activity
20242026
collaborators

16 papers

cs.CL2026

Imagination Helps Visual Reasoning, But Not Yet in Latent Space

You Li, Chi Chen, Yanghao Li +4

Latent visual reasoning aims to mimic human's imagination process by meditating through hidden states of Multimodal Large Language Models. While recognized as a promising paradigm…

cs.CV2026

Does Seeing More Mean Knowing More? Mono-Anchored Advantage Normalization for Multi-Source Visual Reasoning

Fanhu Zeng, Zhicong Luo, Zefan Wang +3

Visual reasoning through reinforcement learning with verifiable rewards (RLVR) has achieved remarkable progress. However, when dealing with multi-source inputs, existing approaches…

cs.CV2026

Unveiling Fine-Grained Visual Traces: Evaluating Multimodal Interleaved Reasoning Chains in Multimodal STEM Tasks

Jing Jin, Hao Liu, Yan Bai +9

Multimodal large language models (MLLMs) have shown promising reasoning abilities, yet evaluating their performance in specialized domains remains challenging. STEM reasoning is a…

cs.CV2026

CL-VISTA: Benchmarking Continual Learning in Video Large Language Models

Haiyang Guo, Yichen Shi, Fei Zhu +6

Video Large Language Models (Video-LLMs) require continual learning to adapt to non-stationary real-world data. However, existing benchmarks fall short of evaluating modern foundat…

cs.CV2026

Fine-Grained Post-Training Quantization for Large Vision Language Models with Quantization-Aware Integrated Gradients

Ziwei Xiang, Fanhu Zeng, Hongjian Fang +6

Large Vision Language Models (LVLMs) have achieved remarkable success in a range of downstream tasks that require multimodal interaction, but their capabilities come with substanti…

cs.IR2026

HyTRec: A Hybrid Temporal-Aware Attention Architecture for Long Behavior Sequential Recommendation

Lei Xin, Yuhao Zheng, Ke Cheng +3

Modeling long sequences of user behaviors has emerged as a critical frontier in generative recommendation. However, existing solutions face a dilemma: linear attention mechanisms a…