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Peiran Yin

Rescuing Your Pruning: Rethinking Visual Token Pruning and Post-Training Recovery in MLLMs
2026 · Yin, Peiran, Wu, Hao, et al. · arXiv (Cornell University)
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ReInsVLN: Revisiting Historical Evidence for Training-Free Vision-and-Language Navigation
2026 · Cheng, Siwei, Wu, Hao, et al. · arXiv (Cornell University)
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Bifocal: Training-Free Mixed Granularity Visual Token Pruning for Multimodal LLMs
2026 · Yin, Peiran, Wu, Hao, et al. · arXiv (Cornell University)
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GeoGR: Spatial-Semantic Token Compression and Group Routing for Efficient 3D VLMs
2026 · Zheng, Yongxin, Wu, Hao, et al. · arXiv (Cornell University)
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MWOP: Modality-aware Width-wise Operation Pruning for Efficient MLLMs
2026 · Wang, Xudong, Wu, Hao, et al. · arXiv (Cornell University)
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WIDE: Boosting Adaptive LLM Inference via Token-level Dynamic Width Pruning
2026 · Hu, Haozhe, Wu, Hao, et al. · arXiv (Cornell University)
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From Static Inference to Dynamic Interaction: A Survey of Streaming Large Language Models
2026 · Tong, Junlong, Wang, Zilong, et al. · arXiv (Cornell University)
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Beyond FLOPs: Benchmarking Real Inference Acceleration of LLM Pruning under a GEMM-Centric Taxonomy
2026 · Haozhe Hu, Hao Wu, et al. · Conference on Empirical Methods in Natural Language Processing (EMNLP)
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From Static Inference to Dynamic Interaction: A Survey of Streaming Large Language Models
2026 · Junlong Tong, Zilong Wang, et al. · Findings of the Association for Computational Linguistics: ACL (Findings of ACL)
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Works count: 9
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