http://repository.iiitd.edu.in/xmlui/handle/123456789/1722 Year-2024 2026-05-05T12:40:59Z http://repository.iiitd.edu.in/xmlui/handle/123456789/1963 Knowledge graph distillation Narotam, N; Kaif, Mohammad; Akhter, Md. Shad (Advisor); Mutharaju, Raghava (Advisor) We combine domain-specific knowledge graphs with general knowledge graphs to enrich a language model. The objective of this semester was to implement baselines, test var- ious previous literature surveyed, and try to formulate what works. We develop a test hypothesis and plan to evaluate our proposed solutions. We try to investigate various tasks across domains to test our solution and its generalizability Keywords: Knowledge 2024-11-27T00:00:00Z http://repository.iiitd.edu.in/xmlui/handle/123456789/1961 Consistent vision: exploring multi-domain applications of consistency models Bhagat, Amil; Jain, Milind; Subramanyam, A V (Advisor) This project focuses on leveraging consistency models for downstream tasks involving the trans- lation and mapping between different modalities, such as converting visible images to their corresponding infrared representations. By utilizing paired data for training, the model learns a robust mapping that preserves essential features across modalities. The ultimate goal is to build a model capable of generating accurate outputs in the target domain (e.g., infrared) from inputs in the source domain (e.g., visible), enabling practical applications in domains like imaging, vision enhancement, and modality transformation while showcasing the potential of consistency models for cross-domain learning tasks. 2024-05-01T00:00:00Z http://repository.iiitd.edu.in/xmlui/handle/123456789/1960 Non - rigid motion transfer between non - isometric 3D bodies Pandey, Daksh; Sharma, Ojaswa (Advisor) This paper explores the problem of motion transfer between 3D non-isometric shapes. The re- search addresses the challenge of transferring motion between shapes that do not share identical geometric properties, which is often encountered in real-world scenarios. The project outlines a pipeline involving shape matching and motion transfer. The literature review reveals key ad- vancements and gaps in the field, while the proposed framework aims to contribute new method- ologies for handling complex transformations. The project is partially implemented, with shape matching algorithms defined, while the motion transfer pipeline is under development. 2024-11-27T00:00:00Z http://repository.iiitd.edu.in/xmlui/handle/123456789/1959 Ontology reasoning in EL++ Chawla, Jessica Kaur; Mutharaju, Raghava (Advisor) The project builds upon existing research that has investigated the reasoning capabilities of PLMs, primarily using RDFS rules. I aim to extend this work by incorporating the more expressive EL++ formalism, which potentially allows for more complex reasoning tasks. EL++ is chosen because it offers a balance between expressiveness and computational tractability. EL++ allows for the representation of complex relationships while ensuring that reasoning tasks can be performed effectively. 2024-11-27T00:00:00Z