Papers by Robinson Piramuthu

2 papers
MDSEval: A Meta-Evaluation Benchmark for Multimodal Dialogue Summarization (2025.findings-emnlp)

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Challenge: Multimodal Dialogue Summarization (MDS) is a critical task with wide-ranging applications.
Approach: They propose a meta-evaluation benchmark for multimodal dialogue summarization based on image-sharing dialogues, corresponding summaries and human judgments .
Outcome: The proposed framework is the first to identify and formalize key evaluation dimensions specific to MDS.
VISITRON: Visual Semantics-Aligned Interactively Trained Object-Navigator (2022.findings-acl)

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Challenge: Interactive robots navigating photo-realistic environments need to be trained to handle dynamic nature of dialogue and vision-and-language navigation (VLN).
Approach: They propose a Transformer-based multi-modal navigator that is better suited to the interactive regime inherent to Cooperative Vision-and-Dialog Navigation (CVDN).
Outcome: The proposed model is trained to identify and associate object-level concepts and semantics between the environment and dialogue history and identify when to interact vs. navigate via imitation learning of a binary classification head.

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