Papers by Hoang Ngo
RecGPT: Generative Pre-training for Text-based Recommendation (2024.acl-short)
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| Challenge: | Existing models for text-based recommendation lack data sparsity and flexibility to capture fluctuations in user preferences over time. |
| Approach: | They present the first domain-adapted and fully-trained large language model for text-based recommendation. |
| Outcome: | The proposed model outperforms baseline models on rating prediction and sequential recommendation tasks. |
Who’s Who: Large Language Models Meet Knowledge Conflicts in Practice (2024.findings-emnlp)
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| Challenge: | Recent large-scale pretrained language models excel in tasks requiring natural language understanding, but they often "hallucinate" plausible but incorrect content due to outdated or incorrect pretraining information. |
| Approach: | They propose a public benchmark dataset to examine model’s behavior in knowledge conflict situations. |
| Outcome: | The proposed model induces conflicts by asking about a common property among entities having the same name, resulting in questions with up to 8 distinctive answers. |
A Self-enhancement Multitask Framework for Unsupervised Aspect Category Detection (2023.emnlp-main)
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| Challenge: | Recent work has focused on learning embedding spaces for seed words and sentences to establish similarities between sentences and aspects. |
| Approach: | They propose a framework that enhances the quality of initial seed words and selects high-quality sentences instead of using the entire dataset. |
| Outcome: | The proposed framework surpasses strong baselines on standard datasets and improves on the noise resolution task. |