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Chengqi Dong

2 accepted papers

2026

LazyVAR: Accelerating Visual Autoregressive Models via Scale-wise Token Pruning and Parallel Group Decoding

CVPR 2026

Visual Autoregressive (VAR) modeling introduces a new paradigm for image generation by extending autoregressive mechanisms from next-token prediction to next-scale prediction, achieving remarkable performance. However, as the number of tokens increases rapidly with scale, processing full token maps

Cited by 0SourceScholar
2026

Promoting Efficient Reasoning with Verifiable Stepwise Reward

AAAI 2026technical

Large reasoning models (LRMs) have recently achieved significant progress in complex reasoning tasks, aided by reinforcement learning with verifiable rewards. However, LRMs often suffer from overthinking, expending excessive computation on simple problems and reducing efficiency. Existing efficient

Cited by 0SourcePDFScholar