1 citations · 1 across the 4 of their papers we have counts for
4 papers
Selective Self-Rehearsal: A Fine-Tuning Approach to Improve Generalization in Large Language Models
Sonam Gupta, Yatin Nandwani, Asaf Yehudai +4
Fine-tuning Large Language Models (LLMs) on specific datasets is a common practice to improve performance on target tasks. However, this performance gain often leads to overfitting…
Evaluating Robustness of Dialogue Summarization Models in the Presence of Naturally Occurring Variations
Ankita Gupta, Chulaka Gunasekara, Hui Wan +3
Dialogue summarization task involves summarizing long conversations while preserving the most salient information. Real-life dialogues often involve naturally occurring variations…
Evaluating Chatbots to Promote Users' Trust -- Practices and Open Problems
Biplav Srivastava, Kausik Lakkaraju, Tarmo Koppel +3
Chatbots, the common moniker for collaborative assistants, are Artificial Intelligence (AI) software that enables people to naturally interact with them to get tasks done. Although…
DG2: Data Augmentation Through Document Grounded Dialogue Generation
Qingyang Wu, Song Feng, Derek Chen +3
Collecting data for training dialog systems can be extremely expensive due to the involvement of human participants and need for extensive annotation. Especially in document-ground…