Papers with text embedding model
Leveraging Large Language Models for Conversational Multi-Doc Question Answering: The First Place of WSDM Cup 2024 (2025.findings-acl)
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| Challenge: | WSDM Cup 2024 presents a challenge for conversational multi-doc question answering using large language models . a hybrid training strategy is developed to make the most of in-domain unlabeled data . |
| Approach: | They propose a conversational multi-doc question answering challenge in WSDM Cup 2024 . they adapt LLMs to the task, then devise a hybrid training strategy to make the most of unlabeled data. |
| Outcome: | The proposed approach ranked 1st in the WSDM Cup 2024 challenge . it exploits the superior natural language understanding and generation capability of Large Language Models . |
ReasonEmbed: Enhanced Text Embeddings for Reasoning-Intensive Document Retrieval (2026.acl-long)
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| Challenge: | Recent studies suggest that traditional retrievers struggle with reasoningintensive tasks such as personal assistants and scientific research. |
| Approach: | They propose a new data synthesis method that overcomes the triviality problem prevalent in previous synthetic datasets and propose 'ReMixer', a data fusion method that generates 82K high-quality training samples. |
| Outcome: | The proposed model outperforms existing models on reasoning-intensive retrieval tasks. |
LETS-C: Leveraging Text Embedding for Time Series Classification (2025.acl-long)
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| Challenge: | Recent advances in language modeling have shown promising results when applied to time series data. |
| Approach: | They propose a method to fine-tune large language models for time series classification tasks using text embedding models and a simple classification head. |
| Outcome: | The proposed model outperforms the current SOTA model on a time series classification benchmark and uses only 14.5% of the trainable parameters. |