Papers by Himanshu Maheshwari
DynamicTOC: Persona-based Table of Contents for Consumption of Long Documents (2022.naacl-main)
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Himanshu Maheshwari, Nethraa Sivakumar, Shelly Jain, Tanvi Karandikar, Vinay Aggarwal, Navita Goyal, Sumit Shekhar
| Challenge: | Long documents are tedious to read through and can be authored by multiple entities . traditional document navigation is through a Table of Contents (ToC) but there is no way to highlight information relevant to different personas. |
| Approach: | They propose a dynamic table of content-based navigator that highlights sections of interest . DYNAMICTOC is augmented with short questions to assist users in understanding underlying content . |
| Outcome: | The proposed navigator highlights sections of interest in documents as per the aspects relevant to different personas. human and automatic evaluations suggest the efficacy of both end-to-end pipeline and different components. |
Presentations are not always linear! GNN meets LLM for Text Document-to-Presentation Transformation with Attribution (2024.findings-emnlp)
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| Challenge: | Existing approaches to generate presentations from document to slide are difficult to implement and cause hallucination. |
| Approach: | They propose a graph-based solution that uses a combination of graph neural network and LLM to generate a presentation with attribution of content for each slide. |
| Outcome: | The proposed approach is more efficient than using LLMs for generating a presentation from the text of a document. |
Open-World Factually Consistent Question Generation (2023.findings-acl)
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| Challenge: | Existing methods for question generation suffer from factual inconsistencies and incorrect entities and are not answerable from the input paragraph. |
| Approach: | They propose a data processing technique based on de-lexicalization for consistent question generation across domains and a model that is generic across question-generation models. |
| Outcome: | The proposed method produces entity-level factually consistent questions without significant impact on traditional metrics. |