activity
20092026
most citedDynamic Sparse Training: Find Efficient Sparse Network From Scratch With Trainable Masked Layers

27 citations · 151 across the 26 of their papers we have counts for

collaborators

34 papers

cs.CL2026

Efficient Reasoning Exploration via State-Conditioned Latent Steering with Progress Guidance

Hengyuan Zhang, Chenming Shang, Zunhai Su +10

Best-of- is a widely used inference strategy for complex reasoning, whose effectiveness depends on whether sampled candidates can cover diverse and high-quality reasoning paths.…

cs.CV2026

Towards Memory-Efficient Autoregressive Video Generation via Instance-Specific Parametric Absorption

Xiaomeng Fu, Jia Li, Yiming Hu +5

Autoregressive (AR) streaming models have emerged as a powerful paradigm for long video generation. However, the linearly growing Key-Value (KV) cache poses a significant bottlenec…

cs.CV2026

Learning to See through Illumination Extremes with Event Streaming in Multimodal Large Language Models

Baoheng Zhang, Jiahui Liu, Gui Zhao +7

Multimodal Large Language Models (MLLMs) perform strong vision-language reasoning under standard conditions but fail in extreme illumination, where RGB inputs lose irrevocable stru…

cs.CV2026

Residual Decoding: Mitigating Hallucinations in Large Vision-Language Models via History-Aware Residual Guidance

Xinrong Chen, Xu Chu, Yingmin Qiu +8

Large Vision-Language Models (LVLMs) can reason from image-text inputs and perform well in various multimodal tasks. Despite this success, they are affected by language priors and…

cs.LG2026

Beyond Outliers: A Data-Free Layer-wise Mixed-Precision Quantization Approach Driven by Numerical and Structural Dual-Sensitivity

Hengyuan Zhang, Xinrong Chen, Zunhai Su +10

Layer-wise mixed-precision quantization (LMPQ) enables effective compression under extreme low-bit settings by allocating higher precision to sensitive layers. However, existing me…

cs.CV2026

Train Short, Inference Long: Training-free Horizon Extension for Autoregressive Video Generation

Jia Li, Xiaomeng Fu, Xurui Peng +7

Autoregressive video diffusion models have emerged as a scalable paradigm for long video generation. However, they often suffer from severe extrapolation failure, where rapid error…