4 citations · 4 across the 7 of their papers we have counts for
9 papers
Large Language Model Agents for Evidence Based Genetic Disease Severity Classification
Tohid Ghasemnejad, Ahmadreza Argha, Mark Grosser +7
Disease severity classification for genetic conditions is subjective and labor-intensive, creating bottlenecks in genomic screening, where commercial panels vary widely in size and…
Harmonised benchmarking of foundation models for single-cell and spatial transcriptomics reveals context-dependent generalisation
Sally Chen, Roxana Zahedi, Lucy Chhuo +12
Single-cell and spatial foundation models promise transferable biological representations, yet their generality remains largely untested across modalities, biological domains and a…
RxSafeBench: Identifying Medication Safety Issues of Large Language Models in Simulated Consultation
Jiahao Zhao, Luxin Xu, Minghuan Tan +4
Numerous medical systems powered by Large Language Models (LLMs) have achieved remarkable progress in diverse healthcare tasks. However, research on their medication safety remains…
Structuring Reasoning for Complex Rules Beyond Flat Representations
Zhihao Yang, Ancheng Xu, Jingpeng Li +11
Large language models (LLMs) face significant challenges when processing complex rule systems, as they typically treat interdependent rules as unstructured textual data rather than…
STORYTELLER: An Enhanced Plot-Planning Framework for Coherent and Cohesive Story Generation
Jiaming Li, Yukun Chen, Ziqiang Liu +10
Stories are central to human culture, serving to share ideas, preserve traditions, and foster connections. Automatic story generation, a key advancement in artificial intelligence…
Breaking the Block: Preserving Data Continuity to Train Superior SAEs for Instruct Models
Jiaming Li, Haoran Ye, Yukun Chen +5
Sparse Autoencoders (SAEs) are a cornerstone of mechanistic interpretability. Existing training methods inherit the Block Training paradigm from LLM pre-training, which introduces…
Expanding before Inferring: Enhancing Factuality in Large Language Models through Premature Layers Interpolation
Dingwei Chen, Ziqiang Liu, Feiteng Fang +6
Large Language Models (LLMs) demonstrate remarkable capabilities in text understanding and generation. However, their tendency to produce factually inconsistent outputs, commonly r…
Interpretable graph-based models on multimodal biomedical data integration: A technical review and benchmarking
Alireza Sadeghi, Farshid Hajati, Ahmadreza Argha +3
Integrating heterogeneous biomedical data including imaging, omics, and clinical records supports accurate diagnosis and personalised care. Graph-based models fuse such non-Euclide…
Revolutionizing Genomics with Reinforcement Learning Techniques
Mohsen Karami, Khadijeh Jahanian, Khadijeh +10
In recent years, Reinforcement Learning (RL) has emerged as a powerful tool for solving a wide range of problems, including decision-making and genomics. The exponential growth of…