Results 141 to 150 of about 4,141 (216)

MATO: A Model-Agnostic Training Optimization for Aspect Sentiment Triplet Extraction [PDF]

Shaopeng Tang, Lin Li, Xiaohui Tao, L. Zhong, Qing Xie   +4 more
openalex   +1 more source

Research on the Method and Dataset for Aspect Sentiment Triplet Extraction from Documents

Xiaowen Hu, Qing Zhu, Yang Xiao, Wanting Zhu   +3 more
openalex   +1 more source

LDA2Net Digging under the surface of COVID-19 scientific literature topics via a network-based approach. [PDF]

PLoS One
Minello G, Santagiustina CRMA, Warglien M.   +2 more
europepmc   +1 more source

Exploring a GPT-based large language model for variable autonomy in a VR-based human-robot teaming simulation. [PDF]

Front Robot AI
Lakhnati Y, Pascher M, Gerken J.
europepmc   +1 more source

The paradox of thermal vs. non-thermal effects in plasmonic photocatalysis. [PDF]

Nat Commun
Verma R, Sharma G, Polshettiwar V.
europepmc   +1 more source

The role of natural language processing in cancer care: a systematic scoping review with narrative synthesis

Sun M, Reiter E, Duncan L, Adam R.
europepmc   +1 more source

The Most Effective Interventions for Classification Model Development to Predict Chat Outcomes Based on the Conversation Content in Online Suicide Prevention Chats: Machine Learning Approach.

JMIR Ment Health
Salmi S, Mérelle S, Gilissen R, van der Mei R, Bhulai S.   +4 more
europepmc   +1 more source

CONTRASTE: Supervised Contrastive Pre-training With Aspect-based Prompts For Aspect Sentiment Triplet Extraction [PDF]

Conference on Empirical Methods in Natural Language Processing, 2023
Existing works on Aspect Sentiment Triplet Extraction (ASTE) explicitly focus on developing more efficient fine-tuning techniques for the task. Instead, our motivation is to come up with a generic approach that can improve the downstream performances of ...
Rajdeep Mukherjee, Nithish Kannen, Saurabh Kumar Pandey, Pawan Goyal   +3 more
semanticscholar   +6 more sources

Test-Time Code-Switching for Cross-lingual Aspect Sentiment Triplet Extraction [PDF]

North American Chapter of the Association for Computational Linguistics
Aspect Sentiment Triplet Extraction (ASTE) is a thriving research area with impressive outcomes being achieved on high-resource languages. However, the application of cross-lingual transfer to the ASTE task has been relatively unexplored, and current ...
Dongming Sheng, Kexin Han, Hao Li, Yan Zhang, Yucheng Huang, Jun Lang, Wenqiang Liu   +6 more
semanticscholar   +4 more sources