One embedder, any task: Instruction-finetuned text embeddings H Su, W Shi, J Kasai, Y Wang, Y Hu, M Ostendorf, W Yih, NA Smith, ... arXiv preprint arXiv:2212.09741, 2022 | 165 | 2022 |
Selective annotation makes language models better few-shot learners H Su, J Kasai, CH Wu, W Shi, T Wang, J Xin, R Zhang, M Ostendorf, ... arXiv preprint arXiv 220901975, 2022 | 152* | 2022 |
Taming pre-trained language models with n-gram representations for low-resource domain adaptation S Diao, R Xu, H Su, Y Jiang, Y Song, T Zhang Proceedings of the 59th Annual Meeting of the Association for Computational …, 2021 | 49 | 2021 |
Openagents: An open platform for language agents in the wild T Xie, F Zhou, Z Cheng, P Shi, L Weng, Y Liu, TJ Hua, J Zhao, Q Liu, C Liu, ... arXiv preprint arXiv:2310.10634, 2023 | 36 | 2023 |
Lemur: Harmonizing natural language and code for language agents Y Xu, H Su, C Xing, B Mi, Q Liu, W Shi, B Hui, F Zhou, Y Liu, T Xie, ... arXiv preprint arXiv:2310.06830, 2023 | 34 | 2023 |
Generative representational instruction tuning N Muennighoff, H Su, L Wang, N Yang, F Wei, T Yu, A Singh, D Kiela arXiv preprint arXiv:2402.09906, 2024 | 33 | 2024 |
ARKS: Active Retrieval in Knowledge Soup for Code Generation H Su, S Jiang, Y Lai, H Wu, B Shi, C Liu, Q Liu, T Yu arXiv preprint arXiv:2402.12317, 2024 | 4 | 2024 |
BRIGHT: A Realistic and Challenging Benchmark for Reasoning-Intensive Retrieval H Su, H Yen, M Xia, W Shi, N Muennighoff, H Wang, H Liu, Q Shi, ... arXiv preprint arXiv:2407.12883, 2024 | 1 | 2024 |