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Found 7 papers, 3 papers with code
HELLaMA: LLaMA-based Table to Text Generation by Highlighting the Important Evidence
To facilitate this, we propose a search strategy to construct reasoning labels for training the table reasoner.
Inspire the Large Language Model by External Knowledge on BioMedical Named Entity Recognition
In this paper, inspired by Chain-of-thought, we leverage the LLM to solve the Biomedical NER step-by-step: break down the NER task into entity span extraction and entity type determination.
DMNER: Biomedical Entity Recognition by Detection and Matching
Biomedical named entity recognition (BNER) serves as the foundation for numerous biomedical text mining tasks.
GoSum: Extractive Summarization of Long Documents by Reinforcement Learning and Graph Organized discourse state
In this paper, we propose GoSum, a novel graph and reinforcement learning based extractive model for long-paper summarization.
Ranked #4 on
Text Summarization
on Pubmed
Controllable Length Control Neural Encoder-Decoder via Reinforcement Learning
Here, we denote a concept of Controllable Length Control (CLC) for the trade-off between length control capacity and semantic accuracy of the language generation model.
Hybrid Function Sparse Representation towards Image Super Resolution
Based on the idea of making the magnification of function curve without losing its fidelity, we proposed a function based dictionary on sparse representation for super resolution, called hybrid function sparse representation (HFSR).
