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Found 11 papers, 9 papers with code
Characteristic AI Agents via Large Language Models
In response to this research gap, we create a benchmark for the characteristic AI agents task, including dataset, techniques, and evaluation metrics.
An Empirical Investigation of Domain Adaptation Ability for Chinese Spelling Check Models
Chinese Spelling Check (CSC) is a meaningful task in the area of Natural Language Processing (NLP) which aims at detecting spelling errors in Chinese texts and then correcting these errors.
Medical Report Generation based on Segment-Enhanced Contrastive Representation Learning
Automated radiology report generation has the potential to improve radiology reporting and alleviate the workload of radiologists.
ConsistentEE: A Consistent and Hardness-Guided Early Exiting Method for Accelerating Language Models Inference
We propose ConsistentEE, an early exiting method that is consistent in training and inference.
From Ultra-Fine to Fine: Fine-tuning Ultra-Fine Entity Typing Models to Fine-grained
We can simply fine-tune the previously trained model with a small number of examples annotated under this schema.
Ultra-Fine Entity Typing with Weak Supervision from a Masked Language Model
Recently, there is an effort to extend fine-grained entity typing by using a richer and ultra-fine set of types, and labeling noun phrases including pronouns and nominal nouns instead of just named entity mentions.
Ranked #1 on
Entity Typing
on Ontonotes v5 (English)
(using extra training data)
A Chinese Corpus for Fine-grained Entity Typing
In this paper, we introduce a corpus for Chinese fine-grained entity typing that contains 4, 800 mentions manually labeled through crowdsourcing.
Exploiting Semantic Relations for Fine-grained Entity Typing
We find that, in some cases, existing neural fine-grained entity typing models may ignore the semantic information in the context that is important for typing.
Improving Fine-grained Entity Typing with Entity Linking
Fine-grained entity typing is a challenging problem since it usually involves a relatively large tag set and may require to understand the context of the entity mention.
Neural Aspect and Opinion Term Extraction with Mined Rules as Weak Supervision
Lack of labeled training data is a major bottleneck for neural network based aspect and opinion term extraction on product reviews.
Entity Linking within a Social Media Platform: A Case Study on Yelp
In this paper, we study a new entity linking problem where both the entity mentions and the target entities are within a same social media platform.
