Tong Che
18 papers · 2016–2026 · 9 conferences · across top CS/AI conferences
Achievements
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🐝 Cross-Pollinator (9) 🧭 Keyword Pioneer 🌍 Conference Polyglot (8) 🏃 Academic Marathon (9) 🌈 Renaissance Researcher (6)
🌍
Conference Polyglot
(8)
🏃
Academic Marathon
(9)
🌉
Interdisciplinary Bridge
👑
Triple Crown
🏆
Grand Slam
🔥
Unstoppable
(8)
📈
Trend Setter
💎
Century Club
(17)
🗃️
Keyword Collector
(55)
🚀
Conference Pioneer
Conferences
ICLR (5)
NIPS (4)
ICCV (2)
ICML (2)
AAAI (1)
ACL (1)
ECCV (1)
EMNLP (1)
NAACL (1)
Top co-authors
Research topics
Keywords
energy-based model
(3)
out-of-distribution detection
(2)
generative adversarial network
(2)
representation learning
(1)
semi-supervised learning
(1)
feature learning
(1)
adversarial learning
(1)
offline reinforcement learning
(1)
imitation learning
(1)
anomaly detection
(1)
pose estimation
(1)
uncertainty quantification
(1)
mathematical reasoning
(1)
knowledge distillation
(1)
factual knowledge
(1)
masked language model
(1)
knowledge probing
(1)
confidence calibration
(1)
image synthesis
(1)
few-shot learning
(1)
Papers
Reasoning over Precedents Alongside Statutes: Case-Augmented Deliberative Alignment for LLM Safety
ACL 2026
LLaMA-Berry: Pairwise Optimization for Olympiad-level Mathematical Reasoning via O1-like Monte Carlo Tree Search
NAACL 2025
LoR-VP: Low-Rank Visual Prompting for Efficient Vision Model Adaptation
ICLR 2025
Parallelized Spatiotemporal Slot Binding for Videos
ICML 2024
Learning from Teaching Regularization: Generalizable Correlations Should be Easy to Imitate
NIPS 2024
EmerNeRF: Emergent Spatial-Temporal Scene Decomposition via Self-Supervision
ICLR 2024
Bayesian Reparameterization of Reward-Conditioned Reinforcement Learning with Energy-based Models
ICML 2023
Robust and Controllable Object-Centric Learning through Energy-based Models
ICLR 2023
Sparse Mixture-of-Experts are Domain Generalizable Learners
ICLR 2023
SPE: Symmetrical Prompt Enhancement for Fact Probing
EMNLP 2022
Deep Verifier Networks: Verification of Deep Discriminative Models with Deep Generative Models
AAAI 2021
Energy-Based Open-World Uncertainty Modeling for Confidence Calibration
ICCV 2021
Your GAN is Secretly an Energy-based Model and You Should Use Discriminator Driven Latent Sampling
NIPS 2020
AUTO3D: Novel view synthesis through unsupervisely learned variational viewpoint and global 3D representation
ECCV 2020
Conservative Wasserstein Training for Pose Estimation
ICCV 2019
Residual Connections Encourage Iterative Inference
ICLR 2018
MetaGAN: An Adversarial Approach to Few-Shot Learning
NIPS 2018
Architectural Complexity Measures of Recurrent Neural Networks
NIPS 2016