14 citations · 30 across the 12 of their papers we have counts for
12 papers
Staying in the Sweet Spot: Responsive Reasoning Evolution via Capability-Adaptive Hint Scaffolding
Ziheng Li, Zexu Sun, Jinman Zhao +8
Reinforcement learning with verifiable rewards (RLVR) has achieved remarkable success in enhancing the reasoning capabilities of large language models (LLMs). However, existing RLV…
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…
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…
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…
GPT-Signal: Generative AI for Semi-automated Feature Engineering in the Alpha Research Process
Yining Wang, Jinman Zhao, Yuri Lawryshyn
In the trading process, financial signals often imply the time to buy and sell assets to generate excess returns compared to a benchmark (e.g., an index). Alpha is the portion of a…
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…
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…
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,…
Data Imputation using Large Language Model to Accelerate Recommendation System
Zhicheng Ding, Jiahao Tian, Zhenkai Wang +2
This paper aims to address the challenge of sparse and missing data in recommendation systems, a significant hurdle in the age of big data. Traditional imputation methods struggle…
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…
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…
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…