9 papers
FrameMorrow: Future-guided Frame Selection with Prospective Tokens for Long-Horizon Video Generation
Bo Yin, Xiaobin Hu, Jiaqi Zhao +1
Long-horizon video generation requires models to effectively leverage an increasingly long generation history. As the generated history grows, retaining all previous content become…
QuantWM: Temporally Consistent 2-Bit KV Cache Quantization for Video World Models
Jiaqi Zhao, Xiaobin Hu, Bo Yin +3
Video world models achieve long-range temporal consistency by storing KV cache during generation, but the growing cache makes KV cache memory a major deployment bottleneck, which m…
Beyond Shortcuts: Mitigating Visual Illusions in Frozen VLMs via Qualitative Reasoning
Hao Guo, Fei Wang, Junjie Chen +4
While Vision-Language Models (VLMs) have achieved state-of-the-art performance in general visual tasks, their perceptual robustness remains remarkably brittle when confronted with…
3D Smoke Scene Reconstruction Guided by Vision Priors from Multimodal Large Language Models
Xinye Zheng, Fei Wang, Yiqi Nie +5
Reconstructing 3D scenes from smoke-degraded multi-view images is particularly difficult because smoke introduces strong scattering effects, view-dependent appearance changes, and…
InfoMamba: An Attention-Free Hybrid Mamba-Transformer Model
Youjin Wang, Jiaqiao Zhao, Rong Fu +5
Balancing fine-grained local modeling with long-range dependency capture under computational constraints remains a central challenge in sequence modeling. While Transformers provid…
Boost Post-Training Quantization via Null Space Optimization for Large Language Models
Jiaqi Zhao, Miao Zhang, Deng Xiang +3
Existing post-training quantization methods for large language models (LLMs) offer remarkable success. However, the increasingly marginal performance gains suggest that existing qu…
PTQ1.61: Push the Real Limit of Extremely Low-Bit Post-Training Quantization Methods for Large Language Models
Jiaqi Zhao, Miao Zhang, Ming Wang +5
Large Language Models (LLMs) suffer severe performance degradation when facing extremely low-bit (sub 2-bit) quantization. Several existing sub 2-bit post-training quantization (PT…
Benchmarking Post-Training Quantization in LLMs: Comprehensive Taxonomy, Unified Evaluation, and Comparative Analysis
Jiaqi Zhao, Ming Wang, Miao Zhang +5
Post-training Quantization (PTQ) technique has been extensively adopted for large language models (LLMs) compression owing to its efficiency and low resource requirement. However,…
Temporal-Frequency State Space Duality: An Efficient Paradigm for Speech Emotion Recognition
Jiaqi Zhao, Fei Wang, Kun Li +4
Speech Emotion Recognition (SER) plays a critical role in enhancing user experience within human-computer interaction. However, existing methods are overwhelmed by temporal domain…