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

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cs.AI2026

MolRecBench-Wild: A Real-World Benchmark for Optical Chemical Structure Recognition

Haote Yang, Hui Wang, Chen Zhu +14

Optical Chemical Structure Recognition (OCSR) aims to translate molecular diagrams in scientific literature into machine-readable formats, but current systems remain unreliable on…

cs.AI2026

Tracing the Roots: A Multi-Agent Framework for Uncovering Data Lineage in Post-Training LLMs

Yu Li, Xiaoran Shang, Qizhi Pei +11

Post-training data plays a pivotal role in shaping the capabilities of Large Language Models (LLMs), yet datasets are often treated as isolated artifacts, overlooking the systemic…

cs.AI2026

GGBench: A Geometric Generative Reasoning Benchmark for Unified Multimodal Models

Jingxuan Wei, Caijun Jia, Xi Bai +7

The advent of Unified Multimodal Models (UMMs) signals a paradigm shift in artificial intelligence, moving from passive perception to active, cross-modal generation. Despite their…

cs.AI2026

GTR-CoT: Graph Traversal as Visual Chain of Thought for Molecular Structure Recognition

Jingchao Wang, Yifan He, Haote Yang +10

Optical Chemical Structure Recognition (OCSR) is essential for converting molecular images into machine-readable formats. While recent vision-language models (VLMs) have shown prom…

cs.AI2026

LRAS: Advanced Legal Reasoning with Agentic Search

Yujin Zhou, Chuxue Cao, Jinluan Yang +4

While Large Reasoning Models (LRMs) have demonstrated exceptional logical capabilities in mathematical domains, their application to the legal field remains hindered by the strict…

cs.AI2025

OpenDataArena: A Fair and Open Arena for Benchmarking Post-Training Dataset Value

Mengzhang Cai, Xin Gao, Yu Li +13

The rapid evolution of Large Language Models (LLMs) is predicated on the quality and diversity of post-training datasets. However, a critical dichotomy persists: while models are r…