collaborators

8 papers

cs.AI2026

Offline-Online Curriculum RL for Multimodal Reasoning

Wendi Deng, Hang Du, Guoshun Nan +11

Multimodal large language models exhibit capabilities on reasoning tasks, yet often produce flawed intermediate steps while yielding correct final answers. This behavior undermines…

cs.IR2026

Uncertainty as Remedy: Mitigating Satisfaction Label Bias in Short Video Multi-Objective Ensemble Ranking

Zonghe Shao, Tiantian He, Xiaoxiao Xu +6

The core objective of short video recommendation is to model users' unobservable true satisfaction with recommended videos. As the dominant industrial framework, end-to-end multi-o…

cs.CL2026

SentGuard: Sentence-Level Streaming Guardrails for Large Language Models

Jiaqi Yu, Xin Wang, Yixu Wang +4

Large language models increasingly stream long, reasoning-intensive responses in real time, making when to moderate as critical as whether to moderate. Existing guardrails fall int…

cs.LG2026

S2Aligner: Pair-Efficient and Transferable Pre-Training for Sparse Text-Attributed Graphs

Yuhan Wang, Haopeng Zhang, Yibo Ding +6

Pre-training on text-attributed graphs (TAGs) is central to building transferable graph foundation models, where LLM-as-Aligner methods align graph and text representations through…

cs.CV2026

TAME: Test-Time Adversarial Prompt Tuning via Mixture-of-Experts for Vision-Language Models

Xin Wang, Yixu Wang, Jiaming Zhang +6

Large-scale pre-trained Vision-Language models (VLMs), such as CLIP, exhibit strong zero-shot generalization, yet remain highly vulnerable to imperceptible adversarial perturbation…

cs.CV2026

LDDR: Linear-DPP-Based Dynamic-Resolution Frame Sampling for Video MLLMs

Jingfeng Chen, Jiawen Qian, Wendi Deng +5

Video understanding in multimodal large language models requires selecting informative frames from long, redundant videos under limited visual-token budgets. Existing methods often…