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Found 8 papers, 8 papers with code
Generating Diverse Criteria On-the-Fly to Improve Point-wise LLM Rankers
The most recent pointwise Large Language Model (LLM) rankers have achieved remarkable ranking results.
XAL: EXplainable Active Learning Makes Classifiers Better Low-resource Learners
Active learning (AL), which aims to construct an effective training set by iteratively curating the most formative unlabeled data for annotation, has been widely used in low-resource tasks.
Mere Contrastive Learning for Cross-Domain Sentiment Analysis
Cross-domain sentiment analysis aims to predict the sentiment of texts in the target domain using the model trained on the source domain to cope with the scarcity of labeled data.
Unsupervised Key Event Detection from Massive Text Corpora
Automated event detection from news corpora is a crucial task towards mining fast-evolving structured knowledge.
Weakly-Supervised Aspect-Based Sentiment Analysis via Joint Aspect-Sentiment Topic Embedding
Aspect-based sentiment analysis of review texts is of great value for understanding user feedback in a fine-grained manner.
Aspect-Based Sentiment Analysis
Aspect-Based Sentiment Analysis (ABSA)
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User-Guided Aspect Classification for Domain-Specific Texts
Aspect classification, identifying aspects of text segments, facilitates numerous applications, such as sentiment analysis and review summarization.
Easing Embedding Learning by Comprehensive Transcription of Heterogeneous Information Networks
To cope with the challenges in the comprehensive transcription of HINs, we propose the HEER algorithm, which embeds HINs via edge representations that are further coupled with properly-learned heterogeneous metrics.
Revisiting Video Saliency: A Large-scale Benchmark and a New Model
Existing video saliency datasets lack variety and generality of common dynamic scenes and fall short in covering challenging situations in unconstrained environments.
