| Can llms express their uncertainty? an empirical evaluation of confidence elicitation in llms M Xiong, Z Hu, X Lu, Y Li, J Fu, J He, B Hooi arXiv preprint arXiv:2306.13063, 2023 | 285 | 2023 |
| Source Attribution for Large Language Model-Generated Data J Wang, X Lu, Z Zhao, Z Dai, CS Foo, SK Ng, BKH Low arXiv preprint arXiv:2310.00646, 2023 | 13 | 2023 |
| An exploratory study of reactions to bot comments on GitHub JC Farah, B Spaenlehauer, X Lu, S Ingram, D Gillet Proceedings of the Fourth International Workshop on Bots in Software …, 2022 | 13 | 2022 |
| Can LLMs express their uncertainty M Xiong, Z Hu, X Lu, Y Li, J Fu, J He, B Hooi An empirical evaluation of confidence elicitation in LLMs. ArXiv abs/2306.13063, 2023 | 11 | 2023 |
| On Newton's Method to Unlearn Neural Networks N Bui, X Lu, RHL Sim, SK Ng, BKH Low arXiv preprint arXiv:2406.14507, 2024 | 2 | 2024 |
| Global-to-Local Support Spectrums for Language Model Explainability L Agussurja, X Lu, BKH Low arXiv preprint arXiv:2408.05976, 2024 | | 2024 |
| TRACE: TRansformer-based Attribution using Contrastive Embeddings in LLMs C Wang, X Lu, SK Ng, BKH Low arXiv preprint arXiv:2407.04981, 2024 | | 2024 |
| Global-to-Local Support Spectrums for Model Explainability L Agussurja, X Lu, BKH Low | | |
| Source Attribution for Large Language Model-Generated Data X Lu, J Wang, Z Zhao, Z Dai, CS Foo, SK Ng, BKH Low | | |
| WASA: WAtermark-based Source Attribution for Large Language Model-Generated Data X Lu, J Wang, Z Zhao, Z Dai, CS Foo, SK Ng, BKH Low | | |
