Papers with weather forecasting
An Integrated Search System for Korea Weather Data (2023.emnlp-industry)
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| Challenge: | a weather search system is used to retrieve weather data from a massive weather database . a lack of navigation and time-consuming navigation hinders accurate weather forecasting . |
| Approach: | They propose a weather search system that allows users to retrieve weather data from a massive weather database with simple queries. |
| Outcome: | The proposed system achieves an average MRR and Recall of 0.82 on 4 million data points . it is based on a weather database at the Korea Meteorological Administration . |
Evaluating Automatic Speech Recognition Systems for Korean Meteorological Experts (2025.findings-emnlp)
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| Challenge: | Using a dataset of Korean weather queries, we find that automatic speech recognition systems fail on specialized vocabulary. |
| Approach: | They propose an evaluation dataset of Korean weather queries . the dataset was recorded by diverse native speakers following pronunciation guidelines . |
| Outcome: | The proposed model reduces error rates on meteorological terms and improves overall recognition accuracy. |
Re3: Relevance & Recency Retrieval for Mitigating Temporal Hallucination (2026.acl-long)
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| Challenge: | Existing retrievers suffer from temporal-semantic misalignment and outdated-document interference . Existing frameworks suffer from both temporal validity and outdated factual versions . |
| Approach: | They propose a framework that mitigates temporal hallucinations by embedding heterogeneous temporal signals into the semantic space to ensure retrieval fidelity. |
| Outcome: | Experiments show that Re3 outperforms baselines by 9.7% in generation accuracy . the framework outperformed strongest baselines on challenging dynamic tasks . |
Retrieval-Augmented Modular Prompt Tuning for Low-Resource Data-to-Text Generation (2024.lrec-main)
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| Challenge: | Data-to-text generation methods are often limited by data sparsity and lack of training data. |
| Approach: | They propose a retrieval-augmented modular prompt tuning method that generates texts with few hallucinations from structured data inputs. |
| Outcome: | The proposed method generates texts with few hallucinations and achieves state-of-the-art performance on a dataset for drone handover message generation. |