2 citations · 2 across the 15 of their papers we have counts for
16 papers
PopPert: Population-level Joint-Distribution Modeling for Single-Cell Perturbation Prediction
Handong Wang, Jiaxin Qi, Haochen Feng +1
Predicting transcriptional responses to specific perturbations is critical for understanding cellular regulatory mechanisms and accelerating drug discovery. Single-cell RNA sequenc…
SymFold: Synergizing Evolutionary and Structural Priors for Accurate Protein Inverse Folding
Handong Wang, Jiaxin Qi, Baisheng Lai +1
Protein inverse folding aims to recover amino acid sequences for a given 3D protein structure, underpinning broad applications such as enzyme engineering and drug discovery.Current…
A Model-Internal Protocol for Assessing Multimodal Models as Integrated Systems
Hao Zhang, Jiaxin Qi, Zhijiang Tang +1
As Large Vision-Language Models increasingly aim to integrate visual generation and understanding within a single parameter space, evaluating such structural unification in a cohes…
Beyond Gene Reconstruction: Learning Cell Representations through Complementary Transcriptomic Views
Jiaqi Xiong, Yuntao hu, Yu Zheng +3
The rapid growth of single-cell transcriptomic data has enabled the development of foundation models pretrained primarily by reconstructing masked expression values. This objective…
A Reconstruction-Based Framework for Caption Evaluation Beyond Reference Captions
Zhijiang Tang, Jiaxin Qi, Kaihua Tang +2
Image captioning is a primary task in vision--language research, yet assessing how faithfully a caption preserves image semantics without relying on reference captions remains unse…
Intrinsic Gradient Suppression for Label-Noise Prompt Tuning in Vision-Language Models
Jiayu Li, Jiaxin Qi, Sheng Zhou +2
Contrastive vision-language models like CLIP exhibit remarkable zero-shot generalization. However, prompt tuning remains highly sensitive to label noise, as mislabeled samples gene…
Matching Matters: A Fair Quality-Efficiency Benchmark for Command-Line Agents
Han Chi, Jiaxin Qi, Yan Cui +2
Rapid advances in large language models have improved the task-solving capabilities of command-line-interface (CLI)-based agents, whose CLIs determine how models invoke tools, main…
Towards Universal Gene Regulatory Network Inference: Unlocking Generalizable Regulatory Knowledge in Single-cell Foundation Models
Jiaxin Qi, Hang Li, Yan Cui +2
Gene Regulatory Network (GRN) inference is essential for understanding complex cellular mechanisms, rendered tractable through single-cell transcriptomic data. With the emergence o…
Long-CODE: Isolating Pure Long-Context as an Orthogonal Dimension in Video Evaluation
Zhijiang Tang, Jiaxin Qi, Bing Zhao +1
As video generation models achieve unprecedented capabilities, the demand for robust video evaluation metrics becomes increasingly critical. Traditional metrics are intrinsically t…
In Search of Lost DNA Sequence Pretraining
Zhijiang Tang, Jiaxin Qi, Yan Cui +3
DNA sequence encoding is fundamental to gene function prediction, protein synthesis, and diverse downstream biological tasks. Despite the substantial progress achieved by large-sca…
Scaling Test-Time Robustness of Vision-Language Models via Self-Critical Inference Framework
Kaihua Tang, Jiaxin Qi, Jinli Ou +2
The emergence of Large Language Models (LLMs) has driven rapid progress in multi-modal learning, particularly in the development of Large Vision-Language Models (LVLMs). However, e…
Experience is the Best Teacher: Motivating Effective Exploration in Reinforcement Learning for LLMs
Wenjian Zhang, Kongcheng Zhang, Jiaxin Qi +2
Reinforcement Learning (RL) with rubric-based rewards has recently shown remarkable progress in enhancing general reasoning capabilities of Large Language Models (LLMs), yet still…
Spatial Transcriptomics as Images for Large-Scale Pretraining
Yishun Zhu, Jiaxin Qi, Jian Wang +2
Spatial Transcriptomics (ST) profiles thousands of gene expression values at discrete spots with precise coordinates on tissue sections, preserving spatial context essential for cl…
Gene Incremental Learning for Single-Cell Transcriptomics
Jiaxin Qi, Yan Cui, Jianqiang Huang +1
Classes, as fundamental elements of Computer Vision, have been extensively studied within incremental learning frameworks. In contrast, tokens, which play essential roles in many r…
Graph Neural Networks as a Substitute for Transformers in Single-Cell Transcriptomics
Jiaxin Qi, Yan Cui, Jinli Ou +2
Graph Neural Networks (GNNs) and Transformers share significant similarities in their encoding strategies for interacting with features from nodes of interest, where Transformers u…
A Comprehensive Benchmark for Electrocardiogram Time-Series
Zhijiang Tang, Jiaxin Qi, Yuhua Zheng +1
Electrocardiogram~(ECG), a key bioelectrical time-series signal, is crucial for assessing cardiac health and diagnosing various diseases. Given its time-series format, ECG data is…