activity
20242026
collaborators

6 papers

cs.CV2026

HG-Bench: A Benchmark for Multi-Page Handwritten Answer-Region Grounding in Automated Homework Assessment

Chuangxin Zhao, Boyan Shi, Yanling Wang +7

Automated homework assessment depends not only on recognizing student answers, but also on accurately locating where each answer and each intermediate reasoning step appears in noi…

cs.CV2026

An LMM for Precisely Grounding Elements in Documents

Yijian Lu, Chuangxin Zhao, Kai Sun +3

Visual grounding in documents is a crucial ability for Large Multimodal Models (LMMs) in areas such as document understanding, deep research and document error detection. However,…

cs.CV2026

GLM-5V-Turbo: Toward a Native Foundation Model for Multimodal Agents

V Team, Wenyi Hong, Xiaotao Gu +94

We present GLM-5V-Turbo, a step toward native foundation models for multimodal agents. As foundation models are increasingly deployed in real environments, agentic capability depen…

cs.CL2025

Can LLM Watermarks Robustly Prevent Unauthorized Knowledge Distillation?

Leyi Pan, Aiwei Liu, Shiyu Huang +5

The radioactive nature of Large Language Model (LLM) watermarking enables the detection of watermarks inherited by student models when trained on the outputs of watermarked teacher…

cs.CL2025

WaterSeeker: Pioneering Efficient Detection of Watermarked Segments in Large Documents

Leyi Pan, Aiwei Liu, Yijian Lu +6

Watermarking algorithms for large language models (LLMs) have attained high accuracy in detecting LLM-generated text. However, existing methods primarily focus on distinguishing fu…

cs.CR2024

MarkLLM: An Open-Source Toolkit for LLM Watermarking

Leyi Pan, Aiwei Liu, Zhiwei He +9

LLM watermarking, which embeds imperceptible yet algorithmically detectable signals in model outputs to identify LLM-generated text, has become crucial in mitigating the potential…