반응형 오늘의 자연어 처리572 [2023-08-11] 오늘의 자연어처리 Building Interpretable and Reliable Open Information Retriever for New Domains Overnight Information retrieval (IR) or knowledge retrieval, is a critical component for many down-stream tasks such as open-domain question answering (QA). It is also very challenging, as it requires succinctness, completeness, and correctness. In recent works, dense retrieval models have achieved state-of-the-art (S.. 2023. 8. 11. [2023-08-10] 오늘의 자연어처리 Hybrid Retrieval-Augmented Generation for Real-time Composition Assistance Retrieval augmented models show promise in enhancing traditional language models by improving their contextual understanding, integrating private data, and reducing hallucination. However, the processing time required for retrieval augmented large language models poses a challenge when applying them to tasks that require .. 2023. 8. 10. [2023-08-09] 오늘의 자연어처리 Improving Few-shot and Zero-shot Entity Linking with Coarse-to-Fine Lexicon-based Retriever Few-shot and zero-shot entity linking focus on the tail and emerging entities, which are more challenging but closer to real-world scenarios. The mainstream method is the ''retrieve and rerank'' two-stage framework. In this paper, we propose a coarse-to-fine lexicon-based retriever to retrieve entity cand.. 2023. 8. 9. [2023-08-08] 오늘의 자연어처리 Efficient Sentiment Analysis: A Resource-Aware Evaluation of Feature Extraction Techniques, Ensembling, and Deep Learning Models While reaching for NLP systems that maximize accuracy, other important metrics of system performance are often overlooked. Prior models are easily forgotten despite their possible suitability in settings where large computing resources are unavailable or relatively mor.. 2023. 8. 8. 이전 1 ··· 36 37 38 39 40 41 42 ··· 143 다음 반응형