Title |
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 The Power of Noise: Redefining Retrieval for RAG SystemsAnnual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2024 |
 Chain-of-Note: Enhancing Robustness in Retrieval-Augmented Language
ModelsConference on Empirical Methods in Natural Language Processing (EMNLP), 2023 |
 Self-RAG: Learning to Retrieve, Generate, and Critique through
Self-ReflectionInternational Conference on Learning Representations (ICLR), 2023 |
 Enhancing Retrieval-Augmented Large Language Models with Iterative
Retrieval-Generation SynergyConference on Empirical Methods in Natural Language Processing (EMNLP), 2023 |
![Pre-trained Embeddings for Entity Resolution: An Experimental Analysis
[Experiment, Analysis & Benchmark]](/_next/image?url=https%3A%2F%2Fcdn.parameterlab.de%2Fpapers%2F2304.12329%2Fpages%2Fpage-1-q80d300.jpg&w=256&q=75) Pre-trained Embeddings for Entity Resolution: An Experimental Analysis
[Experiment, Analysis & Benchmark]Proceedings of the VLDB Endowment (PVLDB), 2023 |
 REPLUG: Retrieval-Augmented Black-Box Language ModelsNorth American Chapter of the Association for Computational Linguistics (NAACL), 2023 |
 Can Foundation Models Wrangle Your Data?Proceedings of the VLDB Endowment (PVLDB), 2022 |
 Self-Consistency Improves Chain of Thought Reasoning in Language ModelsInternational Conference on Learning Representations (ICLR), 2022 |
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 Deep Entity Matching with Pre-Trained Language ModelsProceedings of the VLDB Endowment (PVLDB), 2020 |
 Low-resource Deep Entity Resolution with Transfer and Active LearningAnnual Meeting of the Association for Computational Linguistics (ACL), 2019 |
