most citedTowards a Neural Era in Dialogue Management for Collaboration: A Literature Survey

1 citations · 2 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL2024

Making Task-Oriented Dialogue Datasets More Natural by Synthetically Generating Indirect User Requests

Amogh Mannekote, Jinseok Nam, Ziming Li +3

Indirect User Requests (IURs), such as "It's cold in here" instead of "Could you please increase the temperature?" are common in human-human task-oriented dialogue and require worl…

cs.CL2024

Towards Compositionally Generalizable Semantic Parsing in Large Language Models: A Survey

Amogh Mannekote

Compositional generalization is the ability of a model to generalize to complex, previously unseen types of combinations of entities from just having seen the primitives. This type…

cs.CL2024

Can Similarity-Based Domain-Ordering Reduce Catastrophic Forgetting for Intent Recognition?

Amogh Mannekote, Xiaoyi Tian, Kristy Elizabeth Boyer +1

Task-oriented dialogue systems are expected to handle a constantly expanding set of intents and domains even after they have been deployed to support more and more functionalities.…

cs.CL20231 cited

Towards a Neural Era in Dialogue Management for Collaboration: A Literature Survey

Amogh Mannekote

Dialogue-based human-AI collaboration can revolutionize collaborative problem-solving, creative exploration, and social support. To realize this goal, the development of automated…

cs.CL20231 cited

Agreement Tracking for Multi-Issue Negotiation Dialogues

Amogh Mannekote, Bonnie J. Dorr, Kristy Elizabeth Boyer

Automated negotiation support systems aim to help human negotiators reach more favorable outcomes in multi-issue negotiations (e.g., an employer and a candidate negotiating over is…