Chinese Sentiment Analysis

Benchmarks archive 2025-07-28

No benchmark for this task in the archive.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

3 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

No subtask under this task in the archive's task tree.

Most implemented papers archive 2025-07-28

4 shown of 4 papers with code (11 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• ERNIE: Enhanced Representation through Knowledge Integration
  19 Apr 2019 19 repositories listed Syntology ran 0 of 7 samples · 7 unverified
  We present a novel language representation model enhanced by knowledge called ERNIE (Enhanced Representation through kNowledge IntEgration).
• ERNIE 2.0: A Continual Pre-training Framework for Language Understanding
  29 Jul 2019 3 repositories listed Syntology ran 0 of 1 samples · 1 unverified · 1 pointer-only (licence)
  Recently, pre-trained models have achieved state-of-the-art results in various language understanding tasks, which indicates that pre-training on large-scale corpora may play a crucial role in natural language…
• CPED: A Large-Scale Chinese Personalized and Emotional Dialogue Dataset for Conversational AI
  29 May 2022 1 repository listed
  Finally, we provide baseline systems for these tasks and consider the function of speakers' personalities and emotions on conversation.
• Fine-grained Sentiment Classification using BERT
  4 Oct 2019 1 repository listed Syntology ran 0 of 2 samples · 2 unverified
  In this paper, we use a promising deep learning model called BERT to solve the fine-grained sentiment classification task.

Syntology lines on 3 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.