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20242026
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cs.CL2026

GLM-OCR Technical Report

Shuaiqi Duan, Yadong Xue, Weihan Wang +20

GLM-OCR is an efficient 0.9B-parameter compact multimodal model designed for real-world document understanding. It combines a 0.4B-parameter CogViT visual encoder with a 0.5B-param…

cs.CL2025

AlignMMBench: Evaluating Chinese Multimodal Alignment in Large Vision-Language Models

Yuhang Wu, Wenmeng Yu, Yean Cheng +5

Evaluating the alignment capabilities of large Vision-Language Models (VLMs) is essential for determining their effectiveness as helpful assistants. However, existing benchmarks pr…

cs.CL2025

ComplexFuncBench: Exploring Multi-Step and Constrained Function Calling under Long-Context Scenario

Lucen Zhong, Zhengxiao Du, Xiaohan Zhang +2

Enhancing large language models (LLMs) with real-time APIs can help generate more accurate and up-to-date responses. However, evaluating the function calling abilities of LLMs in r…

cs.CL2024

AutoWebGLM: A Large Language Model-based Web Navigating Agent

Hanyu Lai, Xiao Liu, Iat Long Iong +8

Large language models (LLMs) have fueled many intelligent web agents, but most existing ones perform far from satisfying in real-world web navigation tasks due to three factors: (1…

cs.CL2024

AlignBench: Benchmarking Chinese Alignment of Large Language Models

Xiao Liu, Xuanyu Lei, Shengyuan Wang +15

Alignment has become a critical step for instruction-tuned Large Language Models (LLMs) to become helpful assistants. However, the effective evaluation of alignment for emerging Ch…

cs.CL2024

NaturalCodeBench: Examining Coding Performance Mismatch on HumanEval and Natural User Prompts

Shudan Zhang, Hanlin Zhao, Xiao Liu +6

Large language models (LLMs) have manifested strong ability to generate codes for productive activities. However, current benchmarks for code synthesis, such as HumanEval, MBPP, an…