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20232026
most citedA Theoretical Understanding of Self-Correction through In-context Alignment

3 citations · 7 across the 19 of their papers we have counts for

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6 papers · 1 filter

cs.LG2026

A Theoretical Framework for Masked Pretraining (MPT)

Qi Zhang, Runyu Zhou, Yifei Wang +1

Recently, Masked Pretraining (MPT) based on reconstruction pretraining tasks has risen to a promising self-supervised learning paradigm across various domains and achieves remarkab…

cs.LG2026

Beyond the Next Step: Variable-Length Latent World Models for Long-Horizon Planning

Tianqi Du, Qi Zhang, Yifei Wang +1

Recently, world models have emerged as a promising paradigm for building intelligent agents by learning predictive models that estimate future environment states conditioned on obs…

cs.IR2026

No More K-means: Single-Stage Sparse Coding for Efficient Multi-Vector Retrieval

Lixuan Guo, Yifei Wang, Tiansheng Wen +3

Multi-vector retrieval (MVR) models, exemplified by ColBERT, have established new benchmarks in retrieval accuracy by preserving fine-grained token-level interactions. However, thi…

cs.DC2026

Optimus: Elastic Decoding for Efficient Diffusion LLM Serving

Chiyue Wei, Cong Guo, Bowen Duan +7

Large language model (LLM) serving is fundamentally limited by inefficient hardware utilization. Autoregressive (AR) decoding underutilizes GPUs due to its strictly sequential exec…

cs.LG2026

Scaling Attention via Feature Sparsity

Yan Xie, Tiansheng Wen, Tangda Huang +4

Scaling Transformers to ultra-long contexts is bottlenecked by the cost of self-attention. Existing methods reduce this cost along the sequence axis through local window…

cs.CV2026

StreamingEval: A Unified Evaluation Protocol towards Realistic Streaming Video Understanding

Guowei Tang, Tianwen Qian, Huanran Zheng +2

Real-time, continuous understanding of visual signals is essential for real-world interactive AI applications, and poses a fundamental system-level challenge. Existing research on…