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20232026
most citedThe Rise and Potential of Large Language Model Based Agents: A Survey

256 citations · 279 across the 26 of their papers we have counts for

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7 papers · 1 filter

cs.CV2026

How Far Are We from Removing the Visual Encoder? Scaling Laws for Encoder-Free Multimodal Pretraining

Lin Chen, Bolin Ni, Qi Yang +6

Most modern multimodal large language models (MLLMs) build on a pretrained visual encoder that provides a strong visual prior. Encoder-free MLLMs instead learn visual representatio…

cs.CV2026

ChartE: A Comprehensive Benchmark for End-to-End Chart Editing

Shuo Li, Jiajun Sun, Zhekai Wang +9

Charts are a fundamental visualization format for structured data analysis. Enabling end-to-end chart editing according to user intent is of great practical value, yet remains chal…

cs.CV2026

MHA2MLA-VLM: Enabling DeepSeek's Economical Multi-Head Latent Attention across Vision-Language Models

Xiaoran Fan, Zhichao Sun, Tao Ji +2

As vision-language models (VLMs) tackle increasingly complex and multimodal tasks, the rapid growth of Key-Value (KV) cache imposes significant memory and computational bottlenecks…

cs.CV2025

The Role of Entropy in Visual Grounding: Analysis and Optimization

Shuo Li, Jiajun Sun, Zhihao Zhang +10

Recent advances in fine-tuning multimodal large language models (MLLMs) using reinforcement learning have achieved remarkable progress, particularly with the introduction of variou…

cs.CV2025

Mitigating Object Hallucinations in MLLMs via Multi-Frequency Perturbations

Shuo Li, Jiajun Sun, Guodong Zheng +10

Recently, multimodal large language models (MLLMs) have demonstrated remarkable performance in visual-language tasks. However, the authenticity of the responses generated by MLLMs…

cs.CV2024

Have the VLMs Lost Confidence? A Study of Sycophancy in VLMs

Shuo Li, Tao Ji, Xiaoran Fan +10

In the study of LLMs, sycophancy represents a prevalent hallucination that poses significant challenges to these models. Specifically, LLMs often fail to adhere to original correct…

cs.CV2024

MouSi: Poly-Visual-Expert Vision-Language Models

Xiaoran Fan, Tao Ji, Changhao Jiang +21

Current large vision-language models (VLMs) often encounter challenges such as insufficient capabilities of a single visual component and excessively long visual tokens. These issu…