collaborators

13 papers

q-bio.GN2026

Harmonised benchmarking of foundation models for single-cell and spatial transcriptomics reveals context-dependent generalisation

Sally Chen, Roxana Zahedi, Lucy Chhuo +11

Single-cell and spatial foundation models promise transferable biological representations, yet their generality remains largely untested across modalities, biological domains and a…

q-bio.GN2026

Transcriptomic Models for Immunotherapy Response Prediction Show Limited Cross-cohort Generalisability

Yuheng Liang, Lucy Chhuo, Ahmadreza Argha +8

Immune checkpoint inhibitors (ICIs) have transformed cancer therapy; yet substantial proportion of patients exhibit intrinsic or acquired resistance, making accurate pre-treatment…

cs.AI2026

Beyond Quantity: Trajectory Diversity Scaling for Code Agents

Guhong Chen, Chenghao Sun, Cheng Fu +16

As code large language models (LLMs) evolve into tool-interactive agents via the Model Context Protocol (MCP), their generalization is increasingly limited by low-quality synthetic…

q-bio.GN2026

Revolutionizing Genomics with Reinforcement Learning Techniques

Mohsen Karami, Khadijeh, Jahanian +9

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…

cs.AI2026

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…

cs.CL2026

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…