Papers by Anutosh Maitra

5 papers
Persona or Context? Towards Building Context adaptive Personalized Persuasive Virtual Sales Assistant (2022.aacl-main)

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Challenge: Existing task-oriented conversational agents assume that end-users will always have a pre-determined and servable task goal, which results in dialogue failure in hostile scenarios, such as goal unavailability.
Approach: They propose to build an end-to-end multi-modal persuasive dialogue system incorporating a personalized persuasive module aided goal controller and goal persuader.
Outcome: The proposed system achieves user tasks even in goal unavailability scenarios by persuading them towards a similar and servable goal.
INA: An Integrative Approach for Enhancing Negotiation Strategies with Reward-Based Dialogue Agent (2023.findings-emnlp)

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Challenge: a novel negotiation agent is designed for the online marketplace . a dialogue agent can negotiate on price and other factors .
Approach: They propose a novel negotiation agent that is integrative in nature and can negotiate on price and other factors.
Outcome: The proposed agent is integrative in nature and can negotiate on price and other factors.
Hollywood Identity Bias Dataset: A Context Oriented Bias Analysis of Movie Dialogues (2022.lrec-1)

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Challenge: Movies reflect society and also hold power to transform opinions.
Approach: They propose to annotate movie scripts for identity bias using a dataset that is annotated for gender, race/ethnicity, religion, age, occupation, LGBTQ, and other .
Outcome: The proposed dataset contains dialogue turns annotated for gender, race/ethnicity, religion, age, occupation, LGBTQ, and other, which contains biases like body shaming, personality bias, etc.
TRIP NEGOTIATOR: A Travel Persona-aware Reinforced Dialogue Generation Model for Personalized Integrative Negotiation in Tourism (2024.findings-emnlp)

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Challenge: Incorporating traveler preferences, constraints, and expectations allows for customizing negotiation strategies, resulting in a more personalized and integrative experience.
Approach: They propose a novel travel persona-aware Reinforced dIalogue generation model for personalized integrative negotiation in the tourism domain.
Outcome: The proposed system generates coherent and diverse responses consistent with the traveler's personality.
Can Taxonomy Help? Improving Semantic Question Matching using Question Taxonomy (C18-1)

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Challenge: Existing QA systems that answer factual questions with short answers are rare in practice.
Approach: They propose a proposed two-layered taxonomy technique for semantic question matching . they augment state-of-the-art deep learning models with question classes from a deep learning based question classifier .
Outcome: The proposed technique achieves state-of-the-art on an open-domain dataset.

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