3 citations · 9 across the 12 of their papers we have counts for
12 papers
DeepSeek-V4: Towards Highly Efficient Million-Token Context Intelligence
DeepSeek-AI, Anyi Xu, Bangcai Lin +315
We present a preview version of DeepSeek-V4 series, including two strong Mixture-of-Experts (MoE) language models -- DeepSeek-V4-Pro with 1.6T parameters (49B activated) and DeepSe…
Learning-based density-equalizing map
Yanwen Huang, Lok Ming Lui, Gary P. T. Choi
Density-equalizing map (DEM) serves as a powerful technique for creating shape deformations with the area changes reflecting an underlying density function. In recent decades, DEM…
Sentinel: Decoding Context Utilization via Attention Probing for Efficient LLM Context Compression
Yong Zhang, Heng Li, Yanwen Huang +6
Retrieval-augmented generation (RAG) often suffers from long and noisy retrieved contexts. Existing context compression methods typically rely on heuristic relevance estimation or…
PharmAgents: Building a Virtual Pharma with Large Language Model Agents
Bowen Gao, Yanwen Huang, Yiqiao Liu +4
The discovery of novel small molecule drugs remains a critical scientific challenge with far-reaching implications for treating diseases and advancing human health. Traditional dru…
Pushing the boundaries of Structure-Based Drug Design through Collaboration with Large Language Models
Bowen Gao, Yanwen Huang, Yiqiao Liu +4
Structure-Based Drug Design (SBDD) has revolutionized drug discovery by enabling the rational design of molecules for specific protein targets. Despite significant advancements in…
Large Language Model as Universal Retriever in Industrial-Scale Recommender System
Junguang Jiang, Yanwen Huang, Bin Liu +6
In real-world recommender systems, different retrieval objectives are typically addressed using task-specific datasets with carefully designed model architectures. We demonstrate t…
MoleculeCLA: Rethinking Molecular Benchmark via Computational Ligand-Target Binding Analysis
Shikun Feng, Jiaxin Zheng, Yinjun Jia +4
Molecular representation learning is pivotal for various molecular property prediction tasks related to drug discovery. Robust and accurate benchmarks are essential for refining an…
From Theory to Therapy: Reframing SBDD Model Evaluation via Practical Metrics
Bowen Gao, Haichuan Tan, Yanwen Huang +5
Recent advancements in structure-based drug design (SBDD) have significantly enhanced the efficiency and precision of drug discovery by generating molecules tailored to bind specif…
SIU: A Million-Scale Structural Small Molecule-Protein Interaction Dataset for Unbiased Bioactivity Prediction
Yanwen Huang, Bowen Gao, Yinjun Jia +4
Small molecules play a pivotal role in modern medicine, and scrutinizing their interactions with protein targets is essential for the discovery and development of novel, life-savin…
UniCorn: A Unified Contrastive Learning Approach for Multi-view Molecular Representation Learning
Shikun Feng, Yuyan Ni, Minghao Li +4
Recently, a noticeable trend has emerged in developing pre-trained foundation models in the domains of CV and NLP. However, for molecular pre-training, there lacks a universal mode…
Rethinking Specificity in SBDD: Leveraging Delta Score and Energy-Guided Diffusion
Bowen Gao, Minsi Ren, Yuyan Ni +5
In the field of Structure-based Drug Design (SBDD), deep learning-based generative models have achieved outstanding performance in terms of docking score. However, further study sh…
UniMAP: Universal SMILES-Graph Representation Learning
Shikun Feng, Lixin Yang, Yanwen Huang +3
Molecular representation learning is fundamental for many drug related applications. Most existing molecular pre-training models are limited in using single molecular modality, eit…