Zhifeng Gao
12 papers · 2017–2026 · 6 conferences · across top CS/AI conferences
Achievements
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🌈 Renaissance Researcher (7) 🌍 Conference Polyglot (5) 🏃 Academic Marathon (8) 🐝 Cross-Pollinator (13) 🌉 Interdisciplinary Bridge
🏃
Academic Marathon
(8)
🐝
Cross-Pollinator
(13)
🌈
Renaissance Researcher
(7)
👥
Mega-Team
(23)
💎
Century Club
(11)
⚡
Prolific Year
(6)
Conferences
ICLR (3)
ICML (3)
NIPS (3)
ACL (1)
EMNLP (1)
NAACL (1)
Top co-authors
Keywords
contrastive learning
(2)
video prediction
(2)
representation learning
(2)
recurrent neural network
(2)
vision language model
(1)
multimodal learning
(1)
self-supervised learning
(1)
inverse optimal transport
(1)
long short-term memory
(1)
geometric structure
(1)
molecular representation
(1)
scaling law
(1)
zero-shot generalization
(1)
supervised fine-tuning
(1)
drug discovery
(1)
multi-modal learning
(1)
virtual screening
(1)
unmanned aerial vehicle
(1)
semi-supervised learning
(1)
benchmark evaluation
(1)
Papers
NOSE: Neural Olfactory-Semantic Embedding with Tri-Modal Orthogonal Contrastive Learning
ACL 2026
CBGBench: Fill in the Blank of Protein-Molecule Complex Binding Graph
ICLR 2025
FlightGPT: Towards Generalizable and Interpretable UAV Vision-and-Language Navigation with Vision-Language Models
EMNLP 2025
A Simple yet Effective $\Delta\Delta G$ Predictor is An Unsupervised Antibody Optimizer and Explainer
ICLR 2025
Beyond Atoms: Enhancing Molecular Pretrained Representations with 3D Space Modeling
ICML 2025
PolyConf: Unlocking Polymer Conformation Generation through Hierarchical Generative Models
ICML 2025
SciAssess: Benchmarking LLM Proficiency in Scientific Literature Analysis
NAACL 2025
S-MolSearch: 3D Semi-supervised Contrastive Learning for Bioactive Molecule Search
NIPS 2024
Exploring Molecular Pretraining Model at Scale
NIPS 2024
Uni-Mol: A Universal 3D Molecular Representation Learning Framework
ICLR 2023
PredRNN++: Towards A Resolution of the Deep-in-Time Dilemma in Spatiotemporal Predictive Learning
ICML 2018
PredRNN: Recurrent Neural Networks for Predictive Learning using Spatiotemporal LSTMs
NIPS 2017