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20242026
most citedVisRAG: Vision-based Retrieval-augmented Generation on Multi-modality Documents

6 citations · 18 across the 24 of their papers we have counts for

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6 papers · 1 filter

math.PR2026

Supercritical sharpness for Ising double random currents

Trishen S. Gunaratnam, Christoforos Panagiotis, Romain Panis +1

We show that the percolation model induced by the double random current representation of the Ising model on , with , satisfies local uniqueness of the macros…

cs.CL2026

CheckRLM: Effective Knowledge-Thought Coherence Checking in Retrieval-Augmented Reasoning

Dingling Xu, Ruobing Wang, Qingfei Zhao +8

Reasoning Language Models (RLMs) have significantly improved performance on complex tasks by extending the reasoning chain. However, these chains are prone to containing factual er…

cs.CL2026

Student-in-the-Loop Chain-of-Thought Distillation via Generation-Time Selection

Chaoqun He, Yingfa Chen, Chaojun Xiao +2

Large reasoning models achieve strong performance on complex tasks through long chain-of-thought (CoT) trajectories, but directly transferring such reasoning processes to smaller m…

cs.CV2026

Cheers: Decoupling Patch Details from Semantic Representations Enables Unified Multimodal Comprehension and Generation

Yichen Zhang, Da Peng, Zonghao Guo +19

A recent cutting-edge topic in multimodal modeling is to unify visual comprehension and generation within a single model. However, the two tasks demand mismatched decoding regimes…

cs.CL2026

Hybrid Linear Attention Done Right: Efficient Distillation and Effective Architectures for Extremely Long Contexts

Yingfa Chen, Zhen Leng Thai, Zihan Zhou +6

Hybrid Transformer architectures, which combine softmax attention blocks and recurrent neural networks (RNNs), have shown a desirable performance-throughput tradeoff for long-conte…

cs.CV2026

APB-V: Accelerating Long-Video Understanding via Sequence-Parallelism-aware Approximate Attention

Yuxiang Huang, Mingye Li, Xu Han +7

The efficiency of long-video inference remains a critical bottleneck, mainly due to the dense computation in the prefill stage of Large Multimodal Models (LMMs). Existing methods e…