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From the 1 of 21 linked papers with an AI index.

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20242026
most citedMinerU2.5-Pro: Pushing the Limits of Data-Centric Document Parsing at Scale

1 citations · 1 across the 4 of their papers we have counts for

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cs.CL2024

ANAH-v2: Scaling Analytical Hallucination Annotation of Large Language Models

Yuzhe Gu, Ziwei Ji, Wenwei Zhang +3

Large language models (LLMs) exhibit hallucinations in long-form question-answering tasks across various domains and wide applications. Current hallucination detection and mitigati…

cs.CL2024

Training Language Models to Critique With Multi-agent Feedback

Tian Lan, Wenwei Zhang, Chengqi Lyu +6

Critique ability, a meta-cognitive capability of humans, presents significant challenges for LLMs to improve. Recent works primarily rely on supervised fine-tuning (SFT) using crit…

cs.CL2024

CriticEval: Evaluating Large Language Model as Critic

Tian Lan, Wenwei Zhang, Chen Xu +4

Critique ability, i.e., the capability of Large Language Models (LLMs) to identify and rectify flaws in responses, is crucial for their applications in self-improvement and scalabl…

cs.CL2024

Scaling Behavior for Large Language Models regarding Numeral Systems: An Example using Pythia

Zhejian Zhou, Jiayu Wang, Dahua Lin +1

Though Large Language Models (LLMs) have shown remarkable abilities in mathematics reasoning, they are still struggling with performing numeric operations accurately, such as addit…

cs.AI2024

LEAN-GitHub: Compiling GitHub LEAN repositories for a versatile LEAN prover

Zijian Wu, Jiayu Wang, Dahua Lin +1

Recently, large language models have presented promising results in aiding formal mathematical reasoning. However, their performance is restricted due to the scarcity of formal the…

cs.CL2024

InternLM-Law: An Open Source Chinese Legal Large Language Model

Zhiwei Fei, Songyang Zhang, Xiaoyu Shen +9

While large language models (LLMs) have showcased impressive capabilities, they struggle with addressing legal queries due to the intricate complexities and specialized expertise r…