Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Dey, Suvodip"'
Autor:
Dongre, Vardhan, Yang, Xiaocheng, Acikgoz, Emre Can, Dey, Suvodip, Tur, Gokhan, Hakkani-Tür, Dilek
Large language model (LLM)-based agents have been increasingly used to interact with external environments (e.g., games, APIs, etc.) and solve tasks. However, current frameworks do not enable these agents to work with users and interact with them to
Externí odkaz:
http://arxiv.org/abs/2411.00927
Estimation of a model's confidence on its outputs is critical for Conversational AI systems based on large language models (LLMs), especially for reducing hallucination and preventing over-reliance. In this work, we provide an exhaustive exploration
Externí odkaz:
http://arxiv.org/abs/2409.09629
Text Style Transfer (TST) is performable through approaches such as latent space disentanglement, cycle-consistency losses, prototype editing etc. The prototype editing approach, which is known to be quite successful in TST, involves two key phases a
Externí odkaz:
http://arxiv.org/abs/2210.06394
Long-range context modeling is crucial to both dialogue understanding and generation. The most popular method for dialogue context representation is to concatenate the last-$k$ utterances in chronological order. However, this method may not be ideal
Externí odkaz:
http://arxiv.org/abs/2210.06282
Recent studies show that auto-encoder based approaches successfully perform language generation, smooth sentence interpolation, and style transfer over unseen attributes using unlabelled datasets in a zero-shot manner. The latent space geometry of su
Externí odkaz:
http://arxiv.org/abs/2205.02309
Dialogue State Tracking (DST) is primarily evaluated using Joint Goal Accuracy (JGA) defined as the fraction of turns where the ground-truth dialogue state exactly matches the prediction. Generally in DST, the dialogue state or belief state for a giv
Externí odkaz:
http://arxiv.org/abs/2204.03375