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cs.AI2026

DNAlign: Dynamic Null-Space Safe Alignment for LLMs

Jisheng Dang, Yushuo Zhao, Dewei Liu +6

Ensuring the safe and reliable deployment of large language models (LLMs) remains a fundamental challenge. Existing safety alignment approaches either incur high computational cost…

cs.AI2026

MVFA: A Multi-View Text-Guided Multimodal Fusion LLM Adapter for Sentiment Analysis and Emotion Recognition

Pengfei Shao, Jisheng Dang, Jiawen Fang +7

Multimodal sentiment analysis and emotion recognition in conversations demand effective modeling of heterogeneous interactions across textual, acoustic, and visual modalities. Alth…

cs.AI2026

PhysMLLMs: Spatial Priors for Unified Referring Segmentation and Grounded Reasoning of Images and Videos

Siyao Yan, Bo Han, Jisheng Dang +7

Video multimodal large language models support language guided video segmentation, but they often show spatio temporal inconsistencies, e.g., jitter, drift, and identity switches.…

cs.AI2026

AffectOmni: RL-Verifiable People-Centric Grounded Affective Reasoning for Social and Art-Related Scenes

Yibo Wang, Rui Yang, Jisheng Dang +7

Multimodal large language models (MLLMs) achieve strong performance on VQA and scene understanding, yet affective reasoning remains vulnerable to shortcut behavior. Models may pred…

cs.AI2026

MODF-SIR: A Multi-agent Omni-modal Distilled Framework for Social Intelligence Reasoning

Shang Ma, Jisheng Dang, Wencan Zhang +6

We propose a multi-agent collaborative framework built upon a lightweight Multimodal Large Language Model (MLLM), specifically designed for social intelligence reasoning. A key fea…