activity
20202026
most citedInstructUIE: Multi-task Instruction Tuning for Unified Information Extraction

48 citations · 288 across the 47 of their papers we have counts for

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Showing 2024Show all

14 papers · 1 filter

cs.DB2024

From Words to Structured Visuals: A Benchmark and Framework for Text-to-Diagram Generation and Editing

Jingxuan Wei, Cheng Tan, Qi Chen +6

We introduce the task of text-to-diagram generation, which focuses on creating structured visual representations directly from textual descriptions. Existing approaches in text-to-…

cs.LG2024

MeToken: Uniform Micro-environment Token Boosts Post-Translational Modification Prediction

Cheng Tan, Zhenxiao Cao, Zhangyang Gao +6

Post-translational modifications (PTMs) profoundly expand the complexity and functionality of the proteome, regulating protein attributes and interactions that are crucial for biol…

cs.LG2024★ 6 cited

A Survey on Mixup Augmentations and Beyond

Xin Jin, Hongyu Zhu, Siyuan Li +6

As Deep Neural Networks have achieved thrilling breakthroughs in the past decade, data augmentations have garnered increasing attention as regularization techniques when massive la…

cs.LG2024

Short-Long Convolutions Help Hardware-Efficient Linear Attention to Focus on Long Sequences

Zicheng Liu, Siyuan Li, Li Wang +3

To mitigate the computational complexity in the self-attention mechanism on long sequences, linear attention utilizes computation tricks to achieve linear complexity, while state s…

cs.CL2024★ 3 cited

Peer Review as A Multi-Turn and Long-Context Dialogue with Role-Based Interactions

Cheng Tan, Dongxin Lyu, Siyuan Li +5

Large Language Models (LLMs) have demonstrated wide-ranging applications across various fields and have shown significant potential in the academic peer-review process. However, ex…

q-bio.GN2024★ 1 cited

VQDNA: Unleashing the Power of Vector Quantization for Multi-Species Genomic Sequence Modeling

Siyuan Li, Zedong Wang, Zicheng Liu +5

Similar to natural language models, pre-trained genome language models are proposed to capture the underlying intricacies within genomes with unsupervised sequence modeling. They h…

cs.LG2024★ 4 cited

CBGBench: Fill in the Blank of Protein-Molecule Complex Binding Graph

Haitao Lin, Guojiang Zhao, Odin Zhang +7

Structure-based drug design (SBDD) aims to generate potential drugs that can bind to a target protein and is greatly expedited by the aid of AI techniques in generative models. How…

cs.CV2024

Retrieval Meets Reasoning: Even High-school Textbook Knowledge Benefits Multimodal Reasoning

Cheng Tan, Jingxuan Wei, Linzhuang Sun +5

Large language models equipped with retrieval-augmented generation (RAG) represent a burgeoning field aimed at enhancing answering capabilities by leveraging external knowledge bas…

cs.AI2024★ 3 cited

UniIF: Unified Molecule Inverse Folding

Zhangyang Gao, Jue Wang, Cheng Tan +5

Molecule inverse folding has been a long-standing challenge in chemistry and biology, with the potential to revolutionize drug discovery and material science. Despite specified mod…

q-bio.QM2024★ 4 cited

Learning to Predict Mutation Effects of Protein-Protein Interactions by Microenvironment-aware Hierarchical Prompt Learning

Lirong Wu, Yijun Tian, Haitao Lin +4

Protein-protein bindings play a key role in a variety of fundamental biological processes, and thus predicting the effects of amino acid mutations on protein-protein binding is cru…

cs.LG2024★ 10 cited

MAPE-PPI: Towards Effective and Efficient Protein-Protein Interaction Prediction via Microenvironment-Aware Protein Embedding

Lirong Wu, Yijun Tian, Yufei Huang +4

Protein-Protein Interactions (PPIs) are fundamental in various biological processes and play a key role in life activities. The growing demand and cost of experimental PPI assays r…

q-bio.BM2024★ 6 cited

Re-Dock: Towards Flexible and Realistic Molecular Docking with Diffusion Bridge

Yufei Huang, Odin Zhang, Lirong Wu +5

Accurate prediction of protein-ligand binding structures, a task known as molecular docking is crucial for drug design but remains challenging. While deep learning has shown promis…

cs.LG2024★ 3 cited

Switch EMA: A Free Lunch for Better Flatness and Sharpness

Siyuan Li, Zicheng Liu, Juanxi Tian +9

Exponential Moving Average (EMA) is a widely used weight averaging (WA) regularization to learn flat optima for better generalizations without extra cost in deep neural network (DN…

cs.CV2024★ 7 cited

Masked Modeling for Self-supervised Representation Learning on Vision and Beyond

Siyuan Li, Luyuan Zhang, Zedong Wang +8

As the deep learning revolution marches on, self-supervised learning has garnered increasing attention in recent years thanks to its remarkable representation learning ability and…