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Ziqian Lin

8 accepted papers

2026

DS-ProGen: A Dual-Structure Deep Language Model for Functional Protein Design

AAAI 2026technical

Inverse Protein Folding (IPF) is a critical subtask in the field of protein design, aiming to engineer amino acid sequences capable of folding correctly into a specified three-dimensional (3D) conformation. Although substantial progress has been achieved in recent years, existing methods generally r

Cited by 0SourcePDFScholar
2026

RMSAGen: Integrating Multiple Sequence Alignment for Function RNA Design

AAAI 2026technical

Biological sequences, including RNAs and proteins, share similarities with natural languages, enabling the application of advanced language models to various biological tasks. However, due to its flexibility and lack of experimental data, RNA is a particularly challenging biological ``language

Cited by 0SourcePDFScholar
2026

WBMCF: Robust Spatiotemporal Forecasting of Terrorism Fatalities with Multi-Scale Time–Frequency Fusion

IJCAI 2026

Reliable forecasting of cross-regional terrorism fatalities is essential for early warning and security planning. However, real-world terrorism data are characterized by extreme sparsity, abrupt volatility, and weak, rapidly shifting non-Euclidean spatial relationships, posing substantial challenges

Cited by 0Scholar
2025

Everything Everywhere All at Once: LLMs can In-Context Learn Multiple Tasks in Superposition

ICML 2025spotlight

Large Language Models (LLMs) have demonstrated remarkable in-context learning (ICL) capabilities. In this study, we explore a surprising phenomenon related to ICL: LLMs can perform multiple, computationally distinct ICL tasks simultaneously, during a single inference call, a capability we term task…

Cited by 3SourcePDFScholar
2022

LIFT: Language-Interfaced Fine-Tuning for Non-language Machine Learning Tasks

NeurIPS 2022accept

Fine-tuning pretrained language models (LMs) without making any architectural changes has become a norm for learning various language downstream tasks. However, for non-language downstream tasks, a common practice is to employ task-specific designs for input, output layers, and loss functions. For i…

2020

A Sequential Convolution Network for Population Flow Prediction with Explicitly Correlation Modelling

IJCAI 2020poster

Population flow prediction is one of the most fundamental components in many applications from urban management to transportation schedule. It is challenging due to the complicated spatial-temporal correlation.While many studies have been done in recent years, they fail to simultaneously and effecti…

Cited by 0SourcePDFScholar