Named-Entity-Recognition (NER) for Tamil Language Using Margin-Infused Relaxed Algorithm (MIRA). - Pranavan Theivendiram; Megala Uthayakumar; Nilusija Nadarasamoorthy; Mokanarangan Thayaparan; Sanath Jayasena; Gihan Dias; Surangika Ranathunga (CICLing (1), 2016)

Tamil Morphological Analyzer Using Support Vector Machines. - Mokanarangan Thayaparan; Pranavan Theivendiram; Megala Uthayakumar; Nilusija Nadarasamoorthy; Gihan Dias; Sanath Jayasena; Surangika Ranathunga (NLDB, 2016)

Graph Based Semi-Supervised Learning Approach for Tamil POS tagging. - Mokanarangan Thayaparan; Surangika Ranathunga; Uthayasanker Thayasivam (LREC, 2018)

Identifying Supporting Facts for Multi-hop Question Answering with Document Graph Networks. - Mokanarangan Thayaparan; Marco Valentino; Viktor Schlegel; André Freitas (TextGraphs@EMNLP, 2019)

Unification-based Reconstruction of Explanations for Science Questions. - Marco Valentino; Mokanarangan Thayaparan; André Freitas (CoRR, 2020)

Explainable Natural Language Reasoning via Conceptual Unification. - Marco Valentino; Mokanarangan Thayaparan; André Freitas (CoRR, 2020)

A Survey on Explainability in Machine Reading Comprehension. - Mokanarangan Thayaparan; Marco Valentino; André Freitas (CoRR, 2020)

ExplanationLP: Abductive Reasoning for Explainable Science Question Answering. - Mokanarangan Thayaparan; Marco Valentino; André Freitas (CoRR, 2020)

Does My Representation Capture X? Probe-Ably. - Deborah Ferreira; Julia Rozanova; Mokanarangan Thayaparan; Marco Valentino; André Freitas (ACL (demo), 2021)

Explainable Inference Over Grounding-Abstract Chains for Science Questions. - Mokanarangan Thayaparan; Marco Valentino; André Freitas (ACL/IJCNLP (Findings), 2021)

Unification-based Reconstruction of Multi-hop Explanations for Science Questions. - Marco Valentino; Mokanarangan Thayaparan; André Freitas (EACL, 2021)

Switching Contexts: Transportability Measures for NLP. - Guy Marshall; Mokanarangan Thayaparan; Philip Osborne; André Freitas (CoRR, 2021)

∂-Explainer: Abductive Natural Language Inference via Differentiable Convex Optimization. - Mokanarangan Thayaparan; Marco Valentino; Deborah Ferreira; Julia Rozanova; André Freitas (CoRR, 2021)

Supporting Context Monotonicity Abstractions in Neural NLI Models. - Julia Rozanova; Deborah Ferreira; Mokanarangan Thayaparan; Marco Valentino; André Freitas (CoRR, 2021)

Hybrid Autoregressive Solver for Scalable Abductive Natural Language Inference. - Marco Valentino; Mokanarangan Thayaparan; Deborah Ferreira; André Freitas (CoRR, 2021)

Hybrid Autoregressive Inference for Scalable Multi-Hop Explanation Regeneration. - Marco Valentino; Mokanarangan Thayaparan; Deborah Ferreira; André Freitas (AAAI, 2022)

To be or not to be an Integer? Encoding Variables for Mathematical Text. - Deborah Ferreira; Mokanarangan Thayaparan; Marco Valentino; Julia Rozanova; André Freitas (ACL (Findings), 2022)

Decomposing Natural Logic Inferences for Neural NLI. - Julia Rozanova; Deborah Ferreira; Mokanarangan Thayaparan; Marco Valentino; André Freitas (BlackboxNLP@EMNLP, 2022)

Case-Based Abductive Natural Language Inference. - Marco Valentino; Mokanarangan Thayaparan; André Freitas (COLING, 2022)

Going Beyond Approximation: Encoding Constraints for Explainable Multi-hop Inference via Differentiable Combinatorial Solvers. - Mokanarangan Thayaparan; Marco Valentino; André Freitas (CoRR, 2022)

Diff-Explainer: Differentiable Convex Optimization for Explainable Multi-hop Inference. - Mokanarangan Thayaparan; Marco Valentino; Deborah Ferreira; Julia Rozanova; André Freitas (Trans. Assoc. Comput. Linguistics, 2022)

A Differentiable Integer Linear Programming Solver for Explanation-Based Natural Language Inference. - Mokanarangan Thayaparan; Marco Valentino; André Freitas (LREC/COLING, 2024)

Utilizing Multilingual Encoders to Improve Large Language Models for Low-Resource Languages. - Imalsha Puranegedara; Themira Chathumina; Nisal Ranathunga; Nisansa de Silva; Surangika Ranathunga; Mokanarangan Thayaparan (CoRR, 2025)