← Authors

Ce Zhang

90 papers · 2012–2026 · 16 conferences · across top CS/AI conferences

Achievements

🌍 Conference Polyglot (16) 🐣 Hot Topic Early Bird 🐝 Cross-Pollinator (8) πŸƒ Academic Marathon (14) 🌈 Renaissance Researcher (5) πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (18) 🧭 Keyword Pioneer 🏠 Conference Loyalist (25) 🀝 Dynamic Duo (16) πŸ‘‘ Triple Crown πŸ† Grand Slam πŸ‘₯ Mega-Team (47) πŸ”¬ Deep Specialist (17) πŸ† Keyword Champion πŸ”₯ Unstoppable (15) πŸ“ˆ Trend Setter πŸ’Ž Century Club (90) ❓ The Questioner (6) πŸ—ƒοΈ Keyword Collector (51) ⚑ Prolific Year (15)

Conferences

NIPS (25) ICML (18) ICLR (9) AAAI (7) CVPR (6) EMNLP (5) AISTATS (4) WACV (4) ACL (3) NAACL (3) COLING (1) CONLL (1) ICCV (1) JMLR (1) NSDI (1) SEMEVAL (1)

Top co-authors

Christopher Re (16) Bo Li (11) Ji Liu (10) Beidi Chen (7) Jue Wang (7) Nora Hollenstein (7) Simon Stepputtis (6) Bojan KarlaΕ‘ (6) Yaqi Xie (6) Binhang Yuan (5)

Keywords

distributed learning (8) model compression (7) neural network (5) large language model (5) stochastic gradient descent (5) hyperparameter optimization (5) language model (4) convergence analysis (4) communication compression (4) vision-language model (4) bayesian optimization (3) foundation model (3) attention mechanism (3) few-shot learning (3) transfer learning (3) test-time adaptation (2) federated learning (2) multimodal learning (2) video understanding (2) domain adaptation (2)

Papers

Enhancing Visual Planning with Auxiliary Tasks and Multi-token Prediction WACV 2026
Enhancing Vision-Language Few-Shot Adaptation with Negative Learning WACV 2025
Differentially Private Analysis for Binary Response Models: Optimality, Estimation, and Inference ICML 2025
Improving Model Alignment Through Collective Intelligence of Open-Source Models ICML 2025
Speculative Prefill: Turbocharging TTFT with Lightweight and Training-Free Token Importance Estimation ICML 2025
Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models ICLR 2025
Scaling Instruction-tuned LLMs to Million-token Contexts via Hierarchical Synthetic Data Generation ICLR 2025
Mixture-of-Agents Enhances Large Language Model Capabilities ICLR 2025
ONLY: One-Layer Intervention Sufficiently Mitigates Hallucinations in Large Vision-Language Models ICCV 2025
InstructPart: Task-Oriented Part Segmentation with Instruction Reasoning ACL 2025
BASKET: A Large-Scale Video Dataset for Fine-Grained Skill Estimation CVPR 2025
Data Debugging with Shapley Importance over Machine Learning Pipelines ICLR 2024
Dual Prototype Evolving for Test-Time Generalization of Vision-Language Models NIPS 2024
OAM-TCD: A globally diverse dataset of high-resolution tree cover maps NIPS 2024
FM-Delta: Lossless Compression for Storing Massive Fine-tuned Foundation Models NIPS 2024
RedPajama: an Open Dataset for Training Large Language Models NIPS 2024
Concept-Guided Prompt Learning for Generalization in Vision-Language Models AAAI 2024
HiKER-SGG: Hierarchical Knowledge Enhanced Robust Scene Graph Generation CVPR 2024
A Simple LLM Framework for Long-Range Video Question-Answering EMNLP 2024
Mitigating Catastrophic Forgetting in Language Transfer via Model Merging EMNLP 2024
AntGPT: Can Large Language Models Help Long-term Action Anticipation from Videos? ICLR 2024
Effective and Efficient Federated Tree Learning on Hybrid Data ICLR 2024
Mechanistic Design and Scaling of Hybrid Architectures ICML 2024
OpenBox: A Python Toolkit for Generalized Black-box Optimization JMLR 2024
Object-Centric Video Representation for Long-Term Action Anticipation WACV 2024
Learning To Adapt CLIP for Few-Shot Monocular Depth Estimation WACV 2024
Contrastive Learning for Unsupervised Domain Adaptation of Time Series ICLR 2023
Self-Correctable and Adaptable Inference for Generalizable Human Pose Estimation CVPR 2023
Neuro-Modulated Hebbian Learning for Fully Test-Time Adaptation CVPR 2023
Goal-Conditioned Predictive Coding for Offline Reinforcement Learning NIPS 2023
Skill-it! A data-driven skills framework for understanding and training language models NIPS 2023
Laughing Hyena Distillery: Extracting Compact Recurrences From Convolutions NIPS 2023
DataPerf: Benchmarks for Data-Centric AI Development NIPS 2023
CocktailSGD: Fine-tuning Foundation Models over 500Mbps Networks ICML 2023
WordScape: a Pipeline to extract multilingual, visually rich Documents with Layout Annotations from Web Crawl Data NIPS 2023
FedHPO-Bench: A Benchmark Suite for Federated Hyperparameter Optimization ICML 2023
FlexGen: High-Throughput Generative Inference of Large Language Models with a Single GPU ICML 2023
Deja Vu: Contextual Sparsity for Efficient LLMs at Inference Time ICML 2023
Which Model To Transfer? Finding the Needle in the Growing Haystack CVPR 2022
ReforesTree: A Dataset for Estimating Tropical Forest Carbon Stock with Deep Learning and Aerial Imagery AAAI 2022
VF-PS: How to Select Important Participants in Vertical Federated Learning, Efficiently and Securely? NIPS 2022
Neural Methods for Logical Reasoning over Knowledge Graphs ICLR 2022
iFlood: A Stable and Effective Regularizer ICLR 2022
Certifying Out-of-Domain Generalization for Blackbox Functions ICML 2022
Fine-tuning Language Models over Slow Networks using Activation Quantization with Guarantees NIPS 2022
Decentralized Training of Foundation Models in Heterogeneous Environments NIPS 2022
Certifying Some Distributional Fairness with Subpopulation Decomposition NIPS 2022
Improving Certified Robustness via Statistical Learning with Logical Reasoning NIPS 2022
Multilingual Language Models Predict Human Reading Behavior NAACL 2021
Towards Automatic Bias Detection in Knowledge Graphs EMNLP 2021
Evolving Attention with Residual Convolutions ICML 2021
1-bit Adam: Communication Efficient Large-Scale Training with Adam’s Convergence Speed ICML 2021
Knowledge Enhanced Machine Learning Pipeline against Diverse Adversarial Attacks ICML 2021
DocParser: Hierarchical Document Structure Parsing from Renderings AAAI 2021
Knowledge Router: Learning Disentangled Representations for Knowledge Graphs NAACL 2021
Online Active Model Selection for Pre-trained Classifiers AISTATS 2021
TRS: Transferability Reduced Ensemble via Promoting Gradient Diversity and Model Smoothness NIPS 2021
Scalability vs. Utility: Do We Have To Sacrifice One for the Other in Data Importance Quantification? CVPR 2021
MFES-HB: Efficient Hyperband with Multi-Fidelity Quality Measurements AAAI 2021
Control, Generate, Augment: A Scalable Framework for Multi-Attribute Text Generation EMNLP 2020
Spectral Temporal Graph Neural Network for Multivariate Time-series Forecasting NIPS 2020
TextNAS: A Neural Architecture Search Space Tailored for Text Representation AAAI 2020
Learning to Mutate with Hypergradient Guided Population NIPS 2020
On Convergence of Nearest Neighbor Classifiers over Feature Transformations NIPS 2020
Don’t Waste Your Bits! Squeeze Activations and Gradients for Deep Neural Networks via TinyScript ICML 2020
Efficient Automatic CASH via Rising Bandits AAAI 2020
Topic Modeling on Document Networks with Adjacent-Encoder AAAI 2020
CogniVal in Action: An Interface for Customizable Cognitive Word Embedding Evaluation COLING 2020
CogniVal: A Framework for Cognitive Word Embedding Evaluation CONLL 2019
Is advance knowledge of flow sizes a plausible assumption? NSDI 2019
Entity Recognition at First Sight: Improving NER with Eye Movement Information NAACL 2019
DL2: Training and Querying Neural Networks with Logic ICML 2019
AutoML from Service Provider’s Perspective: Multi-device, Multi-tenant Model Selection with GP-EI AISTATS 2019
Towards Efficient Data Valuation Based on the Shapley Value AISTATS 2019
Distributed Learning over Unreliable Networks ICML 2019
Patient Risk Assessment and Warning Symptom Detection Using Deep Attention-Based Neural Networks EMNLP 2018
Communication Compression for Decentralized Training NIPS 2018
Layerwise Systematic Scan: Deep Boltzmann Machines and Beyond AISTATS 2018
ETH-DS3Lab at SemEval-2018 Task 7: Effectively Combining Recurrent and Convolutional Neural Networks for Relation Classification and Extraction SEMEVAL 2018
$D^2$: Decentralized Training over Decentralized Data ICML 2018
Asynchronous Decentralized Parallel Stochastic Gradient Descent ICML 2018
Can Decentralized Algorithms Outperform Centralized Algorithms? A Case Study for Decentralized Parallel Stochastic Gradient Descent NIPS 2017
ZipML: Training Linear Models with End-to-End Low Precision, and a Little Bit of Deep Learning ICML 2017
Cyclades: Conflict-free Asynchronous Machine Learning NIPS 2016
Rapidly Mixing Gibbs Sampling for a Class of Factor Graphs Using Hierarchy Width NIPS 2015
Taming the Wild: A Unified Analysis of Hogwild-Style Algorithms NIPS 2015
Parallel Feature Selection Inspired by Group Testing NIPS 2014
Understanding Tables in Context Using Standard NLP Toolkits ACL 2013
An Approximate, Efficient LP Solver for LP Rounding NIPS 2013
Big Data versus the Crowd: Looking for Relationships in All the Right Places ACL 2012