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Found 8 papers, 5 papers with code
InternLM2 Technical Report
The evolution of Large Language Models (LLMs) like ChatGPT and GPT-4 has sparked discussions on the advent of Artificial General Intelligence (AGI).
Ranked #5 on
Long-Context Understanding
on Ada-LEval (BestAnswer)
InternLM-Math: Open Math Large Language Models Toward Verifiable Reasoning
We further explore how to use LEAN to solve math problems and study its performance under the setting of multi-task learning which shows the possibility of using LEAN as a unified platform for solving and proving in math.
Label Refinement via Contrastive Learning for Distantly-Supervised Named Entity Recognition
Distantly-supervised named entity recognition (NER) locates and classifies entities using only knowledge bases and unlabeled corpus to mitigate the reliance on human-annotated labels.
CoRTEx: Contrastive Learning for Representing Terms via Explanations with Applications on Constructing Biomedical Knowledge Graphs
Due to a lack of knowledge, previous contrastive learning models trained with Unified Medical Language System (UMLS) synonyms struggle at clustering difficult terms and do not generalize well beyond UMLS terms.
Sentence Alignment with Parallel Documents Facilitates Biomedical Machine Translation
Materials and Methods: Document-level translations are mixed to train bilingual word embeddings (BWEs) for the evaluation of cross-lingual word similarity, and sentence distance is defined by combining semantic and positional similarities of the sentences.
Biomedical Question Answering: A Survey of Approaches and Challenges
Automatic Question Answering (QA) has been successfully applied in various domains such as search engines and chatbots.
BIOS: An Algorithmically Generated Biomedical Knowledge Graph
For decades, these knowledge graphs have been developed via expert curation; however, this method can no longer keep up with today's AI development, and a transition to algorithmically generated BioMedKGs is necessary.
A Question Answering Based Pipeline for Comprehensive Chinese EHR Information Extraction
Electronic health records (EHRs) hold significant value for research and applications.
