti; Jarret Ross; Yair Schiff; Richard A. Young; Brian Belgodere (J. Artif. Intell. Res., 2022)

Large-scale chemical language representations capture molecular structure and properties. - Jerret Ross; Brian Belgodere; Vijil Chenthamarakshan; Inkit Padhi; Youssef Mroueh; Payel Das (Nat. Mac. Intell., 2022)

Explainable Cross-Topic Stance Detection for Search Results. - Tim Draws; Karthikeyan Natesan Ramamurthy; Ioana Baldini; Amit Dhurandhar; Inkit Padhi; Benjamin Timmermans; Nava Tintarev (CHIIR, 2023)

Reprogramming Pretrained Language Models for Antibody Sequence Infilling. - Igor Melnyk; Vijil Chenthamarakshan; Pin-Yu Chen; Payel Das; Amit Dhurandhar; Inkit Padhi; Devleena Das (ICML, 2023)

The Impact of Positional Encoding on Length Generalization in Transformers. - Amirhossein Kazemnejad; Inkit Padhi; Karthikeyan Natesan Ramamurthy; Payel Das; Siva Reddy (NeurIPS, 2023)

The incentive gap in data work in the era of large models. - Katy Ilonka Gero; Payel Das; Pierre L. Dognin; Inkit Padhi; Prasanna Sattigeri; Kush R. Varshney (Nat. Mac. Intell., 2023)

Value Alignment from Unstructured Text. - Inkit Padhi; Karthikeyan Natesan Ramamurthy; Prasanna Sattigeri; Manish Nagireddy; Pierre L. Dognin; Kush R. Varshney (EMNLP (Industry Track), 2024)

ComVas: Contextual Moral Values Alignment System. - Inkit Padhi; Pierre L. Dognin; Jesus Rios; Ronny Luss; Swapnaja Achintalwar; Matthew Riemer; Miao Liu 001; Prasanna Sattigeri; Manish Nagireddy; Kush R. Varshney; Djallel Bouneffouf 001 (IJCAI, 2024)

WikiContradict: A Benchmark for Evaluating LLMs on Real-World Knowledge Conflicts from Wikipedia. - Yufang Hou 001; Alessandra Pascale; Javier Carnerero-Cano; Tigran T. Tchrakian; Radu Marinescu 002; Elizabeth Daly; Inkit Padhi; Prasanna Sattigeri (NeurIPS, 2024)

Detectors for Safe and Reliable LLMs: Implementations, Uses, and Limitations. - Swapnaja Achintalwar; Adriana Alvarado Garcia; Ateret Anaby-Tavor; Ioana Baldini; Sara E. Berger; Bishwaranjan Bhattacharjee; Djallel Bouneffouf 001; Subhajit Chaudhury; Pin-Yu Chen; Lamogha Chiazor; Elizabeth M. Daly; Rogério Abreu de Paula; et al. (CoRR, 2024)

Contextual Moral Value Alignment Through Context-Based Aggregation. - Pierre L. Dognin; Jesus Rios; Ronny Luss; Inkit Padhi; Matthew D. Riemer; Miao Liu 001; Prasanna Sattigeri; Manish Nagireddy; Kush R. Varshney; Djallel Bouneffouf 001 (CoRR, 2024)

Split, Unlearn, Merge: Leveraging Data Attributes for More Effective Unlearning in LLMs. - Swanand Ravindra Kadhe; Farhan Ahmed; Dennis Wei; Nathalie Baracaldo; Inkit Padhi (CoRR, 2024)

When in Doubt, Cascade: Towards Building Efficient and Capable Guardrails. - Manish Nagireddy; Inkit Padhi; Soumya Ghosh; Prasanna Sattigeri (CoRR, 2024)

Final-Model-Only Data Attribution with a Unifying View of Gradient-Based Methods. - Dennis Wei; Inkit Padhi; Soumya Ghosh; Amit Dhurandhar; Karthikeyan Natesan Ramamurthy; Maria Chang 001 (CoRR, 2024)

Granite Guardian. - Inkit Padhi; Manish Nagireddy; Giandomenico Cornacchia; Subhajit Chaudhury; Tejaswini Pedapati; Pierre L. Dognin; Keerthiram Murugesan; Erik Miehling; Martin Santillan Cooper; Kieran Fraser; Giulio Zizzo; Muhammad Zaid Hameed; et al. (CoRR, 2024)

Alignment Studio: Aligning Large Language Models to Particular Contextual Regulations. - Swapnaja Achintalwar; Ioana Baldini; Djallel Bouneffouf 001; Joan Byamugisha; Maria Chang 001; Pierre L. Dognin; Eitan Farchi; Ndivhuwo Makondo; Aleksandra Mojsilovic; Manish Nagireddy; Karthikeyan Natesan Ramamurthy; Inkit Padhi; et al. (IEEE Internet Comput., 2024)

Auditing and Generating Synthetic Data With Controllable Trust Trade-Offs. - Brian Belgodere; Pierre L. Dognin; Adam Ivankay; Igor Melnyk; Youssef Mroueh; Aleksandra Mojsilovic; Jirí Navrátil 001; Apoorva Nitsure; Inkit Padhi; Mattia Rigotti; Jerret Ross; Yair Schiff; et al. (IEEE J. Emerg. Sel. Topics Circuits Syst., 2024)

Contextual Value Alignment. - Pierre Dognin; Jesus Rios; Ronny Luss; Prasanna Sattigeri; Miao Liu 001; Inkit Padhi; Matthew Riemer; Manish Nagireddy; Kush R. Varshney; Djallel Bouneffouf 001 (ICASSP, 2025)

Programming Refusal with Conditional Activation Steering. - Bruce W. Lee; Inkit Padhi; Karthikeyan Natesan Ramamurthy; Erik Miehling; Pierre L. Dognin; Manish Nagireddy; Amit Dhurandhar (ICLR, 2025)

Granite Guardian: Comprehensive LLM Safeguarding. - Inkit Padhi; Manish Nagireddy; Giandomenico Cornacchia; Subhajit Chaudhury; Tejaswini Pedapati; Pierre L. Dognin; Keerthiram Murugesan; Erik Miehling; Martín Santillán Cooper; Kieran Fraser; Giulio Zizzo; Muhammad Zaid Hameed; et al. (NAACL (Industry Track), 2025)