Papers by Saar Kuzi
External Knowledge Acquisition for End-to-End Document-Oriented Dialog Systems (2023.eacl-main)
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| Challenge: | End-to-end neural models for conversational AI often assume that a response can be generated by considering only the knowledge acquired during training. |
| Approach: | They propose an architecture for document-oriented conversations with access to external knowledge sources. |
| Outcome: | The proposed architecture outperforms baseline models on the Wizard of Wikipedia dataset by 10.3% and 7.4%. |
Wizard of Tasks: A Novel Conversational Dataset for Solving Real-World Tasks in Conversational Settings (2022.coling-1)
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Jason Ingyu Choi, Saar Kuzi, Nikhita Vedula, Jie Zhao, Giuseppe Castellucci, Marcus Collins, Shervin Malmasi, Oleg Rokhlenko, Eugene Agichtein
| Challenge: | Existing Conversational Task Assistants fail to provide a comprehensive natural conversation that includes search, context-aware QA, step-by-step instructions. |
| Approach: | They present a corpus of conversations in two domains: cooking and home improvement . they crowd-sourced 549 conversations with an asynchronous Wizard-of-Oz setup . |
| Outcome: | The proposed model performs well in both Intent Classification and Abstractive Question Answering tasks, but the performance is poor on AQA tasks. |
Generative Product Recommendations for Implicit Superlative Queries (2025.naacl-srw)
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| Challenge: | Existing retrieval and ranking systems struggle with implicit superlative queries . lack of explicit attribute mentions and complexity of the query complicates ranking . |
| Approach: | They propose a four-point schema for annotating the best product candidates for superlative queries . they propose pointwise, deliberated pointwise and pairwise methods to analyze the results . |
| Outcome: | The proposed schema can be used to rank products with implicit attributes and reason over them. |