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Found 10 papers, 8 papers with code
AI Hospital: Interactive Evaluation and Collaboration of LLMs as Intern Doctors for Clinical Diagnosis
To simulate the procedure, we collect high-quality medical records to create patient, examiner, and medical director agents.
Harvesting Event Schemas from Large Language Models
Event schema provides a conceptual, structural and formal language to represent events and model the world event knowledge.
Procedural Text Understanding via Scene-Wise Evolution
In this paper, we propose a new \textbf{scene-wise} paradigm for procedural text understanding, which jointly tracks states of all entities in a scene-by-scene manner.
Text2Event: Controllable Sequence-to-Structure Generation for End-to-end Event Extraction
Event extraction is challenging due to the complex structure of event records and the semantic gap between text and event.
Ranked #3 on
Event Extraction
on ACE2005
From Discourse to Narrative: Knowledge Projection for Event Relation Extraction
Current event-centric knowledge graphs highly rely on explicit connectives to mine relations between events.
Syntactic and Semantic-driven Learning for Open Information Extraction
One of the biggest bottlenecks in building accurate, high coverage neural open IE systems is the need for large labelled corpora.
Enhanced Aspect-Based Sentiment Analysis Models with Progressive Self-supervised Attention Learning
In aspect-based sentiment analysis (ABSA), many neural models are equipped with an attention mechanism to quantify the contribution of each context word to sentiment prediction.
Aspect-Based Sentiment Analysis
Aspect-Based Sentiment Analysis (ABSA)
End-to-End Neural Event Coreference Resolution
Traditional event coreference systems usually rely on pipeline framework and hand-crafted features, which often face error propagation problem and have poor generalization ability.
A Rigorous Study on Named Entity Recognition: Can Fine-tuning Pretrained Model Lead to the Promised Land?
Specifically, we erase name regularity, mention coverage and context diversity respectively from the benchmarks, in order to explore their impact on the generalization ability of models.
Progressive Self-Supervised Attention Learning for Aspect-Level Sentiment Analysis
In aspect-level sentiment classification (ASC), it is prevalent to equip dominant neural models with attention mechanisms, for the sake of acquiring the importance of each context word on the given aspect.
Aspect-Based Sentiment Analysis (ABSA)
Sentiment Classification
