Zhenheng Tang
Orcid: 0000-0001-8769-9974
According to our database1,
Zhenheng Tang
authored at least 48 papers
between 2019 and 2025.
Collaborative distances:
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Bibliography
2025
RouteMark: A Fingerprint for Intellectual Property Attribution in Routing-based Model Merging.
CoRR, August, 2025
AnTKV: Anchor Token-Aware Sub-Bit Vector Quantization for KV Cache in Large Language Models.
CoRR, June, 2025
Can Compressed LLMs Truly Act? An Empirical Evaluation of Agentic Capabilities in LLM Compression.
CoRR, May, 2025
CoRR, April, 2025
The Lottery LLM Hypothesis, Rethinking What Abilities Should LLM Compression Preserve?
CoRR, February, 2025
DreamDDP: Accelerating Data Parallel Distributed LLM Training with Layer-wise Scheduled Partial Synchronization.
CoRR, February, 2025
Mediator: Memory-efficient LLM Merging with Less Parameter Conflicts and Uncertainty Based Routing.
CoRR, February, 2025
CoRR, February, 2025
ChunkKV: Semantic-Preserving KV Cache Compression for Efficient Long-Context LLM Inference.
CoRR, February, 2025
Hot-pluggable Federated Learning: Bridging General and Personalized FL via Dynamic Selection.
Proceedings of the Thirteenth International Conference on Learning Representations, 2025
Proceedings of the Thirteenth International Conference on Learning Representations, 2025
Proceedings of the 30th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, 2025
MegaAgent: A Large-Scale Autonomous LLM-based Multi-Agent System Without Predefined SOPs.
Proceedings of the Findings of the Association for Computational Linguistics, 2025
Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025
2024
ExpertFlow: Optimized Expert Activation and Token Allocation for Efficient Mixture-of-Experts Inference.
CoRR, 2024
FusionLLM: A Decentralized LLM Training System on Geo-distributed GPUs with Adaptive Compression.
CoRR, 2024
FuseFL: One-Shot Federated Learning through the Lens of Causality with Progressive Model Fusion.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024
Bandwidth-Aware and Overlap-Weighted Compression for Communication-Efficient Federated Learning.
Proceedings of the 53rd International Conference on Parallel Processing, 2024
Pruner-Zero: Evolving Symbolic Pruning Metric From Scratch for Large Language Models.
Proceedings of the Forty-first International Conference on Machine Learning, 2024
Proceedings of the Twelfth International Conference on Learning Representations, 2024
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024
VMRNN: Integrating Vision Mamba and LSTM for Efficient and Accurate Spatiotemporal Forecasting.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024
2023
GossipFL: A Decentralized Federated Learning Framework With Sparsified and Adaptive Communication.
IEEE Trans. Parallel Distributed Syst., March, 2023
Reliable and Efficient In-Memory Fault Tolerance of Large Language Model Pretraining.
CoRR, 2023
FusionAI: Decentralized Training and Deploying LLMs with Massive Consumer-Level GPUs.
CoRR, 2023
FedML Parrot: A Scalable Federated Learning System via Heterogeneity-aware Scheduling on Sequential and Hierarchical Training.
CoRR, 2023
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023
2022
Virtual Homogeneity Learning: Defending against Data Heterogeneity in Federated Learning.
Proceedings of the International Conference on Machine Learning, 2022
2021
IEEE Netw., 2021
2020
Communication-Efficient Distributed Deep Learning: Survey, Evaluation, and Challenges.
CoRR, 2020
CoRR, 2020
Communication-Efficient Decentralized Learning with Sparsification and Adaptive Peer Selection.
Proceedings of the 40th IEEE International Conference on Distributed Computing Systems, 2020
Layer-Wise Adaptive Gradient Sparsification for Distributed Deep Learning with Convergence Guarantees.
Proceedings of the ECAI 2020 - 24th European Conference on Artificial Intelligence, 29 August-8 September 2020, Santiago de Compostela, Spain, August 29 - September 8, 2020, 2020
Benchmarking the Performance and Energy Efficiency of AI Accelerators for AI Training.
Proceedings of the 20th IEEE/ACM International Symposium on Cluster, 2020
2019
A Convergence Analysis of Distributed SGD with Communication-Efficient Gradient Sparsification.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019
A Distributed Synchronous SGD Algorithm with Global Top-k Sparsification for Low Bandwidth Networks.
Proceedings of the 39th IEEE International Conference on Distributed Computing Systems, 2019
The Impact of GPU DVFS on the Energy and Performance of Deep Learning: an Empirical Study.
Proceedings of the Tenth ACM International Conference on Future Energy Systems, 2019
Computer-Aided Clinical Skin Disease Diagnosis Using CNN and Object Detection Models.
Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019