13 papers
Proact-VL: A Proactive VideoLLM for Real-Time AI Companions
Weicai Yan, Yuhong Dai, Qi Ran +6
Proactive and real-time interactive experiences are essential for human-like AI companions, yet face three key challenges: (1) achieving low-latency inference under continuous stre…
Decoupling Stability and Plasticity for Multi-Modal Test-Time Adaptation
Yongbo He, Zirun Guo, Tao Jin
Adapting pretrained multi-modal models to evolving test-time distributions, known as multi-modal test-time adaptation, presents a significant challenge. Existing methods frequently…
Text-Guided Multi-Scale Frequency Representation Adaptation
Weicai Yan, Xinhua Ma, Wang Lin +1
Parameter-efficient fine-tuning methods introduce a small number of training parameters, enabling pre-trained models to adapt rapidly to new data distributions. While these methods…
Thinking with Programming Vision: Towards a Unified View for Thinking with Images
Zirun Guo, Minjie Hong, Feng Zhang +2
Multimodal large language models (MLLMs) that think with images can interactively use tools to reason about visual inputs, but current approaches often rely on a narrow set of tool…
Hybrid LLM and Higher-Order Quantum Approximate Optimization for CSA Collateral Management
Tao Jin, Stuart Florescu, Heyu +1
We address finance-native collateral optimization under ISDA Credit Support Annexes (CSAs), where integer lots, Schedule A haircuts, RA/MTA gating, and issuer/currency/class caps c…
LLM-I: LLMs are Naturally Interleaved Multimodal Creators
Zirun Guo, Feng Zhang, Kai Jia +1
We propose LLM-Interleaved (LLM-I), a flexible and dynamic framework that reframes interleaved image-text generation as a tool-use problem. LLM-I is designed to overcome the "one-t…