most citedPreP-OCR: A Complete Pipeline for Document Image Restoration and Enhanced OCR Accuracy

14 citations · 30 across the 12 of their papers we have counts for

collaborators
Showing cs.CLShow all

9 papers · 1 filter

cs.CL2025

Pretraining on the Test Set Is No Longer All You Need: A Debate-Driven Approach to QA Benchmarks

Linbo Cao, Jinman Zhao

As frontier language models increasingly saturate standard QA benchmarks, concerns about data contamination, memorization, and escalating dataset creation costs persist. We propose…

cs.CL2025★ 14 cited

PreP-OCR: A Complete Pipeline for Document Image Restoration and Enhanced OCR Accuracy

Shuhao Guan, Moule Lin, Cheng Xu +5

This paper introduces PreP-OCR, a two-stage pipeline that combines document image restoration with semantic-aware post-OCR correction to enhance both visual clarity and textual con…

cs.CL2025

UORA: Uniform Orthogonal Reinitialization Adaptation in Parameter-Efficient Fine-Tuning of Large Models

Xueyan Zhang, Jinman Zhao, Zhifei Yang +4

This paper introduces Uniform Orthogonal Reinitialization Adaptation (UORA), a novel parameter-efficient fine-tuning (PEFT) approach for Large Language Models (LLMs). UORA achieves…

cs.CL2024

Can Language Model Understand Word Semantics as A Chatbot? An Empirical Study of Language Model Internal External Mismatch

Jinman Zhao, Xueyan Zhang, Xingyu Yue +3

Current common interactions with language models is through full inference. This approach may not necessarily align with the model's internal knowledge. Studies show discrepancies…

cs.CL2024

LongRecipe: Recipe for Efficient Long Context Generalization in Large Language Models

Zhiyuan Hu, Yuliang Liu, Jinman Zhao +8

Large language models (LLMs) face significant challenges in handling long-context tasks because of their limited effective context window size during pretraining, which restricts t…

cs.CL2024

Role-Play Paradox in Large Language Models: Reasoning Performance Gains and Ethical Dilemmas

Jinman Zhao, Zifan Qian, Linbo Cao +5

Role-play in large language models (LLMs) enhances their ability to generate contextually relevant and high-quality responses by simulating diverse cognitive perspectives. However,…

cs.CL2024

MMREC: LLM Based Multi-Modal Recommender System

Jiahao Tian, Jinman Zhao, Zhenkai Wang +1

The importance of recommender systems is growing rapidly due to the exponential increase in the volume of content generated daily. This surge in content presents unique challenges…

cs.CL2024

Exploring the Limitations of Large Language Models in Compositional Relation Reasoning

Jinman Zhao, Xueyan Zhang

We present a comprehensive evaluation of large language models(LLMs)' ability to reason about composition relations through a benchmark encompassing 1,500 test cases in English, de…

cs.CL2024★ 9 cited

Gender Bias in Large Language Models across Multiple Languages

Jinman Zhao, Yitian Ding, Chen Jia +2

With the growing deployment of large language models (LLMs) across various applications, assessing the influence of gender biases embedded in LLMs becomes crucial. The topic of gen…