Volume preserving haptic pottery. - Subhajit Chaudhury; Subhasis Chaudhuri (HAPTICS, 2014)

Vision Based Human Pose Estimation for Virtual Cloth Fitting. - Sourav Saha 003; Pritha Ganguly; Subhajit Chaudhury (ICVGIP, 2014)

Text to image generative model using constrained embedding space mapping. - Subhajit Chaudhury; Sakyasingha Dasgupta; Asim Munawar; Md. A. Salam Khan; Ryuki Tachibana (MLSP, 2017)

Can fully convolutional networks perform well for general image restoration problems? - Subhajit Chaudhury; Hiya Roy (MVA, 2017)

Spatial-Temporal Motion Field Analysis for Pixelwise Crack Detection on Concrete Surfaces. - Subhajit Chaudhury; Gaku Nakano; Jun Takada; Akihiko Iketani (WACV, 2017)

Conditional generation of multi-modal data using constrained embedding space mapping. - Subhajit Chaudhury; Sakyasingha Dasgupta; Asim Munawar; Md. A. Salam Khan; Ryuki Tachibana (CoRR, 2017)

Transfer learning from synthetic to real images using variational autoencoders for robotic applications. - Tadanobu Inoue; Subhajit Chaudhury; Giovanni De Magistris; Sakyasingha Dasgupta (CoRR, 2017)

Transfer Learning from Synthetic to Real Images Using Variational Autoencoders for Precise Position Detection. - Tadanobu Inoue; Subhajit Chaudhury; Giovanni De Magistris; Sakyasingha Dasgupta (ICIP, 2018)

Focusing on What is Relevant: Time-Series Learning and Understanding using Attention. - Phongtharin Vinayavekhin; Subhajit Chaudhury; Asim Munawar; Don Joven Agravante; Giovanni De Magistris; Daiki Kimura; Ryuki Tachibana (ICPR, 2018)

Internal Model from Observations for Reward Shaping. - Daiki Kimura; Subhajit Chaudhury; Ryuki Tachibana; Sakyasingha Dasgupta (CoRR, 2018)

Constrained Exploration and Recovery from Experience Shaping. - Tu-Hoa Pham; Giovanni De Magistris; Don Joven Agravante; Subhajit Chaudhury; Asim Munawar; Ryuki Tachibana (CoRR, 2018)

Video Imitation GAN: Learning control policies by imitating raw videos using generative adversarial reward estimation. - Subhajit Chaudhury; Daiki Kimura; Tu-Hoa Pham; Asim Munawar; Ryuki Tachibana (CoRR, 2018)

Unsupervised Temporal Feature Aggregation for Event Detection in Unstructured Sports Videos. - Subhajit Chaudhury; Hiroki Ozaki; Daiki Kimura; Phongtharin Vinayavekhin; Asim Munawar; Ryuki Tachibana; Koji Ito; Yuki Inaba; Minoru Matsumoto; Shuji Kidokoro (ISM, 2019)

Injective State-Image Mapping facilitates Visual Adversarial Imitation Learning. - Subhajit Chaudhury; Daiki Kimura; Asim Munawar; Ryuki Tachibana (MMSP, 2019)

Lunar surface image restoration using U-net based deep neural networks. - Hiya Roy; Subhajit Chaudhury; Toshihiko Yamasaki; Danielle DeLatte; Makiko Ohtake; Tatsuaki Hashimoto (CoRR, 2019)

Understanding Generalization in Neural Networks for Robustness against Adversarial Vulnerabilities. - Subhajit Chaudhury (AAAI, 2020)

Bootstrapped Q-learning with Context Relevant Observation Pruning to Generalize in Text-based Games. - Subhajit Chaudhury; Daiki Kimura; Kartik Talamadupula; Michiaki Tatsubori; Asim Munawar; Ryuki Tachibana (EMNLP (1), 2020)

Investigating Generalization in Neural Networks Under Optimally Evolved Training Perturbations. - Subhajit Chaudhury; Toshihiko Yamasaki (ICASSP, 2020)

Adversarial Discriminative Attention for Robust Anomaly Detection. - Daiki Kimura; Subhajit Chaudhury; Minori Narita; Asim Munawar; Ryuki Tachibana (WACV, 2020)

Assessing Robustness of Deep learning Methods in Dermatological Workflow. - Sourav Mishra; Subhajit Chaudhury; Hideaki Imaizumi; Toshihiko Yamasaki (CoRR, 2020)

VisualHints: A Visual-Lingual Environment for Multimodal Reinforcement Learning. - Thomas Carta; Subhajit Chaudhury; Kartik Talamadupula; Michiaki Tatsubori (CoRR, 2020)

LOA: Logical Optimal Actions for Text-based Interaction Games. - Daiki Kimura; Subhajit Chaudhury; Masaki Ono; Michiaki Tatsubori; Don Joven Agravante; Asim Munawar; Akifumi Wachi; Ryosuke Kohita; Alexander Gray 001 (ACL (demo), 2021)

Language-based General Action Template for Reinforcement Learning Agents. - Ryosuke Kohita; Akifumi Wachi; Daiki Kimura; Subhajit Chaudhury; Michiaki Tatsubori; Asim Munawar (ACL/IJCNLP (Findings), 2021)

Neuro-Symbolic Approaches for Text-Based Policy Learning. - Subhajit Chaudhury; Prithviraj Sen; Masaki Ono; Daiki Kimura; Michiaki Tatsubori; Asim Munawar (EMNLP (1), 2021)

Neuro-Symbolic Reinforcement Learning with First-Order Logic. - Daiki Kimura; Masaki Ono; Subhajit Chaudhury; Ryosuke Kohita; Akifumi Wachi; Don Joven Agravante; Michiaki Tatsubori; Asim Munawar; Alexander Gray 001 (EMNLP (1), 2021)

Adversarial Training Time Attack Against Discriminative and Generative Convolutional Models. - Subhajit Chaudhury; Hiya Roy; Sourav Mishra; Toshihiko Yamasaki (IEEE Access, 2021)

Robustness of Adaptive Neural Network Optimization Under Training Noise. - Subhajit Chaudhury; Toshihiko Yamasaki (IEEE Access, 2021)

Reinforcement Learning with External Knowledge by using Logical Neural Networks. - Daiki Kimura; Subhajit Chaudhury; Akifumi Wachi; Ryosuke Kohita; Asim Munawar; Michiaki Tatsubori; Alexander Gray 001 (CoRR, 2021)

Robustness of Deep Learning Models in Dermatological Evaluation: A Critical Assessment. - Sourav Mishra; Subhajit Chaudhury; Hideaki Imaizumi; Toshihiko Yamasaki (IEICE Trans. Inf. Syst., 2021)

Image inpainting using frequency-domain priors. - Hiya Roy; Subhajit Chaudhury; Toshihiko Yamasaki; Tatsuaki Hashimoto (J. Electronic Imaging, 2021)

Toward Better Planetary Surface Exploration by Orbital Imagery Inpainting. - Hiya Roy; Subhajit Chaudhury; Toshihiko Yamasaki; Tatsuaki Hashimoto (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2021)

Eye of the Beholder: Improved Relation Generalization for Text-Based Reinforcement Learning Agents. - Keerthiram Murugesan; Subhajit Chaudhury; Kartik Talamadupula (AAAI, 2022)

X-FACTOR: A Cross-metric Evaluation of Factual Correctness in Abstractive Summarization. - Subhajit Chaudhury; Sarathkrishna Swaminathan; R. Chulaka Gunasekara; Maxwell Crouse; Srinivas Ravishankar; Daiki Kimura; Keerthiram Murugesan; Ramón Fernandez Astudillo; Tahira Naseem; Pavan Kapanipathi; Alexander Gray 001 (EMNLP, 2022)

Mitigating Gradient Bias in Multi-objective Learning: A Provably Convergent Stochastic Approach. - Heshan Devaka Fernando; Han Shen; Miao Liu 001; Subhajit Chaudhury; Keerthiram Murugesan; Tianyi Chen (CoRR, 2022)

Learning Symbolic Rules over Abstract Meaning Representations for Textual Reinforcement Learning. - Subhajit Chaudhury; Sarathkrishna Swaminathan; Daiki Kimura; Prithviraj Sen; Keerthiram Murugesan; Rosario Uceda-Sosa; Michiaki Tatsubori; Achille Fokoue; Pavan Kapanipathi; Asim Munawar; Alexander Gray 001 (ACL (1), 2023)

Laziness Is a Virtue When It Comes to Compositionality in Neural Semantic Parsing. - Maxwell Crouse; Pavan Kapanipathi; Subhajit Chaudhury; Tahira Naseem; Ramón Fernandez Astudillo; Achille Fokoue; Tim Klinger (ACL (1), 2023)

MISMATCH: Fine-grained Evaluation of Machine-generated Text with Mismatch Error Types. - Keerthiram Murugesan; Sarathkrishna Swaminathan; Soham Dan; Subhajit Chaudhury; R. Chulaka Gunasekara; Maxwell Crouse; Diwakar Mahajan; Ibrahim Abdelaziz; Achille Fokoue; Pavan Kapanipathi; Salim Roukos; Alexander Gray 001 (ACL (Findings), 2023)

Self-Supervised Rule Learning to Link Text Segments to Relational Elements of Structured Knowledge. - Shajith Ikbal; Udit Sharma; Hima Karanam; Sumit Neelam; Ronny Luss; Dheeraj Sreedhar; Pavan Kapanipathi; Naweed Khan; Kyle Erwin; Ndivhuwo Makondo; Ibrahim Abdelaziz; Achille Fokoue; et al. (EMNLP (Findings), 2023)

Mitigating Gradient Bias in Multi-objective Learning: A Provably Convergent Approach. - Heshan Devaka Fernando; Han Shen; Miao Liu 001; Subhajit Chaudhury; Keerthiram Murugesan; Tianyi Chen (ICLR, 2023)

On the Convergence and Sample Complexity Analysis of Deep Q-Networks with ε-Greedy Exploration. - Shuai Zhang 015; Hongkang Li; Meng Wang 003; Miao Liu 001; Pin-Yu Chen; Songtao Lu; Sijia Liu 001; Keerthiram Murugesan; Subhajit Chaudhury (NeurIPS, 2023)

Scalable Learning of Latent Language Structure With Logical Offline Cycle Consistency. - Maxwell Crouse; Ramón Fernandez Astudillo; Tahira Naseem; Subhajit Chaudhury; Pavan Kapanipathi; Salim Roukos; Alexander Gray 001 (CoRR, 2023)

LakeBench: Benchmarks for Data Discovery over Data Lakes. - Kavitha Srinivas; Julian Dolby; Ibrahim Abdelaziz; Oktie Hassanzadeh; Harsha Kokel; Aamod Khatiwada; Tejaswini Pedapati; Subhajit Chaudhury; Horst Samulowitz (CoRR, 2023)

API-BLEND: A Comprehensive Corpora for Training and Benchmarking API LLMs. - Kinjal Basu 002; Ibrahim Abdelaziz; Subhajit Chaudhury; Soham Dan; Maxwell Crouse; Asim Munawar; Vernon Austel; Sadhana Kumaravel; Vinod Muthusamy; Pavan Kapanipathi; Luis A. Lastras (ACL (1), 2024)

A Grounded Preference Model for LLM Alignment. - Tahira Naseem; Guangxuan Xu; Sarathkrishna Swaminathan; Asaf Yehudai; Subhajit Chaudhury; Radu Florian; Ramón Fernandez Astudillo; Asim Munawar (ACL (Findings), 2024)

EXPLORER: Exploration-guided Reasoning for Textual Reinforcement Learning. - Kinjal Basu 002; Keerthiram Murugesan; Subhajit Chaudhury; Murray Campbell; Kartik Talamadupula; Tim Klinger (EACL (1), 2024)

Leveraging Visual Handicaps for Text-Based Reinforcement Learning. - Subhajit Chaudhury; Keerthiram Murugesan; Thomas Carta; Kartik Talamadupula; Michiaki Tatsubori (ICASSP, 2024)

Adversarial Robustness of Convolutional Models Learned in the Frequency Domain. - Subhajit Chaudhury; Toshihiko Yamasaki (ICASSP, 2024)

Variance Reduction Can Improve Trade-Off in Multi-Objective Learning. - Heshan Devaka Fernando; Lisha Chen; Songtao Lu; Pin-Yu Chen; Miao Liu 001; Subhajit Chaudhury; Keerthiram Murugesan; Gaowen Liu; Meng Wang 003; Tianyi Chen (ICASSP, 2024)

Larimar: Large Language Models with Episodic Memory Control. - Payel Das; Subhajit Chaudhury; Elliot Nelson; Igor Melnyk; Sarathkrishna Swaminathan; Sihui Dai; Aurélie C. Lozano; Georgios Kollias; Vijil Chenthamarakshan; Jirí Navrátil 001; Soham Dan; Pin-Yu Chen (ICML, 2024)

API-BLEND: A Comprehensive Corpora for Training and Benchmarking API LLMs. - Kinjal Basu 002; Ibrahim Abdelaziz; Subhajit Chaudhury; Soham Dan; Maxwell Crouse; Asim Munawar; Sadhana Kumaravel; Vinod Muthusamy; Pavan Kapanipathi; Luis A. Lastras (CoRR, 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)

Larimar: Large Language Models with Episodic Memory Control. - Payel Das; Subhajit Chaudhury; Elliot Nelson; Igor Melnyk; Sarath Swaminathan; Sihui Dai; Aurélie C. Lozano; Georgios Kollias; Vijil Chenthamarakshan; Jirí Navrátil 001; Soham Dan; Pin-Yu Chen (CoRR, 2024)

Needle in the Haystack for Memory Based Large Language Models. - Elliot Nelson; Georgios Kollias; Payel Das; Subhajit Chaudhury; Soham Dan (CoRR, 2024)

Generation Constraint Scaling Can Mitigate Hallucination. - Georgios Kollias; Payel Das; Subhajit Chaudhury (CoRR, 2024)

Large Language Models can be Strong Self-Detoxifiers. - Ching-Yun Ko; Pin-Yu Chen; Payel Das; Youssef Mroueh; Soham Dan; Georgios Kollias; Subhajit Chaudhury; Tejaswini Pedapati; Luca Daniel (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)

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 (ACL (1), 2025)

On the Effects of Fine-tuning Language Models for Text-Based Reinforcement Learning. - Maurício Gruppi; Soham Dan; Keerthiram Murugesan; Subhajit Chaudhury (COLING, 2025)

TabSketchFM: Sketch-Based Tabular Representation Learning for Data Discovery Over Data Lakes. - Aamod Khatiwada; Harsha Kokel; Ibrahim Abdelaziz; Subhajit Chaudhury; Julian Dolby; Oktie Hassanzadeh; Zhenhan Huang; Tejaswini Pedapati; Horst Samulowitz; Kavitha Srinivas (ICDE, 2025)

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 (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)

Sparse Gradient Compression for Fine-Tuning Large Language Models. - David H. Yang; Mohammad Mohammadi Amiri; Tejaswini Pedapati; Subhajit Chaudhury; Pin-Yu Chen (CoRR, 2025)

Can Memory-Augmented Language Models Generalize on Reasoning-in-a-Haystack Tasks? - Payel Das; Ching-Yun Ko; Sihui Dai; Georgios Kollias; Subhajit Chaudhury; Aurélie C. Lozano (CoRR, 2025)

LongFuncEval: Measuring the effectiveness of long context models for function calling. - Kiran Kate; Tejaswini Pedapati; Kinjal Basu 002; Yara Rizk; Vijil Chenthamarakshan; Subhajit Chaudhury; Mayank Agarwal; Ibrahim Abdelaziz (CoRR, 2025)