most citedDo LLMs "Feel"? Emotion Circuits Discovery and Control

2 citations · 2 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV2026

Dual-Pathway Geometry-Aware MLLM for Spatial Intelligence

Yufei Zheng, Xuhan Zhu, Zide Liu +9

Spatial understanding of the physical world from 2D visual inputs hinges on two complementary forms of geometric knowledge: holistic 3D structural perception and fine-grained metri…

cs.CV2026

Self-Consistent Latent Reasoning: Long Latent Sequence Reasoning for Vision-Language Model

Chenfeng Wang, Wei He, Xuhan Zhu +10

In language reasoning, longer chains of thought consistently yield better performance, which naturally suggests that visual latent reasoning may likewise benefit from longer latent…

cs.CV2026

StreamingClaw Technical Report

Jiawei Chen, Zhe Chen, Chaoqun Du +21

Emerging applications such as embodied intelligence, AI hardware, autonomous driving, and intelligent cockpits rely on a real-time perception-decision-action closed loop, posing st…

cs.CV2025

MindGPT-4ov: An Enhanced MLLM via a Multi-Stage Post-Training Paradigm

Wei Chen, Chaoqun Du, Feng Gu +14

We present MindGPT-4ov, a multimodal large language model (MLLM) that introduces a general post-training paradigm spanning data production, model training, and efficient deployment…

cs.CL2025★ 2 cited

Do LLMs "Feel"? Emotion Circuits Discovery and Control

Chenxi Wang, Yixuan Zhang, Ruiji Yu +8

As the demand for emotional intelligence in large language models (LLMs) grows, a key challenge lies in understanding the internal mechanisms that give rise to emotional expression…

cs.CV2025

Robust Prompt Tuning for Vision-Language Models with Mild Semantic Noise

Yansheng Gao, Yufei Zheng, Shengsheng Wang

Prompt tuning has shown promising results, but its robustness and generalization to unseen categories remain limited. Through our experiments, we demonstrate that the complete remo…