papers

Publications (9)

cs.CL2025

Mitigating Out-of-Entity Errors in Named Entity Recognition: A Sentence-Level Strategy

Guochao Jiang, Ziqin Luo, Chengwei Hu +2

Many previous models of named entity recognition (NER) suffer from the problem of Out-of-Entity (OOE), i.e., the tokens in the entity mentions of the test samples have not appeared…

cs.CL2025

ChineseEcomQA: A Scalable E-commerce Concept Evaluation Benchmark for Large Language Models

Haibin Chen, Kangtao Lv, Chengwei Hu +8

With the increasing use of Large Language Models (LLMs) in fields such as e-commerce, domain-specific concept evaluation benchmarks are crucial for assessing their domain capabilit…

cs.CV2023

Wavelet-based Fourier Information Interaction with Frequency Diffusion Adjustment for Underwater Image Restoration

Chen Zhao, Weiling Cai, Chenyu Dong +1

Underwater images are subject to intricate and diverse degradation, inevitably affecting the effectiveness of underwater visual tasks. However, most approaches primarily operate in…

cs.CL2025

AIR: Complex Instruction Generation via Automatic Iterative Refinement

Wei Liu, Yancheng He, Hui Huang +5

With the development of large language models, their ability to follow simple instructions has significantly improved. However, adhering to complex instructions remains a major cha…

cs.CL2024

Chinese SimpleQA: A Chinese Factuality Evaluation for Large Language Models

Yancheng He, Shilong Li, Jiaheng Liu +15

New LLM evaluation benchmarks are important to align with the rapid development of Large Language Models (LLMs). In this work, we present Chinese SimpleQA, the first comprehensive…

cs.AI2025

WiS Platform: Enhancing Evaluation of LLM-Based Multi-Agent Systems Through Game-Based Analysis

Chengwei Hu, Jianhui Zheng, Yancheng He +7

Recent advancements in autonomous multi-agent systems (MAS) based on large language models (LLMs) have enhanced the application scenarios and improved the capability of LLMs to han…

cs.IR2022

Improving Continual Relation Extraction through Prototypical Contrastive Learning

Chengwei Hu, Deqing Yang, Haoliang Jin +2

Continual relation extraction (CRE) aims to extract relations towards the continuous and iterative arrival of new data, of which the major challenge is the catastrophic forgetting…

cs.CV2026

AeSlides: Incentivizing Aesthetic Layout in LLM-Based Slide Generation via Verifiable Rewards

Yiming Pan, Chengwei Hu, Xuancheng Huang +6

Large language models (LLMs) have demonstrated strong potential in agentic tasks, particularly in slide generation. However, slide generation poses a fundamental challenge: the gen…

cs.LG2026

GLM-5: from Vibe Coding to Agentic Engineering

GLM-5-Team, :, Aohan Zeng +184

We present GLM-5, a next-generation foundation model designed to transition the paradigm of vibe coding to agentic engineering. Building upon the agentic, reasoning, and coding (AR…