Liu, Fangyu

Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context

Gemini Team, Georgiev, P., Lei, V. I., Burnell, R., Bai, L., Gulati, A., Tanzer, G., Vincent, D., Pan, Z., Wang, S., et al. (2024) · arXiv

Multimodal Machine Learning ApplicationsTopic Modeling

Cited by 306

TweetNLP: Cutting-Edge Natural Language Processing for Social Media

Camacho-collados, J., Rezaee, K., Riahi, T., Ushio, A., Loureiro, D., Antypas, D., Boisson, J., Espinosa Anke, L., Liu, F., & Martínez Cámara, E. (2022) · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: System Demonstrations

Sentiment Analysis and Opinion MiningTopic Modeling

Cited by 142

Revisiting Parameter-Efficient Tuning: Are We Really There Yet?

Chen, G., Liu, F., Meng, Z., & Liang, S. (2022) · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing

Domain Adaptation and Few-Shot LearningTopic Modeling

Cited by 60

POSQA: Probe the World Models of LLMs with Size Comparisons

Shu, C., Han, J., Liu, F., Shareghi, E., & Collier, N. (2023) · arXiv

Topic ModelingMultimodal Machine Learning Applications

Cited by 2