422 citations · 492 across the 12 of their papers we have counts for
13 papers
Unlocking Multimodal Protein Language Models at Inference Time
Yi Zhou, Qipeng Wang, Yunqing Liu +3
Multimodal protein language models (pLMs) learn joint protein sequence-structure distributions, and their generation performance should also depend critically on inference-time sam…
Geometric Flow Matching for Molecular Conformation Generation via Manifold Decomposition
Yunqing Liu, Yi Zhou, Wenqi Fan
The generation of accurate 3D molecular conformations is a pivotal challenge in computational chemistry and drug discovery. Recently, diffusion and flow matching models have achiev…
HD-Prot: A Protein Language Model for Joint Sequence-Structure Modeling with Continuous Structure Tokens
Yi Zhou, Haohao Qu, Yunqing Liu +3
Proteins inherently possess a consistent sequence-structure duality. The abundance of protein sequence data, which can be readily represented as discrete tokens, has driven fruitfu…
The Impact of AI Adoption on Retail Across Countries and Industries
Yunqi Liu
This study investigates the impact of artificial intelligence (AI) adoption on job loss rates using the Global AI Content Impact Dataset (2020--2025). The panel comprises 200 indus…
Error Notebook-Guided, Training-Free Part Retrieval in 3D CAD Assemblies via Vision-Language Models
Yunqing Liu, Nan Zhang, Zhiming Tan
Effective specification-aware part retrieval within complex CAD assemblies is essential for automated engineering tasks. However, using LLMs/VLMs for this task is challenging: the…
Respond Beyond Language: A Benchmark for Video Generation in Response to Realistic User Intents
Shuting Wang, Yunqi Liu, Zixin Yang +3
Querying generative AI models, e.g., large language models (LLMs), has become a prevalent method for information acquisition. However, existing query-answer datasets primarily focu…
GLProtein: Global-and-Local Structure Aware Protein Representation Learning
Yunqing Liu, Wenqi Fan, Xiaoyong Wei +1
Proteins are central to biological systems, participating as building blocks across all forms of life. Despite advancements in understanding protein functions through protein seque…
ATLAS: Autoformalizing Theorems through Lifting, Augmentation, and Synthesis of Data
Xiaoyang Liu, Kangjie Bao, Jiashuo Zhang +5
Autoformalization, the automatic translation of mathematical content from natural language into machine-verifiable formal languages, has seen significant progress driven by advance…
Speak-to-Structure: Evaluating LLMs in Open-domain Natural Language-Driven Molecule Generation
Jiatong Li, Junxian Li, Weida Wang +6
Recently, Large Language Models (LLMs) have demonstrated great potential in natural language-driven molecule discovery. However, existing datasets and benchmarks for molecule-text…
MolReFlect: Towards In-Context Fine-grained Alignments between Molecules and Texts
Jiatong Li, Yunqing Liu, Wei Liu +6
Molecule discovery is a pivotal research field, impacting everything from medicine to materials. Recently, Large Language Models (LLMs) have been widely adopted in molecular unders…
Recommender Systems in the Era of Large Language Models (LLMs)
Zihuai Zhao, Wenqi Fan, Jiatong Li +8
With the prosperity of e-commerce and web applications, Recommender Systems (RecSys) have become an important component of our daily life, providing personalized suggestions that c…
Empowering Molecule Discovery for Molecule-Caption Translation with Large Language Models: A ChatGPT Perspective
Jiatong Li, Yunqing Liu, Wenqi Fan +4
Molecule discovery plays a crucial role in various scientific fields, advancing the design of tailored materials and drugs. However, most of the existing methods heavily rely on do…
Improving User Controlled Table-To-Text Generation Robustness
Hanxu Hu, Yunqing Liu, Zhongyi Yu +1
In this work we study user controlled table-to-text generation where users explore the content in a table by selecting cells and reading a natural language description thereof auto…