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Found 8 papers, 6 papers with code
Exploiting Image–Text Synergy for Contextual Image Captioning
Modern web content - news articles, blog posts, educational resources, marketing brochures - is predominantly multimodal.
Leveraging Contextual Information for Effective Entity Salience Detection
In text documents such as news articles, the content and key events usually revolve around a subset of all the entities mentioned in a document.
Unsupervised Contrast-Consistent Ranking with Language Models
We compare pairwise, pointwise and listwise prompting techniques to elicit a language model's ranking knowledge.
Learning Rich Representation of Keyphrases from Text
In the discriminative setting, we introduce a new pre-training objective - Keyphrase Boundary Infilling with Replacement (KBIR), showing large gains in performance (upto 8. 16 points in F1) over SOTA, when the LM pre-trained using KBIR is fine-tuned for the task of keyphrase extraction.
Fast and Effective Biomedical Entity Linking Using a Dual Encoder
Additionally, we modify our dual encoder model for end-to-end biomedical entity linking that performs both mention span detection and entity disambiguation and out-performs two recently proposed models.
Explainable Link Prediction for Emerging Entities in Knowledge Graphs
Despite their large-scale coverage, cross-domain knowledge graphs invariably suffer from inherent incompleteness and sparsity.
Be Concise and Precise: Synthesizing Open-Domain Entity Descriptions from Facts
Despite being vast repositories of factual information, cross-domain knowledge graphs, such as Wikidata and the Google Knowledge Graph, only sparsely provide short synoptic descriptions for entities.
Generating Fine-Grained Open Vocabulary Entity Type Descriptions
While large-scale knowledge graphs provide vast amounts of structured facts about entities, a short textual description can often be useful to succinctly characterize an entity and its type.
