| 2026 | ACIIDS | An Empirical Study of the Role of Incompleteness and Ambiguity in Interactions with Large Language Models. | Riya Naik, Ashwin Srinivasan, Swati Agarwal, Estrid He |
| 2026 | CaiSE | Engineering Systems for Data Analysis Using Interactive Structured Inductive Programming. | Shraddha Surana, Ashwin Srinivasan, Michael Bain |
| 2026 | ICAART | Agent-Based Detection and Resolution of Incompleteness and Ambiguity in Interactions with Large Language Models. | Riya Naik, Ashwin Srinivasan, Swati Agarwal, Estrid He |
| 2026 | ICAART | Characterization and Detection of Incompleteness and Ambiguity in Multi-Turn Interactions with LLMs. | Riya Naik, Ashwin Srinivasan, Swati Agarwal, Estrid He |
| 2025 | NAACL | Concept Distillation from Strong to Weak Models via Hypotheses-to-Theories Prompting. | Emmanuel Aboah Boateng, Cassiano O. Becker, Nabiha Asghar, Kabir Walia, Ashwin Srinivasan, Ehi Nosakhare, Soundar Srinivasan, Victor Dibia |
| 2025 | PERCOM | Accelerating Medical Image Analysis on Edge Devices: A Study with MobileOne Architecture. | Dev Gala, Jinam Keniya, Harsha Varun Marisetty, Manik Gupta, Tanmay Tulsidas Verlekar, Erik Meijering, Ashwin Srinivasan |
| 2024 | AAAI | Generating Novel Leads for Drug Discovery Using LLMs with Logical Feedback. | Shreyas Bhat Brahmavar, Ashwin Srinivasan, Tirtharaj Dash, Sowmya Ramaswamy Krishnan, Lovekesh Vig, Arijit Roy, Raviprasad Aduri |
| 2023 | ICIP | IKD+: Reliable Low Complexity Deep Models for Retinopathy Classification. | Shreyas Bhat Brahmavar, Rohit Rajesh, Tirtharaj Dash, Lovekesh Vig, Tanmay Tulsidas Verlekar, Md Mahmudul Hasan, Tariq Mahmood Khan, Erik Meijering, Ashwin Srinivasan |
| 2023 | IJCAI | Can LLMs solve generative visual analogies? | Shrey Pandit, Gautam Shroff, Ashwin Srinivasan, Lovekesh Vig |
| 2022 | AAAI | Solving Visual Analogies Using Neural Algorithmic Reasoning (Student Abstract). | Atharv Sonwane, Gautam Shroff, Lovekesh Vig, Ashwin Srinivasan, Tirtharaj Dash |
| 2022 | ACL | Zero-Shot Dense Retrieval with Momentum Adversarial Domain Invariant Representations. | Ji Xin, Chenyan Xiong, Ashwin Srinivasan, Ankita Sharma, Damien Jose, Paul Bennett |
| 2022 | ILP | A Program-Synthesis Challenge for ARC-Like Tasks. | Aditya Challa, Ashwin Srinivasan, Michael Bain, Gautam Shroff |
| 2022 | NeSy | Knowledge-based Analogical Reasoning in Neuro-symbolic Latent Spaces. | Vishwa Shah, Aditya Sharma, Gautam Shroff, Lovekesh Vig, Tirtharaj Dash, Ashwin Srinivasan |
| 2021 | ICANN | Empirical Study of Data-Free Iterative Knowledge Distillation. | Het Shah, Ashwin Vaswani, Tirtharaj Dash, Ramya Hebbalaguppe, Ashwin Srinivasan |
| 2021 | ILP | Using Domain-Knowledge to Assist Lead Discovery in Early-Stage Drug Design. | Tirtharaj Dash, Ashwin Srinivasan, Lovekesh Vig, Arijit Roy |
| 2020 | CVPR | Information Extraction from Document Images via FCA based Template Detection and Knowledge Graph Rule Induction. | Mouli Rastogi, Syed Afshan Ali, Mrinal Rawat, Lovekesh Vig, Puneet Agarwal, Gautam Shroff, Ashwin Srinivasan |
| 2020 | ESANN | An Empirical Study of Iterative Knowledge Distillation for Neural Network Compression. | Sharan Yalburgi, Tirtharaj Dash, Ramya Hebbalaguppe, Srinidhi Hegde, Ashwin Srinivasan |
| 2020 | MICCAI | A Case Study of Transfer of Lesion-Knowledge. | Soundarya Krishnan, Rishab Khincha, Lovekesh Vig, Tirtharaj Dash, Ashwin Srinivasan |
| 2020 | MICCAI | CovidDiagnosis: Deep Diagnosis of COVID-19 Patients Using Chest X-Rays. | Kushagra Mahajan, Monika Sharma, Lovekesh Vig, Rishab Khincha, Soundarya Krishnan, Adithya Niranjan, Tirtharaj Dash, Ashwin Srinivasan, Gautam Shroff |
| 2019 | ICANN | Discrete Stochastic Search and Its Application to Feature-Selection for Deep Relational Machines. | Tirtharaj Dash, Ashwin Srinivasan, Ramprasad S. Joshi, A. Baskar |
| 2019 | NeSy | One-shot Information Extraction from Document Images using Neuro-Deductive Program Synthesis. | Vishal Sunder, Ashwin Srinivasan, Lovekesh Vig, Gautam Shroff, Rohit Rahul |
| 2018 | ACCV | Deep Reader: Information Extraction from Document Images via Relation Extraction and Natural Language. | Vishwanath D, Rohit Rahul, Gunjan Sehgal, Swati, Arindam Chowdhury, Monika Sharma, Lovekesh Vig, Gautam Shroff, Ashwin Srinivasan |
| 2018 | ESANN | Evolutionary RL for Container Loading. | Sarmimala Saikia, Richa Verma, Puneet Agarwal, Gautam Shroff, Lovekesh Vig, Ashwin Srinivasan |
| 2018 | ILP | Large-Scale Assessment of Deep Relational Machines. | Tirtharaj Dash, Ashwin Srinivasan, Lovekesh Vig, Oghenejokpeme I. Orhobor, Ross D. King |
| 2017 | CIKM | Hybrid BiLSTM-Siamese network for FAQ Assistance. | Prerna Khurana, Puneet Agarwal, Gautam Shroff, Lovekesh Vig, Ashwin Srinivasan |
| 2017 | ILP | An Investigation into the Role of Domain-Knowledge on the Use of Embeddings. | Lovekesh Vig, Ashwin Srinivasan, Michael Bain, Ankit Verma |
| 2016 | ILP | Generation of Near-Optimal Solutions Using ILP-Guided Sampling. | Ashwin Srinivasan, Gautam Shroff, Lovekesh Vig, Sarmimala Saikia |
| 2015 | DSAA | Succinctly summarizing machine usage via multi-subspace clustering of multi-sensor data. | Sarmimala Saikia, Gautam Shroff, Puneet Agarwal, Ashwin Srinivasan |
| 2015 | ILP | Identification of Transition Models of Biological Systems in the Presence of Transition Noise. | Ashwin Srinivasan, Michael Bain, Deepika Vatsa, Sumeet Agarwal |
| 2014 | COMAD | Exploratory Data Analysis Using Alternating Covers of Rules and Exceptions. | Sarmimala Saikia, Gautam Shroff, Puneet Agarwal, Ashwin Srinivasan, Aditeya Pandey, Gaurangi Anand |
| 2012 | ILP | Topic Models with Relational Features for Drug Design. | Tanveer A. Faruquie, Ashwin Srinivasan, Ross D. King |
| 2012 | ILP | What Kinds of Relational Features Are Useful for Statistical Learning? | Amrita Saha, Ashwin Srinivasan, Ganesh Ramakrishnan |
| 2011 | ILP | Knowledge-Guided Identification of Petri Net Models of Large Biological Systems. | Ashwin Srinivasan, Michael Bain |
| 2010 | ILP | BET : An Inductive Logic Programming Workbench. | Srihari Kalgi, Chirag Gosar, Prasad Gawde, Ganesh Ramakrishnan, Kekin Gada, Chander Iyer, T. V. S. Kiran, Ashwin Srinivasan |
| 2009 | ILP | Parameter Screening and Optimisation for ILP Using Designed Experiments. | Ashwin Srinivasan, Ganesh Ramakrishnan |
| 2008 | ILP | Feature Construction Using Theory-Guided Sampling and Randomised Search. | Sachindra Joshi, Ganesh Ramakrishnan, Ashwin Srinivasan |
| 2007 | ILP | Using ILP to Construct Features for Information Extraction from Semi-structured Text. | Ganesh Ramakrishnan, Sachindra Joshi, Sreeram Balakrishnan, Ashwin Srinivasan |
| 2006 | ILP | ILP Through Propositionalization and Stochastic k-Term DNF Learning. | Aline Paes, Filip Zelezn, Gerson Zaverucha, C. David Page Jr., Ashwin Srinivasan |
| 2006 | ILP | Word Sense Disambiguation Using Inductive Logic Programming. | Lucia Specia, Ashwin Srinivasan, Ganesh Ramakrishnan, Maria das Graas Volpe Nunes |
| 2005 | ICML | Multi-instance tree learning. | Hendrik Blockeel, David Page, Ashwin Srinivasan |
| 2005 | ILP | Five Problems in Five Areas for Five Years. | Ashwin Srinivasan |
| 2005 | ILP | A Study of Applying Dimensionality Reduction to Restrict the Size of a Hypothesis Space. | Ashwin Srinivasan, Ravi Kothari |
| 2004 | ILP | A Monte Carlo Study of Randomised Restarted Search in ILP. | Filip Zelezn, Ashwin Srinivasan, David Page |
| 2002 | ILP | The Applicability to ILP of Results Concerning the Ordering of Binomial Populations. | Ashwin Srinivasan |
| 2002 | ILP | Lattice-Search Runtime Distributions May Be Heavy-Tailed. | Filip Zelezn, Ashwin Srinivasan, David Page |
| 2000 | ICML | Learning Chomsky-like Grammars for Biological Sequence Families. | Stephen H. Muggleton, Christopher H. Bryant, Ashwin Srinivasan |
| 2000 | ICML | Discovering the Structure of Partial Differential Equations from Example Behaviour. | Ljupco Todorovski, Saso Dzeroski, Ashwin Srinivasan, Jonathan P. Whiteley, David Gavaghan |
| 2000 | ILP | A Note on Two Simple Transformations for Improving the Efficiency of an ILP System. | Vtor Santos Costa, Ashwin Srinivasan, Rui Camacho |
| 1999 | IJCAI | An assessment of submissions made to the Predictive Toxicology Evaluation Challenge. | Ashwin Srinivasan, Ross D. King, Douglas W. Bristol |
| 1999 | ILP | An Assessment of ILP-Assisted Models for Toxicology and the PTE-3 Experiment. | Ashwin Srinivasan, Ross D. King, Douglas W. Bristol |
| 1998 | DIS | Biochemical Knowledge Discovery Using Inductive Logic Programming. | Stephen H. Muggleton, Ashwin Srinivasan, Ross D. King, Michael J. E. Sternberg |
| 1998 | ILP | Application of ILP to Problems in Chemistry and Biology (Abstract). | Ashwin Srinivasan |
| 1997 | IJCAI | The Predictive Toxicology Evaluation Challenge. | Ashwin Srinivasan, Ross D. King, Stephen H. Muggleton, Michael J. E. Sternberg |
| 1997 | ILP | Carcinogenesis Predictions Using ILP. | Ashwin Srinivasan, Ross D. King, Stephen H. Muggleton, Michael J. E. Sternberg |
| 1996 | ILP | An Initial Experiment into Stereochemistry-Based Drug Design Using Inductive Logic Programming. | Stephen H. Muggleton, David Page, Ashwin Srinivasan |
| 1996 | ILP | Feature Construction with Inductive Logic Programming: A Study of Quantitative Predictions of Biological Activity by Structural Attributes. | Ashwin Srinivasan, Ross D. King |
| 1993 | AAAI | Generating Explicit Orderings for Non-monotonic Logics. | James Cussens, Anthony Hunter, Ashwin Srinivasan |
| 1992 | ICML | Compression, Significance, and Accuracy. | Stephen H. Muggleton, Ashwin Srinivasan, Michael Bain |