Payel Das
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
38
Venues
9
Active years
2019–2026
Best venue rank
A*
Where they publish
Papers
38 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2026 | AAAI | GP-MoLFormer-Sim: Test Time Molecular Optimization Through Contextual Similarity Guidance. | Jir Navrtil, Jarret Ross, Payel Das, Youssef Mroueh, Samuel C. Hoffman, Vijil Chenthamarakshan, Brian Belgodere |
| 2026 | ACL | ImReasoner: Improving Memory-based Language Models for Reasoning-in-a-Haystack Tasks. | Ching-Yun Ko, Payel Das, Sihui Dai, Georgios Kollias, Subhajit Chaudhury, Aurlie C. Lozano, Pin-Yu Chen |
| 2025 | ACL | EpMAN: Episodic Memory AttentioN for Generalizing to Longer Contexts. | Subhajit Chaudhury, Payel Das, Sarathkrishna Swaminathan, Georgios Kollias, Elliot Nelson, Khushbu Pahwa, Tejaswini Pedapati, Igor Melnyk, Matthew Riemer |
| 2025 | ACL | Combining Domain and Alignment Vectors Provides Better Knowledge-Safety Trade-offs in LLMs. | Megh Thakkar, Quentin Fournier, Matthew Riemer, Pin-Yu Chen, Amal Zouaq, Payel Das, Sarath Chandar |
| 2025 | ICLR | Large Language Models can Become Strong Self-Detoxifiers. | Ching-Yun Ko, Pin-Yu Chen, Payel Das, Youssef Mroueh, Soham Dan, Georgios Kollias, Subhajit Chaudhury, Tejaswini Pedapati, Luca Daniel |
| 2025 | ICLR | SEAL: Safety-enhanced Aligned LLM Fine-tuning via Bilevel Data Selection. | Han Shen, Pin-Yu Chen, Payel Das, Tianyi Chen |
| 2025 | ICML | Aligning Protein Conformation Ensemble Generation with Physical Feedback. | Jiarui Lu, Xiaoyin Chen, Stephen Zhewen Lu, Aurlie C. Lozano, Vijil Chenthamarakshan, Payel Das, Jian Tang |
| 2025 | ICML | Position: Theory of Mind Benchmarks are Broken for Large Language Models. | Matthew Riemer, Zahra Ashktorab, Djallel Bouneffouf, Payel Das, Miao Liu, Justin D. Weisz, Murray Campbell |
| 2025 | IJCAI | Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction To Generation and Beyond. | Kehan Guo, Yili Shen, Gisela Abigail Gonzalez-Montiel, Yue Huang, Yujun Zhou, Mihir Surve, Zhichun Guo, Payel Das, Nitesh V. Chawla, Olaf Wiest, Xiangliang Zhang |
| 2024 | ACL | NeuroPrune: A Neuro-inspired Topological Sparse Training Algorithm for Large Language Models. | Amit Dhurandhar, Tejaswini Pedapati, Ronny Luss, Soham Dan, Aurlie C. Lozano, Payel Das, Georgios Kollias |
| 2024 | ACL | A Deep Dive into the Trade-Offs of Parameter-Efficient Preference Alignment Techniques. | Megh Thakkar, Quentin Fournier, Matthew Riemer, Pin-Yu Chen, Amal Zouaq, Payel Das, Sarath Chandar |
| 2024 | ICML | Larimar: Large Language Models with Episodic Memory Control. | Payel Das, Subhajit Chaudhury, Elliot Nelson, Igor Melnyk, Sarathkrishna Swaminathan, Sihui Dai, Aurlie C. Lozano, Georgios Kollias, Vijil Chenthamarakshan, Jir Navrtil, Soham Dan, Pin-Yu Chen |
| 2024 | ICML | What Would Gauss Say About Representations? Probing Pretrained Image Models using Synthetic Gaussian Benchmarks. | Ching-Yun Ko, Pin-Yu Chen, Payel Das, Jeet Mohapatra, Luca Daniel |
| 2024 | ICML | Boundary Exploration for Bayesian Optimization With Unknown Physical Constraints. | Yunsheng Tian, Ane Zuniga, Xinwei Zhang, Johannes P. Drholt, Payel Das, Jie Chen, Wojciech Matusik, Mina Konakovic-Lukovic |
| 2023 | AAAI | Equi-Tuning: Group Equivariant Fine-Tuning of Pretrained Models. | Sourya Basu, Prasanna Sattigeri, Karthikeyan Natesan Ramamurthy, Vijil Chenthamarakshan, Kush R. Varshney, Lav R. Varshney, Payel Das |
| 2023 | ICASSP | Direction Aware Positional and Structural Encoding for Directed Graph Neural Networks. | Yonas Sium, Georgios Kollias, Tsuyoshi Id, Payel Das, Naoki Abe, Aurlie C. Lozano, Qi Li |
| 2023 | ICLR | Protein Representation Learning by Geometric Structure Pretraining. | Zuobai Zhang, Minghao Xu, Arian Rokkum Jamasb, Vijil Chenthamarakshan, Aurlie C. Lozano, Payel Das, Jian Tang |
| 2023 | ICML | Hierarchical Grammar-Induced Geometry for Data-Efficient Molecular Property Prediction. | Minghao Guo, Veronika Thost, Samuel W. Song, Adithya Balachandran, Payel Das, Jie Chen, Wojciech Matusik |
| 2023 | ICML | Reprogramming Pretrained Language Models for Antibody Sequence Infilling. | Igor Melnyk, Vijil Chenthamarakshan, Pin-Yu Chen, Payel Das, Amit Dhurandhar, Inkit Padhi, Devleena Das |
| 2022 | AAAI | Fourier Representations for Black-Box Optimization over Categorical Variables. | Hamid Dadkhahi, Jesus Rios, Karthikeyan Shanmugam, Payel Das |
| 2022 | EMNLP | Knowledge Graph Generation From Text. | Igor Melnyk, Pierre L. Dognin, Payel Das |
| 2022 | ICASSP | Augmenting Molecular Deep Generative Models with Topological Data Analysis Representations. | Yair Schiff, Vijil Chenthamarakshan, Samuel C. Hoffman, Karthikeyan Natesan Ramamurthy, Payel Das |
| 2022 | ICLR | Data-Efficient Graph Grammar Learning for Molecular Generation. | Minghao Guo, Veronika Thost, Beichen Li, Payel Das, Jie Chen, Wojciech Matusik |
| 2022 | ICML | Biological Sequence Design with GFlowNets. | Moksh Jain, Emmanuel Bengio, Alex Hernndez-Garca, Jarrid Rector-Brooks, Bonaventure F. P. Dossou, Chanakya Ajit Ekbote, Jie Fu, Tianyu Zhang, Michael Kilgour, Dinghuai Zhang, Lena Simine, Payel Das, Yoshua Bengio |
| 2022 | IJCAI | Towards Creativity Characterization of Generative Models via Group-Based Subset Scanning. | Celia Cintas, Payel Das, Brian Quanz, Girmaw Abebe Tadesse, Skyler Speakman, Pin-Yu Chen |
| 2021 | AAAI | Self-Progressing Robust Training. | Minhao Cheng, Pin-Yu Chen, Sijia Liu, Shiyu Chang, Cho-Jui Hsieh, Payel Das |
| 2021 | EMNLP | ReGen: Reinforcement Learning for Text and Knowledge Base Generation using Pretrained Language Models. | Pierre L. Dognin, Inkit Padhi, Igor Melnyk, Payel Das |
| 2021 | ICASSP | Active Estimation From Multimodal Data. | Arpan Mukherjee, Ali Tajer, Pin-Yu Chen, Payel Das |
| 2021 | ICML | Fold2Seq: A Joint Sequence(1D)-Fold(3D) Embedding-based Generative Model for Protein Design. | Yue Cao, Payel Das, Vijil Chenthamarakshan, Pin-Yu Chen, Igor Melnyk, Yang Shen |
| 2021 | ISIT | Active Binary Classification of Random Fields. | Arpan Mukherjee, Ali Tajer, Pin-Yu Chen, Payel Das |
| 2020 | ACL | Learning Implicit Text Generation via Feature Matching. | Inkit Padhi, Pierre L. Dognin, Ke Bai, Ccero Nogueira dos Santos, Vijil Chenthamarakshan, Youssef Mroueh, Payel Das |
| 2020 | EMNLP | DualTKB: A Dual Learning Bridge between Text and Knowledge Base. | Pierre L. Dognin, Igor Melnyk, Inkit Padhi, Ccero Nogueira dos Santos, Payel Das |
| 2020 | ICASSP | Improving Efficiency in Large-Scale Decentralized Distributed Training. | Wei Zhang, Xiaodong Cui, Abdullah Kayi, Mingrui Liu, Ulrich Finkler, Brian Kingsbury, George Saon, Youssef Mroueh, Alper Buyuktosunoglu, Payel Das, David S. Kung, Michael Picheny |
| 2020 | ICLR | Towards Better Understanding of Adaptive Gradient Algorithms in Generative Adversarial Nets. | Mingrui Liu, Youssef Mroueh, Jerret Ross, Wei Zhang, Xiaodong Cui, Payel Das, Tianbao Yang |
| 2020 | ICLR | Bridging Mode Connectivity in Loss Landscapes and Adversarial Robustness. | Pu Zhao, Pin-Yu Chen, Payel Das, Karthikeyan Natesan Ramamurthy, Xue Lin |
| 2020 | IJCAI | Toward a neuro-inspired creative decoder. | Payel Das, Brian Quanz, Pin-Yu Chen, Jae-wook Ahn, Dhruv Shah |
| 2020 | KDD | Combinatorial Black-Box Optimization with Expert Advice. | Hamid Dadkhahi, Karthikeyan Shanmugam, Jesus Rios, Payel Das, Samuel C. Hoffman, Troy David Loeffler, Subramanian Sankaranarayanan |
| 2019 | ICLR | Interactive Visual Exploration of Latent Space (IVELS) for peptide auto-encoder model selection. | Tom Sercu, Sebastian Gehrmann, Hendrik Strobelt, Payel Das, Inkit Padhi, Ccero Nogueira dos Santos, Kahini Wadhawan, Vijil Chenthamarakshan |