Papers by Hitesh Golchha

2 papers
Courteously Yours: Inducing courteous behavior in Customer Care responses using Reinforced Pointer Generator Network (N19-1)

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Challenge: In order to ensure customer satisfaction and retention, it is imperative for customer care agents and chatbots to be cordial and emphatic to the customer.
Approach: They propose a deep learning framework that automatically transforms neutral customer care responses into courteous replies by stylistic transfer.
Outcome: The proposed model can generate courteous expressions consistent with the emotional state of the customer while preserving the content.
Language Guided Exploration for RL Agents in Text Environments (2024.findings-naacl)

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Challenge: Real-world sequential decision making is characterized by sparse rewards and large decision spaces.
Approach: They introduce a language-based framework that provides decision-level guidance to an RL agent.
Outcome: The proposed framework outperforms vanilla RL agents on ScienceWorld in 2022.

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