Zifeng Wang

Orcid: 0000-0002-0068-9042

Affiliations:
  • Google Cloud AI Research, Mountain View, CA, USA
  • Northeastern University, Department of Electrical and Computer Engineering, Boston, MA, USA (PhD)


According to our database1, Zifeng Wang authored at least 42 papers between 2018 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

Online presence:

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Bibliography

2025
Enabling Flexible Multi-LLM Integration for Scalable Knowledge Aggregation.
CoRR, May, 2025

PlanGEN: A Multi-Agent Framework for Generating Planning and Reasoning Trajectories for Complex Problem Solving.
CoRR, February, 2025

Heterogeneous Swarms: Jointly Optimizing Model Roles and Weights for Multi-LLM Systems.
CoRR, February, 2025

When One LLM Drools, Multi-LLM Collaboration Rules.
CoRR, February, 2025

SAIF: Sparse Adversarial and Imperceptible Attack Framework.
Trans. Mach. Learn. Res., 2025

ADAPT to Robustify Prompt Tuning Vision Transformers.
Trans. Mach. Learn. Res., 2025

Reverse Thinking Makes LLMs Stronger Reasoners.
Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies, 2025

Speculative Knowledge Distillation: Bridging the Teacher-Student Gap Through Interleaved Sampling.
Proceedings of the Thirteenth International Conference on Learning Representations, 2025

STAR: Stability-Inducing Weight Perturbation for Continual Learning.
Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Speculative RAG: Enhancing Retrieval Augmented Generation through Drafting.
Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Magnet: Multi-turn Tool-use Data Synthesis and Distillation via Graph Translation.
Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

In Prospect and Retrospect: Reflective Memory Management for Long-term Personalized Dialogue Agents.
Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

2024
SQL-PaLM: Improved large language model adaptation for Text-to-SQL.
Trans. Mach. Learn. Res., 2024

Model Swarms: Collaborative Search to Adapt LLM Experts via Swarm Intelligence.
CoRR, 2024

TableRAG: Million-Token Table Understanding with Language Models.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

CodecLM: Aligning Language Models with Tailored Synthetic Data.
Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2024, 2024

Chain-of-Table: Evolving Tables in the Reasoning Chain for Table Understanding.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

LMDX: Language Model-based Document Information Extraction and Localization.
Proceedings of the Findings of the Association for Computational Linguistics, 2024

CaLM: Contrasting Large and Small Language Models to Verify Grounded Generation.
Proceedings of the Findings of the Association for Computational Linguistics, 2024

Found in the middle: Calibrating Positional Attention Bias Improves Long Context Utilization.
Proceedings of the Findings of the Association for Computational Linguistics, 2024

2023
DualHSIC: HSIC-Bottleneck and Alignment for Continual Learning.
Proceedings of the International Conference on Machine Learning, 2023

QueryForm: A Simple Zero-shot Form Entity Query Framework.
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

2022
Deep Learning on Multimodal Sensor Data at the Wireless Edge for Vehicular Network.
IEEE Trans. Veh. Technol., 2022

Radio Frequency Fingerprinting on the Edge.
IEEE Trans. Mob. Comput., 2022

Deep Bayesian Unsupervised Lifelong Learning.
Neural Networks, 2022

SAIF: Sparse Adversarial and Interpretable Attack Framework.
CoRR, 2022

SparCL: Sparse Continual Learning on the Edge.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Pruning Adversarially Robust Neural Networks without Adversarial Examples.
Proceedings of the IEEE International Conference on Data Mining, 2022

DualPrompt: Complementary Prompting for Rehearsal-Free Continual Learning.
Proceedings of the Computer Vision - ECCV 2022, 2022

Learning to Prompt for Continual Learning.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021
Improved prediction of smoking status via isoform-aware RNA-seq deep learning models.
PLoS Comput. Biol., 2021

Revisiting Hilbert-Schmidt Information Bottleneck for Adversarial Robustness.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Deep Learning on Visual and Location Data for V2I mmWave Beamforming.
Proceedings of the 17th International Conference on Mobility, Sensing and Networking, 2021

2020
Deep Learning for RF Fingerprinting: A Massive Experimental Study.
IEEE Internet Things Mag., 2020

Instance-wise Feature Grouping.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Open-World Class Discovery with Kernel Networks.
Proceedings of the 20th IEEE International Conference on Data Mining, 2020

Learn-Prune-Share for Lifelong Learning.
Proceedings of the 20th IEEE International Conference on Data Mining, 2020

2019
Adaptive Nonparametric Variational Autoencoder.
CoRR, 2019

Impairment Shift Keying: Covert Signaling by Deep Learning of Controlled Radio Imperfections.
Proceedings of the 2019 IEEE Military Communications Conference, 2019

Finding a 'New' Needle in the Haystack: Unseen Radio Detection in Large Populations Using Deep Learning.
Proceedings of the 2019 IEEE International Symposium on Dynamic Spectrum Access Networks, 2019

2018
Profiling users by online shopping behaviors.
Multim. Tools Appl., 2018

Collaborative Deep Reinforcement Learning for Multi-object Tracking.
Proceedings of the Computer Vision - ECCV 2018, 2018


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