18 papers
Hierarchical Evidence-Driven Reasoning for Long Document Understanding
Junyu Xiong, Yonghui Wang, Rongjian Gu +4
Retrieval-Augmented Generation (RAG) streamlines long-document understanding by leveraging retrieval mechanisms to restrict input images to a highly curated subset. However, existi…
CAGE-SGG: Counterfactual Active Graph Evidence for Open-Vocabulary Scene Graph Generation
Suiyang Guang, Chenyu Liu, Ruohan Zhang +1
Open-vocabulary scene graph generation (SGG) aims to describe visual scenes with flexible and fine-grained relation phrases beyond a fixed predicate vocabulary. While recent vision…
Prefix-Adaptive Block Diffusion for Efficient Document Recognition
Mingxu Chai, Ziyu Shen, Chenyu Liu +9
Block Diffusion Models (BDMs) support parallel generation, flexible-length output, and KV caching, making them promising for efficient document parsing. However, existing BDMs bind…
AppellateGen: A Benchmark for Appellate Legal Judgment Generation
Hongkun Yang, Lionel Z. Wang, Wei Fan +10
Legal judgment generation is a critical task in legal intelligence. However, existing research in legal judgment generation has predominantly focused on first-instance trials, rely…
TDATR: Improving End-to-End Table Recognition via Table Detail-Aware Learning and Cell-Level Visual Alignment
Chunxia Qin, Chenyu Liu, Pengcheng Xia +4
Tables are pervasive in diverse documents, making table recognition (TR) a fundamental task in document analysis. Existing modular TR pipelines separately model table structure and…
Kimi K2: Open Agentic Intelligence
Kimi Team, Yifan Bai, Yiping Bao +195
We introduce Kimi K2, a Mixture-of-Experts (MoE) large language model with 32 billion activated parameters and 1 trillion total parameters. We propose the MuonClip optimizer, which…