collaborators

10 papers

cs.CV2026

RotateAttention: RoPE-Aware Rotation and Range Rectification for INT4 Quantized Attention in Video Generation

Yaofu Liu, Wanli Lan, Jinxi Li +2

In , the attention mechanism remains a primary computational bottleneck due to its…

cs.CL2026

Re:Form -- Reducing Human Annotations in Scalable Formal Software Verification with RL in LLMs: A Preliminary Study on Dafny

Chuanhao Yan, Fengdi Che, Xuhan Huang +12

Existing informal language-based (e.g., human language) Large Language Models (LLMs) trained with Reinforcement Learning (RL) face a significant challenge: their verification proce…

cs.PL2026

VeriEquivBench: An Equivalence Score for Ground-Truth-Free Evaluation of Formally Verifiable Code

Lingfei Zeng, Fengdi Che, Xuhan Huang +4

Formal verification is the next frontier for ensuring the correctness of code generated by Large Language Models (LLMs). While methods that co-generate code and formal specificatio…

cs.CV2026

Synthesizing Multimodal Geometry Datasets from Scratch and Enabling Visual Alignment via Plotting Code

Haobo Lin, Tianyi Bai, Chen Chen +4

Multimodal geometry reasoning requires models to jointly understand visual diagrams and perform structured symbolic inference, yet current vision--language models struggle with com…

cs.LG2025

VADE: Variance-Aware Dynamic Sampling via Online Sample-Level Difficulty Estimation for Multimodal RL

Zengjie Hu, Jiantao Qiu, Tianyi Bai +5

Group-based policy optimization methods like GRPO and GSPO have become standard for training multimodal models, leveraging group-wise rollouts and relative advantage estimation. Ho…

cs.CL2025

UltraLLaDA: Scaling the Context Length to 128K for Diffusion Large Language Models

Guangxin He, Shen Nie, Fengqi Zhu +6

Diffusion LLMs have attracted growing interest, with plenty of recent work emphasizing their great potential in various downstream tasks; yet the long-context behavior of diffusion…