Large language models (LLMs) have shown impressive ability for open-doma...
Recently, instruction-following Large Language Models (LLMs) , represent...
Consistently scaling pre-trained language models (PLMs) imposes substant...
Zero-shot information extraction (IE) aims to build IE systems from the
...
Ultra-fine entity typing (UFET) predicts extremely free-formed types (e....
Metric-based meta-learning is one of the de facto standards in few-shot
...
Speech Entity Linking aims to recognize and disambiguate named entities ...
Successful Machine Learning based Named Entity Recognition models could ...
Recent works of opinion expression identification (OEI) rely heavily on ...
Named entity recognition (NER) is a fundamental task in natural language...
The MultiCoNER shared task aims at detecting semantically ambiguous and
...
We consider the trade-off problem between exploration and exploitation u...
Named Entity Recognition (NER) from speech is among Spoken Language
Unde...
Recently, considerable literature has grown up around the theme of few-s...
Fully supervised neural approaches have achieved significant progress in...
Measurement error in observational datasets can lead to systematic bias ...