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Found 14 papers, 12 papers with code
ChineseHarm-Bench: A Chinese Harmful Content Detection Benchmark
In addition, we propose a knowledge-augmented baseline that integrates both human-annotated knowledge rules and implicit knowledge from large language models, enabling smaller models to achieve performance comparable to state-of-the-art LLMs.
SFM-Protein: Integrative Co-evolutionary Pre-training for Advanced Protein Sequence Representation
Proteins, essential to biological systems, perform functions intricately linked to their three-dimensional structures.
To Forget or Not? Towards Practical Knowledge Unlearning for Large Language Models
Large Language Models (LLMs) trained on extensive corpora inevitably retain sensitive data, such as personal privacy information and copyrighted material.
BioT5+: Towards Generalized Biological Understanding with IUPAC Integration and Multi-task Tuning
However, previous efforts like BioT5 faced challenges in generalizing across diverse tasks and lacked a nuanced understanding of molecular structures, particularly in their textual representations (e. g., IUPAC).
Ranked #2 on
Retrosynthesis
on Mol-Instruction
InstructEdit: Instruction-based Knowledge Editing for Large Language Models
Knowledge editing for large language models can offer an efficient solution to alter a model's behavior without negatively impacting the overall performance.
Mol-Instructions: A Large-Scale Biomolecular Instruction Dataset for Large Language Models
Large Language Models (LLMs), with their remarkable task-handling capabilities and innovative outputs, have catalyzed significant advancements across a spectrum of fields.
Catalytic activity prediction
Chemical-Disease Interaction Extraction
+14
Multimodal Analogical Reasoning over Knowledge Graphs
Analogical reasoning is fundamental to human cognition and holds an important place in various fields.
Decoupling Knowledge from Memorization: Retrieval-augmented Prompt Learning
Specifically, vanilla prompt learning may struggle to utilize atypical instances by rote during fully-supervised training or overfit shallow patterns with low-shot data.
Multi-modal Protein Knowledge Graph Construction and Applications
Existing data-centric methods for protein science generally cannot sufficiently capture and leverage biology knowledge, which may be crucial for many protein tasks.
Relphormer: Relational Graph Transformer for Knowledge Graph Representations
To this end, we propose a new variant of Transformer for knowledge graph representations dubbed Relphormer.
Ranked #3 on
Link Prediction
on FB15k-237
Contrastive Demonstration Tuning for Pre-trained Language Models
Pretrained language models can be effectively stimulated by textual prompts or demonstrations, especially in low-data scenarios.
OntoProtein: Protein Pretraining With Gene Ontology Embedding
We construct a novel large-scale knowledge graph that consists of GO and its related proteins, and gene annotation texts or protein sequences describe all nodes in the graph.
DeepKE: A Deep Learning Based Knowledge Extraction Toolkit for Knowledge Base Population
We present an open-source and extensible knowledge extraction toolkit DeepKE, supporting complicated low-resource, document-level and multimodal scenarios in the knowledge base population.
CBLUE: A Chinese Biomedical Language Understanding Evaluation Benchmark
Artificial Intelligence (AI), along with the recent progress in biomedical language understanding, is gradually changing medical practice.
Ranked #1 on
Semantic Similarity
on CHIP-STS
