Wenxuan Huang

Orcid: 0009-0001-9656-813X

Affiliations:
  • East China Normal University, School of Computer Science and Technology, Shanghai, China


According to our database1, Wenxuan Huang authored at least 14 papers between 2023 and 2025.

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

Timeline

Legend:

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Bibliography

2025
AgentGroupChat-V2: Divide-and-Conquer Is What LLM-Based Multi-Agent System Need.
CoRR, June, 2025

Scientists' First Exam: Probing Cognitive Abilities of MLLM via Perception, Understanding, and Reasoning.
CoRR, June, 2025

MT<sup>3</sup>: Scaling MLLM-based Text Image Machine Translation via Multi-Task Reinforcement Learning.
CoRR, May, 2025

CompBench: Benchmarking Complex Instruction-guided Image Editing.
CoRR, May, 2025

ReactDance: Progressive-Granular Representation for Long-Term Coherent Reactive Dance Generation.
CoRR, May, 2025

TimeSoccer: An End-to-End Multimodal Large Language Model for Soccer Commentary Generation.
CoRR, April, 2025

VCR-Bench: A Comprehensive Evaluation Framework for Video Chain-of-Thought Reasoning.
CoRR, April, 2025

LLaVA-RadZ: Can Multimodal Large Language Models Effectively Tackle Zero-shot Radiology Recognition?
CoRR, March, 2025

Vision-R1: Incentivizing Reasoning Capability in Multimodal Large Language Models.
CoRR, March, 2025

An Intelligent First-Arrival Picking Method of Microseismic Signals Based on the Small Sample Expansion.
IEEE Trans. Geosci. Remote. Sens., 2025

Dynamic-LLaVA: Efficient Multimodal Large Language Models via Dynamic Vision-language Context Sparsification.
Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Weakly Supervised Semantic Segmentation via Progressive Confidence Region Expansion.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025

2024
A General and Efficient Training for Transformer via Token Expansion.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023
Filter Pruning for Efficient CNNs via Knowledge-driven Differential Filter Sampler.
CoRR, 2023


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